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M2090-615 - IBM Business Analytics Performance Management Sales Mastery Test v2 - Dump Information

Vendor : IBM
Exam Code : M2090-615
Exam Name : IBM Business Analytics Performance Management Sales Mastery Test v2
Questions and Answers : 47 Q & A
Updated On : February 20, 2019
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M2090-615 Questions and Answers

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M2090-615 IBM Business Analytics Performance Management Sales Mastery Test v2

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M2090-615 exam Dumps Source : IBM Business Analytics Performance Management Sales Mastery Test v2

Test Code : M2090-615
Test Name : IBM Business Analytics Performance Management Sales Mastery Test v2
Vendor Name : IBM
Q&A : 47 Real Questions

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IBM IBM Business Analytics Performance

IBM Db2 Analytics Accelerator version 7.1 — efficiency with stronger Flexibility | killexams.com Real Questions and Pass4sure dumps

businesses possess a wealth of beneficial facts on their commercial enterprise techniques. Ideally, decisions should still be derived from this statistics as it’s generated to assist today’s actual-time company needs. Deriving insight from out of date records can cause poor first-class decisions and probably hazardous moves. This could enable fraud and cyber criminals to take advantage of that statistics and the systems. It could also outcome in misplaced salary through missed earnings alternatives. in a similar way, the identical could be referred to of not being capable of analyze facts quick satisfactory.

IBM Db2 Analytics Accelerator for z/OS (Accelerator) can assist tackle each of those challenges. initially, it allows for queries to be carried out on current transactional data with little or no affect to operational device efficiency. Secondly, the Accelerator can work to greatly enrich the efficiency of applicable queries typically found in analytics purposes.

The Accelerator is designed for high-velocity evaluation of enterprise records. it will probably aid reduce operational can charge and complexity with the aid of bringing the analytics closer to the information and enabling close actual-time analytics on transactional statistics because it’s generated. The Accelerator transforms the IBM Z platform right into a hybrid transaction and analytical processing (HTAP) atmosphere. it could actually carry excessive-speed processing for complex, aid-intensive Db2 queries to guide business-crucial reporting and analytic workloads.

Flexibility and performance with Db2 Analytics Accelerator edition 7.1

The Accelerator has been available for a couple of years and is used through IBM Z valued clientele across many industries to aid speed complicated queries on company-critical records, while not having to move that records to a distinct platform for analytics. Executing transaction and analytical workloads simultaneously on the identical platform can support reduce latency whereas leveraging the security capabilities of the IBM Z platform. Analytical processing does not degrade transactional workload performance as a result of transactional and analytical queries are each and every processed within separate compute aid pools.

As depicted in figure #1, the Db2 Analytics Accelerator edition 7.1 gives you two deployment options, both on the IBM built-in Analytics gadget (IAS) and/or without delay on the IBM Z mainframe.

determine #1: dedicated equipment (Accelerator on IAS) or Native on IBM Z (Accelerator on IBM Z) choosing the right choice

The Db2 Analytics Accelerator for z/OS version 7.1 gives the choice to set up the form aspect that most closely fits a company’s requirements:

  • Db2 Analytics Accelerator on IAS makes it possible for corporations to install on the IBM integrated Analytics equipment equipment. This pre-configured offering comprises hardware (compute, storage, and networking) and utility for easy deployment, administration, and excessive performance. It additionally offers safety-rich, flexible and elastic facts storage that is both easy to install and control.
  • Db2 Analytics Accelerator on IBM Z makes it possible for corporations to set up directly on the IBM Z mainframe, within a cozy service Container leveraging integrated Facility for Linux (IFL) processors. This allows for deeper integration with the IBM Z infrastructure. This choice can also present flexible capacity to respond to peak analytic workload necessities while assembly SLAs. It supports a subset of SQL, executable in Db2 for z/OS. Basing the Accelerator on Db2 Warehouse enables accelerated use of the supported SQL on account of superior SQL compatibility across the Db2 family.
  • both deployment alternate options are in keeping with IBM’s analytical engine, Db2 Warehouse. This helps guarantee a uniform adventure with one API and database engine. It makes it possible for groups to invest once in enabling their applications and workloads for the Accelerator after which transition comfortably between deployment options. The IBM Db2 Warehouse gives here advantages:

  • more advantageous SQL compatibility across the total Db2 family of products.
  • Columnar technology providing quicker performance for many analytic queries than outdated models.
  • Containerized strategy can facilitate sooner, easier integration with different technologies and tactics.
  • Deployment on IAS

    IBM Db2 Analytics Accelerator on IAS is a next-era hardware equipment. It gives its add-ons out of the field, including optimized hardware and software. This deployment alternative supplies a balanced, advanced, performance-optimized configuration. The hardware comprises the rack, the actual servers and storage. it's based on IBM vigour hardware and is optimized for expense/performance. The software stack comprises the Linux working device, Docker software, Docker container and infrastructure administration amenities.

    Deployment on IBM Z

    IBM Db2 Analytics Accelerator on IBM Z circumstances may also be deployed at once via a down load & go approach. Deploying the Accelerator on IBM Z programs the application stack into an IBM comfy carrier Container (SSC) logical partition (LPAR). This helps carry a self-managed equipment running in a SSC LPAR that can be deployed in minutes.

    distinctive comfortable service Containers can share the same IFLs. distinct Accelerators, hence, can share the identical hardware supplies. This can also be a good suggestion for a few construction, and examine/construction situations, which may well be provisioned and re-provisioned as vital.

    The Accelerator on IBM Z integrates into a company’s IBM Z environment and leverages the widely used LPAR-reminiscence and CPU management approaches. This method additionally leverages the organization’s personal disk to save Accelerator-aspect facts. This alternative is for businesses that are looking to take knowledge of IBM Z amenities for actions such as disaster restoration and enables for deeper integration with the IBM Z infrastructure.

    abstract and next Steps

    When true-time insight matters, IBM Z, along with Db2 for z/OS and the Db2 Analytics Accelerator, can support deliver an impressive transaction and analytical ambiance.

    it could actually support corporations take potential of their enterprise facts the place it originates to work to pressure high influence choices whereas minimizing latency, simplifying infrastructure, assisting to in the reduction of the cost of such IT infrastructure and enhancing statistics security. it will possibly assist flip statistics into perception, and perception into opportunity to give close real-time solutions to some of the most vital questions.

    To study extra about IBM Db2 Analytics Accelerator edition 7.1, click on right here.

    Stephen Astorino,VP of development, Hybrid Cloud, z Analytics and Canada Lab Director IBM Analytics

    observe me: @astorino_steven


    IBM Db2 question Optimization the use of AI | killexams.com Real Questions and Pass4sure dumps

    In September 2018, IBM introduced a brand new product, IBM Db2 AI for z/OS. This artificial intelligence engine monitors facts entry patterns from executing SQL statements, makes use of computing device getting to know algorithms to pick out most desirable patterns and passes this guidance to the Db2 question optimizer to be used by means of subsequent statements.

    computing device discovering on the IBM z Platform

    In might also of 2018, IBM introduced edition 1.2 of its computer discovering for z/OS (MLz) product. this is a hybrid zServer and cloud software suite that ingests efficiency records, analyzes and builds models that symbolize the health popularity of a variety of indications, monitors them over time and gives precise-time scoring capabilities.

    a couple of points of this product providing are geared toward assisting a community of mannequin builders and bosses. as an example:

  • It supports distinctive programming languages similar to Python, Scala and R. This permits records modelers and scientists to make use of a language with which they are established;
  • A graphical person interface known as the visual mannequin Builder courses mannequin builders with out requiring highly-technical programming talents;
  • It includes dissimilar dashboards for monitoring mannequin effects and scoring capabilities, as well as controlling the system configuration.
  • This laptop getting to know suite became in the beginning aimed at zServer-based analytics purposes. one of the crucial first evident decisions become zSystem efficiency monitoring and tuning. gadget administration Facility (SMF) statistics which are immediately generated by means of the operating gadget supply the uncooked data for equipment useful resource consumption reminiscent of principal processor utilization, I/O processing, memory paging and so forth. IBM MLz can bring together and shop these statistics over time, and build and educate fashions of equipment behavior, score these behaviors, establish patterns now not simply foreseen through people, boost key performance warning signs (KPIs) after which feed the mannequin outcomes lower back into the equipment to have an effect on equipment configuration changes that may enrich efficiency.

