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COG-706 exam Dumps Source : IBM Cognos Financial Statement