    The subsequent step turned into to put in force this suite to investigate Db2 performance records. One answer, known as the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the desktop studying technology to Db2 operational records to gain an figuring out of Db2 subsystem fitness. it may well dynamically construct baselines for key performance indicators, supply a dashboard of those KPIs and provides operational team of workers actual-time perception into Db2 operations.

    whereas widespread Db2 subsystem performance is a crucial ingredient in general software health and performance, IBM estimates that the DBA help team of workers spends 25% or more of its time, " ... fighting entry course complications which cause efficiency degradation and service affect.". (See Reference 1).

    AI involves Db2

    accept as true with the plight of contemporary DBAs in a Db2 environment. In modern day IT world they need to guide one or more huge statistics applications, cloud application and database functions, utility setting up and configuration, Db2 subsystem and application performance tuning, database definition and management, disaster recovery planning, and more. query tuning has been in existence given that the origins of the database, and DBAs are always tasked with this as well.

    The heart of question course analysis in Db2 is the Optimizer. It accepts SQL statements from functions, verifies authority to access the facts, studies the areas of the objects to be accessed and develops a listing of candidate statistics access paths. These access paths can include indexes, table scans, quite a few table be a part of strategies and others. within the statistics warehouse and big facts environments there are usually additional decisions accessible. One of these is the existence of abstract tables (now and again called materialized query tables) that include pre-summarized or aggregated information, as a consequence permitting Db2 to evade re-aggregation processing. a further choice is the starjoin entry course, ordinary within the facts warehouse, the place the order of desk joins is modified for performance causes.

    The Optimizer then reports the candidate access paths and chooses the entry path, "with the bottom charge." charge during this context ability a weighted summation of useful resource usage including CPU, I/O, memory and different substances. finally, the Optimizer takes the bottom can charge access course, stores it in reminiscence (and, optionally, in the Db2 listing) and starts entry course execution.

    massive records and data warehouse operations now consist of utility suites that permit the business analyst to make use of a graphical interface to construct and manipulate a miniature facts mannequin of the statistics they wish to analyze. The applications then generate SQL statements based on the users’ requests.

    The problem for the DBA

    with the intention to do first rate analytics in your distinct statistics outlets you need an excellent realizing of the statistics requirements, an figuring out of the analytical capabilities and algorithms available and a excessive-performance statistics infrastructure. sadly, the number and location of facts sources is increasing (both in size and in geography), data sizes are growing to be, and applications proceed to proliferate in quantity and complexity. How may still IT managers support this environment, particularly with probably the most experienced and mature staff nearing retirement?

    take into account additionally that a large a part of decreasing the overall cost of ownership of those techniques is to get Db2 purposes to run faster and extra effectively. This constantly translates into the usage of fewer CPU cycles, doing fewer I/Os and transporting less statistics across the community. in view that it is often problematic to even identify which purposes might advantage from performance tuning, one approach is to automate the detection and correction of tuning concerns. here is the place desktop learning and artificial intelligence can be used to excellent effect.

    Db2 12 for z/OS and synthetic Intelligence

    Db2 version 12 on z/OS uses the desktop studying facilities outlined above to gather and store SQL query text and entry course particulars, as well as exact performance-related old tips equivalent to CPU time used, elapsed instances and outcomes set sizes. This providing, described as Db2 AI for z/OS, analyzes and stores the facts in machine learning fashions, with the model analysis results then being scored and made accessible to the Db2 Optimizer. The next time a scored SQL observation is encountered, the Optimizer can then use the mannequin scoring records as input to its entry path option algorithm.

    The result should still be a reduction in CPU consumption as the Optimizer makes use of model scoring input to choose superior access paths. This then lowers CPU charges and speeds software response instances. a big abilities is that the usage of AI software doesn't require the DBA to have statistics science talents or deep insights into query tuning methodologies. The Optimizer now chooses the top-quality access paths based mostly now not handiest on SQL question syntax and facts distribution records but on modelled and scored ancient efficiency.

    This may also be especially crucial if you save information in varied locations. for example, many analytical queries against massive facts require concurrent access to definite facts warehouse tables. These tables are generally referred to as dimension tables, and that they contain the records facets constantly used to manage subsetting and aggregation. as an example, in a retail environment agree with a table referred to as StoreLocation that enumerates every keep and its region code. Queries against save sales statistics may are looking to combination or summarize sales by using place; hence, the StoreLocation desk will be used with the aid of some large facts queries. in this atmosphere it's commonplace to take the dimension tables and replica them constantly to the huge records application. in the IBM world this place is the IBM Db2 Analytics Accelerator (IDAA).

    Now think about SQL queries from each operational applications, statistics warehouse users and large records business analysts. From Db2's perspective, all these queries are equal, and are forwarded to the Optimizer. besides the fact that children, in the case of operational queries and warehouse queries they may still absolutely be directed to entry the StoreLocation table within the warehouse. nevertheless, the question from the business analyst towards big information tables should doubtless entry the replica of the table there. This effects in a proliferations of talents entry paths, and more work for the Optimizer. fortunately, Db2 AI for z/OS can give the Optimizer the information it must make sensible entry direction decisions.

    the way it Works

    The sequence of pursuits in Db2 AI for z/OS (See Reference 2) is frequently right here:

  • all the way through a bind, rebind, put together or explain operation, an SQL statement is passed to the Optimizer;
  • The Optimizer chooses the facts access route; as the alternative is made, Db2 AI captures the SQL syntax, access path choice and query performance records (CPU used, and so forth.) and passes it to a "getting to know assignment";
  • The gaining knowledge of project, which will also be completed on a zIIP processor (a non-popular-goal CPU core that does not ingredient into utility licensing prices), interfaces with the laptop getting to know application (MLz model functions) to store this counsel in a mannequin;
  • as the amount of data in every model grows, the MLz Scoring provider (which can also be accomplished on a zIIP processor) analyzes the mannequin data and rankings the behavior;
  • all through the subsequent bind, rebind, put together or clarify, the Optimizer now has access to the scoring for SQL models, and makes appropriate alterations to access path selections.
  • There are also quite a lot of user interfaces that supply the administrator visibility to the popularity of the collected SQL commentary efficiency information and model scoring.

    abstract

    IBM's desktop researching for zOS (MLz) providing is getting used to exceptional effect in Db2 edition 12 to enrich the efficiency of analytical queries in addition to operational queries and their linked functions. This requires administration attention, as you must examine that your company is ready to consume these ML and AI conclusions. How will you measure the expenses and advantages of the usage of computer researching? Which IT support group of workers have to be tasked to reviewing the effect of model scoring, and perhaps approving (or overriding) the consequences? How will you overview and justify the assumptions that the utility makes about access direction selections?

    In different phrases, how smartly did you know your statistics, its distribution, its integrity and your current and proposed entry paths? this can verify where the DBAs spend their time in assisting analytics and operational utility efficiency.

    # # #

    Reference 1

    John Campbell, IBM Db2 individual EngineerFrom "IBM Db2 AI for z/OS: increase IBM Db2 software efficiency with desktop getting to know"https://www.worldofdb2.com/activities/ibm-db2-ai-for-z-os-raise-ibm-db2-utility-performance-with-ma

    Reference 2

    Db2 AI for z/OShttps://www.ibm.com/help/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html

    See all articles by means of Lockwood Lyon


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    Absolutdata items and services carry scalable enterprise have an effect on throughout the business by way of combining leading edge AI and ML with its heritage in analytical frameworks, enterprise realizing and expertise. Absolutdata's NAVIK AI Platform has pre-constructed solutions, customizable solutions, and enabling functions to get an commercial enterprise AI-competent. The growing set of AI-powered SaaS options encompass NAVIK SalesAI, NAVIK MarketingAI, NAVIK ResearchAI and NAVIK MicroMods. The features groups build custom options in response to NAVIK AI. headquartered in 2001, Absolutdata is based in San Francisco and employs 450 specialists across workplaces in San Francisco, big apple, Chicago, London, Singapore, Dubai and Gurgaon. For extra information talk over with the Absolutdata site, examine our weblog, and observe us on LinkedIn and Twitter. www.absolutdata.com.

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    Analytics Beyond Spreadsheets

    For many years, Microsoft Excel and other spreadsheets were the tools of choice for business professionals who were looking to visualize their data. But spreadsheets had their limits for many business intelligence (BI)-related tasks. Even today, trying to creating charts analyzing complex datasets in Excel can still be frustrating. Sometimes you start with the wrong kind of data, for example, or you may not know how to manipulate the spreadsheet to create the data visualization{{/ZIFFARTICLE} you need. On the other hand, the rising tide of data democratization is giving everyone in an organization access to corporate data. The need has arisen for effective tools that people of all skill levels can use to make sense of the wealth of information created by businesses every single day.

    Spreadsheets also fall down when the data isn't well-structured or can't be sorted out in neat rows and columns. And, if you have millions of rows or very sparse matrices, then the data in a spreadsheet can be painful to enter and it can be hard to visualize your data. Spreadsheets also have issues if you are trying to create a report that spans multiple data tables or that mixes in Structured Query Language (SQL)-based databases, or when multiple users try to maintain and collaborate on the same spreadsheet.

    A spreadsheet containing up-to-the-minute data can also be a problem, particularly if you have exported graphics that need to be refreshed when the data changes. Finally, spreadsheets aren't good for data exploration; trying to spot trends, outlying data points, or counterintuitive results is difficult when what you are looking for is often hidden in a long row of numbers.

    While spreadsheets and self-service BI tools both make use of tables of numbers, they are really acting in different arenas with different purposes. A spreadsheet is first and foremost a way to store and display calculations. While some spreadsheets can create very sophisticated mathematical models, at their core it is all about the math more than the model itself.

    This is all a long-winded way of saying that when businesses use a spreadsheet, they are actively sabotaging themselves and their ability to consistently get valuable insights from their data. BI tools are specficially designed to help businesses better understand their data, and can prove to be a huge benefit to those upgrading from what a limited spreadsheet can do.

    What Is Business Intelligence?

    Defining BI is tricky. When you examine what it does and why companies use it, it can start to sound vague and nebulous. After all, many different kinds of software offer analytics features, and all businesses want to improve. Understanding what a BI is or isn't can be unclear.

    BI is an umbrella term meant to cover all of the activities necessary for a company to turn raw information into actionable knowledge. In other words, it's a company's efforts to understand what it knows and what it doesn't know of its own existence and operations. The ultimate goal is being able to increase profits and sharpen its competitive edge.

    Framed that way, BI as a concept has been around as long as business. But that concept has evolved from early basics [like Accounts Payable (AP) and Accounts Receivable (AR) reports and customer contact and contract information] to much more sophisticated and nuanced information. This information ranges across everything from customer behaviors to IT infrastructure monitoring to even long-term fixed asset performance. Separately tracking such metrics is something most businesses can do regardless of the tools employed. Combining them, especially disparate results from metrics normally not associated with one another, into understandable and actionable information, well, that's the art of BI. The future of BI is already shaping up to simultaneously broaden the scope and variety of data used and to sharpen the micro-focus to ever finer, more granular levels.

    BI software has been instrumental in this steady progression towards more in-depth knowledge about the business, competitors, customers, industry, market, and suppliers, to name just a few possible metric targets. But as businesses grow and their information stores balloon, the capturing, storing, and organizing of information becomes too large and complex to be entirely handled by mere humans. Early efforts to do these tasks via software, such as customer relationship management (CRM) and enterprise resource planning (ERP), led to the formation of "data silos" wherein data was trapped and useful only within the confines of certain operations or software buckets. This was the case unless IT took on the task of integrating various silos, typically through painstaking and highly manual processes.

    While BI software still covers a variety of software applications used to analyze raw data, today it usually refers to analytics for data mining, analytical processing, querying, reporting, and especially visualizing. The main difference between today's BI software and Big Data analytics is mostly scale. BI software handles data sizes typical for most organizations, from small to large. Big Data analytics and apps handle data analysis for very large data sets, such as silos measured in petabytes (PBs).

    Self-Service BI and Data Democratization

    The BI tools that were popular half a decade or more ago required specialists, not just to use but also to interpret the resulting data and conclusions. That led to an often inconvenient and fallible filter between the people who really needed to get and understand the business—the company decision makers—and those who were gathering, processing, and interpreting that data—usually data analysts and database administrators. Because being a data specialist is a demanding job, many of these folks were less well-versed in the actual workings of the business whose data they were analyzing. That led to a focus on data the company didn't need, a misinterpretation of results, and often a series of "standard" reporting that analysts would run on a scheduled basis instead of more ad hoc intelligence gathering and interpretation, which can be highly valuable in fast-moving situations.

    This problem has led to a growing new trend among new BI tools coming onto the market today: that of self-service BI and data democratization. The goal for much of today's BI software is to be available and usable by anyone in the organization. Instead of requesting reports or queries through the IT or database departments, executives and decision makers can create their own queries, reports, and data visualizations through self-service models, and connect to disparate data both within and outside the organization through prebuilt connectors. IT maintains overall control over who has access to which tools and data through these connectors and their management tool arsenal, but IT no longer acts as a bottleneck to every query and report request.

    As a result, users can take advantage of this distributed BI model. Key tools and critical data have moved from a centralized and difficult-to-access architecture to a decentralized model that merely requires access credentials and familiarity with new BI software. This results in a whole new kind of analysis becoming available to the organization, namely, that of experienced, front-line business people who not only know what data they need but how they need to use it.

    The emerging crop of BI tools all work hard at developing front-end tools that are more intuitive and easier to use than those of older generations—with varying degrees of success. However, that means a key criteria in any BI tool purchasing decision will be to evaluate who in the organization should access such tools and whether the tool is appropriately designed for that audience. Most BI vendors indicate they're looking for their tool suites to become as ubiquitous and easy to use for business users as typical business collaboration tools or productivity suites, such as Microsoft Office. None have gotten quite that far yet in my estimation, but some are closer than others. To that end, these BI tool suites tend to focus on three core types of analytics: descriptive (what did happen), prescriptive (what should happen now), and predictive (what will happen later).

    What Is Data Visualization?

    In the context of BI software, data visualization is a fast and effective method of transferring information from a machine to a human brain. The idea is to place digital information into a visual context so that the analytic output can be quickly ingested by humans, often at a glance. If this sounds like those pie and bar charts you've seen in Microsoft Excel, then you're right. Those are early examples of data visualizations.

    But today's visualization forms are rapidly evolving from those traditional pie charts to the stylized, the artistic, and even the interactive. An interactive visualization comes with layered "drill downs," which means the viewer can interact with the visual to reach more granular information on one or more aspects incorporated in the bigger picture. For example, new values can be added that will change the visualization on the fly, or the visualization is actually built on rapidly changing data that can turn a static visual into an animation or a dashboard.

    The best visualizations do not seek artistic awards but instead are designed with function in mind, usually the quick and intuitive transfer of information. In other words, the best visualizations are simple but powerful in clearly and directly delivering a message. High-end visuals may look impressive at first glance but, if your audience needs help to understand what's being conveyed, then they've ultimately failed.

    Most BI software, including those reviewed here, comes with visualization capabilities. However, some products offer more options than others so, if advanced visuals are key to your BI process, then you'll want to closely examine these tools. There are also third-party and even free data visualization tools that can be used on top of your BI software for even more options.

    Products and Testing

    In this review roundup, I tested each product from the perspective of a business analyst. But I also kept in mind the viewpoint of users who might have no familiarity with data processing or analytics. I loaded and used the same data sets and posed the same queries, evaluating results and the processes involved.

    My aim was to evaluate cloud versions alone, as I often do analysis on the fly or at least on a variety of machines, as do legions of other analysts. But, in some cases, it was necessary to evaluate a desktop version as well or instead of the cloud version. One example of this is Tableau Desktop, a favorite tool of Microsoft Excel users who simply have an affinity for the desktop tool (and who just move to the cloud long enough to share and collaborate).

    I ended up testing the Microsoft Power BI desktop version, too, on a Microsoft representative's recommendation because, as the rep said, "the more robust data prep tools are there." Besides, said the rep, "most users prefer the desktop tool over a web tool anyway." Again, I don't doubt Microsoft's claim but that does seem weird to me. I've heard it said that desktop tools are preferred when the data is local as the process feels faster and easier. But seriously, how much data is truly local anymore? I suspect this odd desktop tool preference is a bit more personal than fact-based, but to each his own.

    Then there's Google Analytics, a pure cloud player. The tool is designed to analyze website and mobile app data so it's a different critter in the BI app zoo. That being the case, I had to deviate from using my test data set and queries, and instead test it in its natural habitat of website data. Nonetheless, it's the processes that are evaluated in this review, not the data.

    While I didn't test any of these tools from a data scientist's role, I did mention advanced capabilities when I found them, simply to let buyers know they exist. IBM Watson Analytics is one tool with the ability to extend to highly advanced features and was also one of the easiest to use upfront. IBM Watson Analytics is well-suited for business analysts and for widespread data democratization because it requires little, if any, knowledge of data science. Instead, it works well by using natural language and keywords to form queries, a characteristic that can make it valuable to practically anyone. It's highly intuitive, very powerful, and easy to learn. Microsoft Power BI is a strong second as it, too, is powerful while also familiar, certainly to any of the millions of Microsoft business users. However, there are several other powerful and intuitive apps in this lineup from which to choose; they all have their own pros and cons. We'll be adding even more in the coming months.

    One thing to watch out for during your evaluations of these products is that many don't yet handle streaming data. For many users, that won't be a problem in the immediate future. However, for those involved with analyzing business processes as they happen, such as website performance metrics or customer behavior patterns, streaming data can be invaluable. Also, the Internet of Things (IoT) will drive this issue in the near future and make streaming data and streaming analytics a must-have feature. Many of these tools will have to up their game accordingly so, unless you want to jump ship in a year or two, it's best to think ahead when considering BI and the IoT.

    BI and Big Data

    Another area in which self-service BI is taking off is in analyzing Big Data. This is a newer development in the database space but it's driving tremendous growth and innovation. The name is an apt descriptor because Big Data generally refers to huge data sets that are simply too big to be managed or queried with traditional data science tools. What's created these behemoth data collections is the explosion of data-generating, tracking, monitoring, transaction, and social media tools (to name a few) that have become so popular over the last several years.

    Not only do these tools generate loads of new data, they also often generate a new kind of data, namely "unstructured" data. Broadly speaking, this is simply data that hasn't been organized in a predefined way. Unlike more traditional, structured data, this kind of data is heavy on text (even free-form text) while also containing more easily defined data, such as dates or credit card numbers. Examples of apps that generate this kind of data include the customer behavior-tracking tools you use to see what your customers are doing on your e-commerce website, the piles of log and event files generated from some smart devices (such as alarms and smart sensors), and broad-swath social media tracking tools.

    Organizations deploying these tools are being challenged not only by a sudden deluge of unstructured data that quickly strains storage resources [think beyond terabytes (TB) into the PB and even exabyte (EB) range] but, even more importantly, they're finding it difficult to query this new information at all. Traditional data warehouse tools generally weren't designed to either manage or query unstructured data. New data storage innovations such as data lakes are emerging to solve for this need, but organizations still relying exclusively on traditional tools while deploying front-line apps that generate unstructured data often find themselves sitting on mountains of data they don't know how to leverage.

    Enter Big Data analysis standards. The golden standard here is Hadoop, which is an open-source software framework that Apache specifically designed to query large data sets stored in a distributed fashion (meaning, in your data center, the cloud, or both). Not only does Hadoop let you query Big Data, it lets you simultaneously query both unstructured as well as traditional structured data. In other words, if you want to query all of your business data for maximum insight, then Hadoop is what you need.

    You can download and implement Hadoop itself to perform your queries, but it's typically easier and more effective to use commercial querying tools that employ Hadoop as the foundation of more intuitive and full-featured analysis packages. Notably, most of the tools reviewed here, including Chartio, IBM Watson Analytics, Microsoft Power BI, and Tableau Desktop, all support this. However, each requires varying levels of configuration or even add-on tools to do so—with IBM, Microsoft, and Tableau offering exceptionally deep capabilities. However, both IBM and Microsoft will still expect customers to utilize additional tools around aspects such as data governance to ensure optimal performance.

    Finding the Right BI Tool

    Given the issues spreadsheets can have when used as ad hoc BI tools and how firmly ingrained they are in our psyches, finding the right BI tool isn't a simple process. Unlike spreadsheets, BI tools have major differences when it comes to how they consume data inputs and outputs and manipulate their tables. Some tools are better at exploration than analysis, and some require a fairly steep learning curve to really make use of their features. Finally, to make matters worse, there are dozens if not hundreds of such tools on the market today, with many vendors willing to claim the self-serve BI label even if it doesn't quite fit.

    Getting the overall workflow down with these tools will take some study and discussion with the people you'll be designating as users. Tableau Desktop and Microsoft Power BI, for example, will start users out with the desktop version to build visualizations and link up to various data sources. Once you have this together, you can start sharing those results online or across your organization's network. With others, such as Chartio or Google Analytics, you start in the cloud and stay there.

    In recent years, companies have been taking advantage of the wide selection of online learning platforms out there to train their employees on using these platforms. As intuitive as these platforms may be, it is important to make sure that your employees actually know how to use these BI platforms so that you can make sure your investment was worthwhile. There are many ways of approaching this, but using the right online learning platform might be a good place to start looking.

    Given the wide price range of these products, you should segment your analytics needs before you make any buying decision. If you want to start out slowly and inexpensively, then the best route is to try something that offers significant functionality for free, such as Microsoft Power BI. Such tools are very affordable and make it easy to get started. Plus, they tend to have large ecosystems of add-ons and partners that can be a cost-effective replacement for doing BI inside a spreadsheet. Tableau Desktop still has the largest collection of charts and visualizations and the biggest partner network, though both IBM Watson Analytics and Microsoft Power BI are catching up fast.

    IBM Watson Analytics scored the highest, and Microsoft Power BI and Tableau Desktop scored the next highest in our roundup. However, all three products received our Editors' Choice award. Tableau Desktop may have a big price tag depending on which version you choose but, as previously mentioned, it has an exceptionally large and growing collection of visualizations plus a manageable learning curve if you're willing to devote some effort to it. Microsoft Power BI and Tableau Desktop also have large and growing collections of data connectors, and both Microsoft and Tableau have their own sizable communities of users that are vocal about their wants and needs. This can carry a lot of weight with the vendors' development teams so it's a good idea to spend some time looking through those community forums to get an idea where these companies are headed.

  • Pros: Extremely user-friendly. Fantastic automatic report generation. Impressive support availability.

    Cons: Automated reports can quickly become defaults. Steep learning curve that might confuse beginners.

    Bottom Line: Zoho Reports is a solid option for general business users who might not be knowledgeable in analytics software. It's also available at an attractive price.

    Read Review
  • Pros: Accessible user interface. Smart guidance features. Impressively fast analytics. Robust natural language querying.

    Cons: Unable to do real-time streaming analytics.

    Bottom Line: IBM Watson Analytics is an exceptional business intelligence (BI) app that offers a strong analytics engine along with an excellent natural language querying tool. This is one of the best BI platforms you'll find and easily takes our Editors' Choice honor.

    Read Review
  • Pros: Extremely powerful platform with a wealth of data source connectors. Very user-friendly. Exceptional data visualization capabilities.

    Cons: Desktop and web versions divide data prep tools. Refresh cycle is limited on free version.

    Bottom Line: Microsoft Power BI earns our Editors' Choice honor for its impressive usability, top-notch data visualization capabilities, and superior compatibility with other Microsoft Office products.

    Read Review
  • Pros: Enormous collection of data connectors and visualizations. User-friendly design. Impressive processing engine. Mature product with a large community of users.

    Cons: Full mastery of the platform will require substantial training.

    Bottom Line: Tableau Desktop is one of the most mature offerings on the market and that shows in its feature set. While it has a steeper learning curve than other platforms, it's easily one of the best tools in the space.

    Read Review
  • Pros: Bottlenecks are eliminated thanks to in-chip processing. Impressive natural language query in third-party applications.

    Cons: Might be too difficult for self-service business intelligence (BI). Analytics process still needs to be ironed out. Natural language capability can be limited.

    Bottom Line: Sisense is a complete platform that should be popular for experienced BI users. It may fall short for beginners, however.

    Read Review
  • Pros: Wide range of connectors. Impressive sharing features. Limitless data storage.

    Cons: User interface is not intuitive. Steep learning curve. Unwelcoming to new analysts.

    Bottom Line: Domo isn't for newcomers but for companies that already have business intelligence (BI) experience in their organization. Domo's a powerful BI tool with a lot of data connectors and solid data visualization capabilities.

    Read Review
  • Pros: Exceptional platform for website and mobile app analytics.

    Cons: Customer support has way too much automation. Focus on marketing and advertising can be frustrating to users. Relies mostly on third parties for training.

    Bottom Line: Due to its brand recognition and the fact that it's free, Google Analytics is the biggest name in website and mobile app intelligence. It has a steep learning curve but it is an awesome business intelligence tool.

    Read Review
  • Pros: Designed with general business users in mind. Solid return on investment.

    Cons: The data you can use is limited. Needs additional platform to connect.

    Bottom Line: The Salesforce Einstein Analytics Platform is designed for customer, sales, and marketing analyses, although it can server other needs, too. Its powerful analytics capabilities along with its solid natural language querying functionality and a wide array of partners make it an attractive offering.

    Read Review
  • Pros: Real-time analytics for Internet of Things (IoT) and streaming data features. Massive ecosystem with plentiful extenders. Responsive pages make mobile publishing easiest. Impressive storytelling paradigm. Centralized view with consolidated analytics.

    Cons: Data prep features are lacking. Confusing toolbar design. Not friendly for beginners.

    Bottom Line: If your business already uses SAP's HANA database platform or some of its other back-end business platforms, then SAP Analytics Cloud is a powerful, well-priced choice. But be warned that there's a steep learning curve and a noted dependence on other SAP products for full functionality.

    Read Review
  • Pros: Impressive processing engine. Powerful query optimization on SQL. Entirely web-based. Complex queries are handled very well.

    Cons: Poorly designed user interface. Steep learning curve.

    Bottom Line: Chartio excels at building a powerful analytics platform that experienced business intelligence (BI) users will appreciate. Those new to BI, however, will find it very difficult to use.

    Read Review
  • Pros: Very deep SQL modeling ability. Uses Git for version management and collaboration.

    Cons: Very expensive. Not for small teams.

    Bottom Line: Looker is a great self-service business intelligence (BI) tool that can help unify SQL and Big Data management across your enterprise.

    Read Review
  • Pros: Custom access roles. Solid collection of public data online.

    Cons: Complex pricing is a deterrent.

    Bottom Line: Qlik Sense Enterprise Server is a self-service business intelligence (BI) tool that delivers the best collection of user access roles among the BI tools we tested, and also demonstrates a promising start towards integrating Data-as-a-Service (DaaS).

    Read Review
  • Pros: One of the largest collections of data connectors. Many granular access roles.

    Cons: No free trial available. Training webinars can be costly.

    Bottom Line: The company's Focus query language is showing its age but Information Builders' self-service business intelligence (BI) tool WebFocus nevertheless has some powerful analysis features.

    Read Review
  • Pros: Very easy to get started. Nice team management and collaboration features.

    Cons: The cloud version has a subset of features found in Windows version. Online documentation could be improved.

    Bottom Line: While Tibco is still making the transition from a desktop to a cloud software vendor, its self-service business intelligence (BI) tool Tibco Spotfire is a great way to start visualizing your Excel data.

    Read Review
  • Pros: Excellent analytical support for Intuit QuickBooks. Very easy setup.

    Cons: Installation and setup is a bit of chore. No support for Intuit QuickBooks' online versions.

    Bottom Line: Clearify QQube is the best self-service business intelligence (BI) tool for in-depth analysis of your Intuit QuickBooks files, though you'll need to look elsewhere for broader BI tasks.

    Read Review

  • ISC West Daily Report | killexams.com real questions and Pass4sure dumps

    Day one

    On Tuesday, I attended the annual DMP Owners Forum, which is “one the ways we show our gratitude to our dealers,” Jon Adams, DMP dealer development manager, told a room full of DMP’s top 100 dealers.

    This year’s speakers included Major Gen. (Ret.) Vincent Boles, who shared the wisdom he has gained throughout his military career, as well as some of his views on what makes a true leader. Boles gave out his book—4-3-2-1 Leadership: What America’s Sons and Daughters Taught Me on the Road from Second Lieutenant to Two-Star General—to all attendees. The other featured speaker was former Southwest Airlines senior level leader, Jason Young, author of the books The Culturetopia Effect and Servicetopia.

    Attendees also learned how DMP is giving dealers access to new markets through a variety of new platforms, including DMP’s CompanyStore, which enables dealers to participate in the DIY marketplace; Secura, a new high-volume residential dealer program; OnDemand Monitoring, a new revenue generator for dealers to offer to consumers that don’t want to sign long term contracts; and new avenues in home automation, including integration with AppleTV, Amazon Echo and Google Home.

    DMP executive management also featured sessions on new technology that will be available this summer, including previews of the DMP’s Gunshot Detector that goes on Existing DMP XR Series panels and DMP’s new Doorbell Camera, which Mark Hillenburg, DMP’s executive director of marketing, said is “deeply integrated” and will “provide new highly sought after functionality to the existing DMP Virtual Keypad, App and control panel family."

    Jeff Britton, DMP’s VP of product design, also walked attendees through DMP’s Tech App Platform, which was “developed to save time on new installs and service calls and really to eliminate some of the service calls you are having to make today. The platform will continue to grow because we feel there are a lot of things that your techs should be able to do right from their phone or their tablet.”

    Day Two

    On Wednesday, I began my day at Axis Communications’ 10th annual press breakfast. With the theme of “The Magic of IoT,” Fredrik Nilsson, VP Americas, and Martin Gren, founder, who were both dressed as magicians—you gotta love these guys!—talked about how the company plans to bring the same innovation and “magic” that it brought to camera technology to other products, such as its Network Speakers, which make up an integrated audio system that is ideal for retail settings. Axis also teamed up with Cognimatics to develop analytic capabilities for its True View People Counter, which is also ideal for retail environments, providing valuable business intelligence data.

    Gren also provided a preview of its newest technology—the AXIS D2050-VE Network Radar Detector, an outdoor motion detector with radar technology that can provide cost-efficient perimeter protection and decrease false alarms. The Company is also previewing at ISC West a selection of products that will be launched later this year, including new high resolution fixed domes in AXIS M30 Series, AXIS P32 Series, and AXIS Q35 Series. Axis also unveiled its AXIS FA Series with modular cameras for highly discreet, cost-efficient video surveillance, and three new additions to AXIS P13 Series that offer 4K resolution in full frame rate and that enable coverage of large areas with high image detail.

    Following the breakfast I headed to the show floor, which was abuzz with high traffic and early indicators point to a record year in terms of attendance for this year’s show.

    My first booth visit was at Legrand, a global specialist in electrical and digital building infrastructures. Manny Linhares, director of strategy, IoT, told me about Eliot, a Legrand global IoT program, that “brings the promise of interoperability, providing the building blocks and infrastructure to enable IoT and bring connectivity to where it is needed.”

    Moving to the Qolsys showcase room, I was able to test drive the company’s second generation panel, which is sleeker and more powerful with some very cool new capabilities. Kevin Woodworth, director of technical account management, pointed out that the panel is the culmination of “all of the lessons we learned from our first panel, and what we learned from dealer feedback.” The panel has a 7-inch HD touchscreen with built-in 5MP camera and multiple wireless radios, as well as LTE connectivity, advanced encryption, a built-in router, a glass break detector, dual path connectivity and Bluetooth disarming, to name just a few of the upgrades.

    Over at the FLIR Systems booth, I was given a demo of the FLIR United VMS 8.0, the latest version of the company’s comprehensive, enterprise-level video management solution for managing video security operations. The company introduced three high-performance security cameras, including the FLIR PT-Series HD thermal and visible camera system, the FLIR Quasar 4K fixed box camera, and the FLIR Ariel 3MP (3-megapixel) corner camera. All three cameras integrate with FLIR United VMS 8.0 and expand the company’s end-to-end line of security solutions. I also got a demo of the company’s Cameleon command and control platform.

    At the Interlogix booth, the company was highlighting TruVision Navigator 7, the latest release of its popular video management software. TruVision Navigator 7 now works seamlessly with Interlogix TruPortal access control systems and IFS network switches, allowing end users to manage their entire security system from one single, easy-to-use interface.

    This year’s ASSA ABLOY Press Event focused on “Security in the IoT Age,” and Martin Huddart, president, looked at how IoT will affect security. He aptly pointed out, “We are producing data, not products today,” noting that the key as we move forward as an industry is “bringing all these devices together.”

    Next, I caught up with Denis Hebert, president, Feenics, a provider of cloud-based access control solutions. The company launched its enterprise Keep by Feenics platform that delivers scalability, flexibility and advanced security. The new cloud-based access control as service (ACaaS) platform integrates native visitor management, and incorporates RESTful API that dramatically simplifies integrating complementary systems plus connecting Keep to applications outside of the organization. Built specifically for the cloud and hosted by Amazon Web Services, Keep significantly minimizes costs through simple, maintenance-free upgrades and patches. 

    At the LifeSafety Power booth, Joe Holland, vice president of engineering, gave me a glimpse into how the company continues to “innovate the category of power,” with new predictive analytics and critical reporting capabilities. The company announced a breakthrough in connecting intelligent power management analytics to leading software manufacturers directly through Authentic Mercury Security hardware.  “This truly enhances and expands the potential for systems integrators to offer remote power management to customers who will benefit from predictive analysis and detailed reporting on the health and well-being of their solutions,” said Holland.

    I also met with Glen L. Smith, director, dealer operations, ADT, who told me about the great strides the ADT Dealer Program has made in the past year alone. In the area of support for dealers, the company went from a net promoter score of -9 to 76 in just 18 months. How did they do this? “We asked our dealers what was broken,” said Smith, who noted that response time was a big issue for dealers. In response to this concern, Smith said they went from a two-hour hold time to a zero hold time in just one year.

    At the Bosch Security Systems booth, the company featured a completely new portfolio of IP cameras and video analytics that extend surveillance beyond security, services that create recurring monthly revenue opportunities for dealers, and an all-in-one wireless multi-sensor that can be configured as a door/window contact, water or tilt sensor. Bosch also introduced In-Store Analytics, a solution to provide retailers with valuable insights on store traffic for improving operations, customer engagement and sales.

    At the Alarm.com booth, Brian Lohse, director, commercial sales, talked about the company’s strategy to take what it has been doing on the residential side and bring that to the SMB space. On the residential side, the company’s open platform continues to expand integrations with a broad range of devices to help its dealer partners extend their footprint in the smart home. Alarm.com has also extended 4G LTE communications capabilities.  In addition, Alarm.com highlighted its Business Intelligence service that helps its dealer partners lower attrition by analyzing data points.

    Next, I caught up with Jeff Whitney, VP of marketing for Arecont Vision, who went over some of the big announcements for the company at the show, including Arecont Vision SNAPstream bandwidth reduction technology that supports multiple new and existing megapixel cameras; SurroundVideo Omni G3 Omnidirectional multi-sensor cameras with remote setup; Arecont Vision Compact MicroBullet indoor/outdoor, day/night megapixel camera; and Arecont Vision MicroDome G2 with Integrated IR indoor/outdoor day/night ultra-low profile megapixel camera.

    At the Pelco by Schneider Electric booth, Sharad Shekhar, CEO, Pelco SVP, video line of business, and Diane Feliciano, VP, global marketing, spoke about how the company has spent the last 12-18 months “transforming and repositioning the company” for the future. “We have been making changes across the entire organization for the last couple of years, from technology developments to new sales, support and operations programming,” said Feliciano. Pelco also showcased several new and enhanced products and systems, including its VideoXpert Video Management System (VMS); Sarix Enhanced IP Cameras with preloaded analytics on every model; ExSite Enhanced Explosion-Proof Cameras; and Optera Panoramic Multi-Sensor Cameras.

    I finished my day with a visit to the Altronix booth, where Kirby Han, art director, took me through the company’s latest upgrades and new products, including its new NetWay Spectrum Fiber Solutions, its eBridge 800E EoC Receiver with Integral PoE Switch and its expanded NetWay Line with new managed midspans and endspans.

    Day Three

    I started day three at the Allegion Trends Talk breakfast, where I was able to speak with Rob Martens, futurist and VP, strategy & partnerships, about how the company is leveraging the latest technologies to provide the best solutions for customers. “I am the tip of the spear when it comes to new technology,” he said. “I create the chaos that the company has to deliver on.” Product wise, the company’s Engage platform is expanding to include many more products, “so that level of connectivity is now getting rolled out and becoming a reality.”

    At the Genetec booth, I spoke with Andrew Elvish, VP, marketing and product management, about the success of the company’s Mission Control system, which he said is “a game changer,” as the decision support system provides organizations with heightened levels of situational intelligence, visualization, and complete incident management capabilities. He also pointed to how the company’s Retail Intelligence application provides business intelligence and operational efficiencies. The company also highlighted the latest capabilities of its Synergis access control system, part of its Security Center unified offering.

    At the AMAG Technology booth, I met company president Kurt Takahashi, and spoke with Kim Rahfaldt, public relations manager. The company unveiled Symmetry CONNECT, its new policy-based identity management system that delivers an easy to use, automated software platform to manage employee, contractor and visitor identities, satisfy regulatory audit and compliance requirements and reduce the administrative costs of the security team. When used with Symmetry Access Control, organizations have a robust identity management system that utilizes data to secure people, property and assets, and automates business processes for better operational efficiency.

    At the HID Global booth, I spoke with Anthony Petrucci, director of global public relations and corporate communications, about the company’s new indoor Location Services for workforce optimization, which won the SIA New Product Showcase award. The Location Services provide organizations with visibility into the location of their workforce in a facility, making it possible to analyze room usage for better building management and increased operational efficiency. He also spoke about how the company is leveraging Bluetooth low energy (BLE) for new and emerging applications in the connected environment, as well as the role of mobile access, advanced smart card technology and biometrics in the company’s overall strategy.

    At the Milestone booth, I spoke with Courtney Dillon Pederson, communications manager, about the company’s strategic alliance with Lenel, which will begin selling Milestone Systems Video Management Software (VMS) solutions directly through the Lenel Value Added Reseller (VAR) channel in North America. “We are really excited about this partnership and believe this is a great combination,” she said, noting that this alliance will reduce the total cost of ownership for users.

    I next visited the Eagle Eye Systems/Brivo booth, and sat down with Dean Drako, president and CEO for Eagle Eye, who shared his views on the “continued adoption of cloud.” He also talked about the technology partnership with Hikvision to deliver customers a seamless and cybersecure cloud video surveillance solution. Eagle Eye also highlighted that is has added Camera Cyber Lockdown to all its products, which blocks cameras from communicating with the Internet, stops them from being attacked and compromised. Drako also spoke about the company’s implementation of two-factor authentication, which “will be the standard for the industry moving forward.”

    At the IDIS booth, I was able to sit down with company president and COO Albert Ryu, who shared his views on how the company is poised to leverage technology to provide the customized solutions for customers. He also spoke about how the company, which is celebrating 20 years, is “bringing AI to security.” On the product side, the company featured H.265 IPC/NVR products, including the new IDIS 12MP Super Fisheye Camera. Also featured were new low light and long distance solutions, and end-user focused enhancements to the company’s award-winning PTZ tracking controls, IDIS Smart UX Controls v2.0 and retail analytics/business intelligence suite IDIS VA in the Box. The company also highlighted its powerful 64-channel IDIS DR-8364 NVR, which delivers enterprise-level performance at an NVR price. Moving over to the Hanwha Techwin booth, Miguel Lazatin, director of product and channel marketing, North America, walked me through all of the new features and capabilities of the Wisenet 5 chip, which was unveiled recently. The new chip powers the Wisenet X series, a new product line that features 27 models split up between 2MP and 5MP camera lines. Features include 150dB WDR performance and clear images in extreme low light conditions, convenient USB port is also available for easy setup and installation, as well as license-free audio and video analytics, dual SD card slot for increased onboard storage and image stabilization using gyro sensors. The company also announced that it is investing $100 million to create a security-only manufacturing facility in Vietnam.

    Next, Dahua product marketing manager Jennifer Hackenburg, gave me a tour of the booth, showing me how the company is embracing “deep learning,” pointing out that the company is “ahead of the curve” in leveraging all of the enhanced capabilities that deep learning can provide. The company announced that it is working with NVIDIA to bring artificial intelligence (AI) functionality to its next-generation deep learning products. Equipped with NVIDIA GPUs, the Dahua DeepSense advanced high-capacity video analytics server provides deep learning capabilities. The technology delivers a powerful, scalable method of extracting rich metadata and processing structural data to deliver fast and accurate analytics. Dahua also announced that Movidius’ Myriad 2 Vision Processing Unit (VPU) technology will power select Dahua video surveillance cameras with advanced intelligence functions that train the devices to gather, analyze, and retain information much like the human brain.

    I next visited with Jim Hoffpauir, president, Zenitel, at the Vingtor Stentofon booth. He showed me how the company’s Turbine Intercom Station can provide a multitude of solutions, in any setting, from schools to airports to military and government applications. He also talked about his dedication to educating customers on how to pick the right system, and he created a scorecard to follow. He noted that it is important to have three key features—intelligibility, interoperability and the “ilities,” which relates to “high availability, scalability, defensibility and maintainability.”

    At the Tyco-Johnson Controls booth, I spoke with Roger Barlow, senior director, product management, TycoSP about a number of new products across its intrusion, access control and video divisions, and how the company is benefitting from the “synergies between Tyco and Johnson Controls,” he said. He also showed the DSC iotega, the company’s new innovative security and lifestyle management platform. A full-featured security technology, iotega facilitates home automation enhancements and add-ons via software apps. The company also announced its SG System 5 now supports PSTN line cards on the SG-System 5 receiver to give central stations the flexibility to monitor both IP and PSTN alarm signals, and how its EntraPass Go Support for Apple Watch is the “industry’s first Apple Watch mobile credential that allows card holders to use the watch as a mobile access control credential."

    At the Sureview Sytems booth, Simon Morgan, chief technology officer, gave me a demo SureView PSIM Solutions, which he pointed out, “improve security, optimize operations and reduce costs. He showed me how the Immix CC Platform delivers more integrations, easy deployment and simple operation. He said SureView Immix CC Simplifies PSIM deployment and operation, featuring “intuitive UI, more integrations and unique architecture, which deliver unprecedented ease of operation and versatility.”

    Next, I visited Ditek, a surge protection company that works closely with the security industry to protect vital systems and equipment from being damaged by power surges, saving money in the process. Jorge Andino, field sales engineer, pointed out that the company does this by providing a site survey for each project, giving that customer the right surge protection equipment to meet their needs. “Our surge protection equipment acts as the sacrificial lamb, preventing costly damage to the equipment.”

    I finished my day speaking with Rick Caruthers, executive VP, Galaxy Control Systems, who told me about the company’s new announcement that is “committing resources and manpower to providing cloud solutions to our customers,” he said. The Galaxy Cloud Concierge solution is a complete turnkey, cloud-based, fully hosted and managed access control and monitoring solution that includes professional 24/7 management and supports industry standard access technologies.

    Day Four

    On Friday I started the day at the Morse Watchmans booth speaking with George Lawson, account executive, and Joseph Granitto, COO, about the company’s key control and access management security systems, which are getting smarter and safer with a lot more functionality. “We take feedback from customers to add new features and make our products easier to use,” said Lawson. In addition to an improved motherboard powering its systems, the company is unveiling a new enterprise-based software system. And its Asset Watcher, which the company tested exhaustively over the past year, is set to come out soon as well.

    At the Pivot3 booth, I spoke with Brandon Reich, surveillance business leader, about the company’s strategic original equipment manufacturer (OEM) relationship with Intelligent Security Systems (ISS), an innovator in the development of advanced video management and video analytics software. Under the agreement, ISS will license the Pivot3 hyperconverged infrastructure (HCI) platform and integrate it with ISS video management software (VMS) to supply more robust security intelligence and video storage options to customers. “We are really excited about that partnership,” said Reich. “We can provide a great solution set together.”

    At the Eizo booth, I spoke with Keisuke Akiba, product and marketing manager, and Brian Cote, about the company’s security and surveillance monitoring solutions. The IP decoding monitors come equipped with visibility enhancement technology for improving the clarity of video footage in real time. Akiba demonstrated the multi-monitor flexibility and showed me the 4k IPS 31.5-inch monitor with 3840 x 2160 native resolution.

    Over at the Boon Edam booth, Tracie Thomas, marketing manager, gave me an overview of the company’s many entry solutions, as well as news on the company’s expanding sales and customer service staff to support record sales growth. The company also announced the expansion of its product-training schedule, with more programs and locations. And, soon, Boon Edam will offer its revolving door specifications on the ARCOM MasterSpec platform, which is widely used by architect and design firms in North America for commercial buildings.

    At the 3xLOGIC booth, Suzi Abell, tradeshow and events manager, shared show news, including the company’s new integrated, hosted video and access control solution for the SMB market and the company’s partnership with Bold Technologies to offer an advanced video solution. The companies recently completed integration of Bold’s ManitouNEO with the 3xLOGIC VIGIL video platform, which supports cloud-managed video. The company also announced the release of a new multi-sensor camera and updated VIGIL software.

    At the Panasonic booth, Charlie Hare, national category manger, security and evidence management solutions, walked me through some of the company’s big announcements at the show, including the company’s expanded portfolio of i-PRO Extreme Surveillance Technology and its new i-PRO Extreme PTZ Camera with Advanced Analytics, as well as its latest video surveillance solutions. The i-PRO features a new chip set that produces “amazing picture quality,” said Hare.

    Over at the ReconaSense booth, Clayton Brown, product manager, described the company’s next-generation situational awareness platform, which provides “the tools to perform real-time critical analysis,” he said. John Carter, the CTO of ReconaSense, is a former NASA engineer. The software leverages the IoT and big data with access control and video analytics to drive “proactive response” across diverse systems. By connecting the dots and alerting operators of suspicious events, the technology facilitates better decision-making and optimal resource allocation.

    My final booth visit was over at NVIDIA, which was showcasing some of its latest IVA-related, AI technology for smart and safe cities, featuring many partners such as IBM, Hikvision and Dahua. Deepu Talla, VP/GM, autonomous machines, showed me how the company’s GPU computing is not only powering its many partners but “driving the latest applications for safety and security in AI cities,” he said, including public safety, traffic management, behavior analysis, video analytics, anomaly detection, facial recognition, fast forensics, parking management and robotics.

    NOTE: In addition to daily reports, look for ssnTVnews video interviews from the show floor, including my video interviews with Bill Bozeman, president and CEO, PSA Security Network; Dan Moceri, executive chairman and founder, and Ken Lochiatto, president and CEO, Convergint Technologies; Maureen Lally, VP of marketing, TycoIS; Richard Tampier, senior director, sales and product strategy, Red Hawk Fire & Security; Craig Layers, senior VP. sales and marketing, ADS Security; and Jon Cropley, principal analyst, video vurveillance, IHS Markit.


    Intel Advances Next Phase of Big Data Intelligence: Real Time Analytics | killexams.com real questions and Pass4sure dumps

    SANTA CLARA, Calif.--(BUSINESS WIRE)--To help companies in a variety of industries from retail and healthcare to banking and transportation turn data into actionable insights, Intel Corporation today introduced the Intel® Xeon® processor E7 v2 family.

    Using analytics enables businesses to make decisions that improve top-line and bottom-line results. The Intel Xeon processor E7 v2 family delivers new capabilities to process and analyze large, diverse amounts of data to unlock information that was previously inaccessible.

    “Organizations that leverage data to accelerate business insights will have a tremendous edge in this economy,” said Diane Bryant, senior vice president and general manager of Intel’s Data Center Group. “The advanced performance, memory capacity and reliability of the Intel Xeon processor E7 v2 family enable IT organizations to deliver real-time analysis of large data sets to spot and capitalize on trends, create new services and deliver business efficiency.”

    Big data and the Internet of Things (IoT) are providing enormous opportunities for many organizations to grow as they create revenue-generating services from the information they are able to derive. The big data technology and services market is expected to grow 27 percent annually through 2017 to reach $32.4 billion4. A leading driver of this growth is the immense amount of data coming from connected devices making up the IoT, which is projected to grow to 30 billion devices by 20205. Investments in the highest performing technologies and analysis solutions can also deliver significant cost savings. For example, Intel’s IT organization expects to achieve cost savings and increased bottom-line revenue of nearly half a billion dollars through use of analytics solutions by 2016.

    New Big Data Processing and Analytics Capabilities with Relentless Reliability

    The Intel Xeon processor E7 v2 family has triple the memory capacity of the previous generation processor family, allowing much faster and thorough data analysis. In-memory analytics places and analyzes an entire data set – such as an organization’s entire customer database – in the system memory rather than on traditional disk drives. This method is gaining in popularity due to the increased need for more complex analytics. Industry analyst firm Gartner expects 35 percent6 of mid- to large-sized companies will adopt in-memory analytics by 2015, up from 10 percent in 2012 and predicts at least 50 percent of Global 2000 companies will use in-memory computing to deliver significant additional benefits from investments in enterprise resource planning (ERP).

    eBay, one of the world's largest and most complex online marketplaces, handles massive data sets of more than 50 petabytes (PB) for more than 100 million users. Based on initial testing of the new Intel Xeon processor E7 v2 and SAP’s HANA* in-memory analytics software, eBay has seen greater performance7 and understanding of larger data sets that will help drive additional revenue opportunities for its customers.

    Built for up to 32-socket8 servers, with configurations supporting up to 15 processing cores and up to 1.5 terabytes (TB) of memory per socket, the new processor family achieves twice the average performance of the previous generation3. These enhancements help businesses that run mission critical applications including business support systems (BSS), customer relationship management (CRM), and ERP to operate more efficiently, at lower cost and with faster response times2. For example, a sales team with these capabilities can maximize revenue by pinpointing the best time to sell a product, or let an oil and gas company better predict when its platforms require preventative maintenance.

    To reduce data bottlenecks, the Intel Xeon Processor E7 v2 family features Intel® Integrated I/O, Intel® Data Direct I/O and support for PCIe 3.0*, achieving up to four times the I/O bandwidth over the previous generation9 and providing extra capacity for storage and networking connections.

    System uptime and reliability also remains a key requirement for mission critical applications. The Intel Xeon Processor E7 v2 family continues Intel’s tradition of delivering world-class reliability, availability and serviceability (RAS). Intel® Run Sure Technology10 is designed for “five nines” solutions essential for business-critical data by reducing the frequency and cost of planned and unplanned downtime.

    Extensive Industry Support

    Starting today, 21 system manufacturers from around the world will announce more than 40 Intel Xeon processor E7 v2 family-based platforms. These manufacturers include Asus*, Bull*, Cisco*, Dell*, EMC*, Fujitsu*, Hitachi*, HP*, Huawei*, IBM*, Inspur*, Lenovo*, NEC*, Oracle*, PowerLeader*, Quanta*, SGI*, Sugon*, Supermicro*, Unisys* and ZTE*. Numerous analytics software vendors also support Xeon processor E7 v2 family-based platforms, including Altibase*, IBM*, Microsoft*, Oracle*, Pivotal*, QlikView*, Red Hat*, SAP*, SAS*, Software AG*, Splunk*, Sungard*, Teradata*, TongTech*, Vertica* and YonYou*.

    About Intel

    Intel (NASDAQ: INTC) is a world leader in computing innovation. The company designs and builds the essential technologies that serve as the foundation for the world’s computing devices. Additional information about Intel is available at newsroom.intel.com and blogs.intel.com.

    Intel, Intel logo and Intel Xeon are trademarks of Intel Corporation in the United States and other countries.

    *Other names and brands may be claimed as the property of others.

    Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.

    Results have been measured by Intel based on software, benchmark or other data of third parties and are provided for informational purposes only. Any difference in system hardware or software design or configuration may affect actual performance. Intel does not control or audit the design or implementation of third party data referenced in this document. Intel encourages all of its customers to visit the websites of the referenced third parties or other sources to confirm whether the referenced data is accurate and reflects performance of systems available for purchase.

    The TCO or other cost reduction scenarios described in this document are intended to enable you to get a better understanding of how the purchase of a given Intel product, combined with a number of situation-specific variables, might affect your future cost and savings. Nothing in this document should be interpreted as either a promise of or contract for a given level of costs.

    1. Intel Xeon processor E7 v2 family provides the largest memory footprint of 1.5 TB per socket vs 1TB per socket delivered by alternative architectures, based on published specs.

    2. Up to 80% leadership performance on Xeon E7 v2 over IBM Power* 7+ at ~80% lower TCO claim based on Intel estimated SPECint*_rate_base2006 results and pricing of comparable 4-socket rack server using Intel® Xeon® processor E7-4890 v2 (37.5M Cache, 2.8 GHz, 15-Cores) to IBM POWER*750 using POWER7+ (80M Cache, 4.0 GHz, 8-Cores) as of December 2013.

    3. Up to double the average generational performance based on results of six key industry-standard workloads: SPECint*_rate_base2006+, SPECfp*_rate_base2006+, brokerage on-line transaction processing (OLTP) database workload, warehouse supply chain OLTP database workload, STREAM memory bandwidth and LINPACK GFLOPS. Configurations: 4-socket server using Intel® Xeon® processor E7-4890 v2 (new processor) vs. E7-4870 (previous generation processor). Learn more about Xeon E7 v2 performance at http://www.intel.com/content/www/us/en/benchmarks/server/xeon-e7-summary.html

    4. Source: IDC WW Big Data Technology and Services 2013-2017 Forecast, Doc #244979, Dec 2013

    5. Source: IDC Market Analysis Perspective: Worldwide Enterprise Servers, 2013 — Technology Market, Doc #245080

    6. Source: Gartner "Top Technology Trends, 2013: In-Memory Computing Aims at Mainstream Adoption"

    7. eBay’s test systems configurations are not disclosed but the observed results are consistent with Intel’s internal measurements from November 2013 showing 2x performance increase when using SAP HANA based on these configurations:Baseline 1.0x: Intel E7505 Chipset using four Intel Xeon processors E7-4870 (4P/10C/20T, 2.4GHz) with 256GB DDR3-1066 memory scoring 110,061 queries per hour. Source: Intel Technical Report #1347.New Generation 2x: Intel C606J Chipset using four Intel Xeon processors E7-4890 v2 (4P/15C/30T, 2.8GHz) with 512GB DDR3-1333 (running 2:1 VMSE) memory scoring 218,406 queries per hour. Source: Intel Technical Report #1347.

    8. Requires node controller (available from 3rd party sources).

    9. Up to 4X I/O bandwidth claim is based on Intel estimates on an internal bandwidth tool running the 1R1W test of the Intel Xeon processor E7-4890 v2 performance normalized against the improvements over dual-IOH Intel Xeon processor E7-4870.

    10. No computer system can provide absolute reliability, availability or serviceability. Requires an Intel® Xeon® processor E7-8800/4800/2800 v2 product families or Intel® Itanium® 9500 series-based system (or follow-on generations of either). Built-in reliability features available on select Intel® processors may require additional software, hardware, services and/or an internet connection. Results may vary depending upon configuration. Consult your system manufacturer for more details.



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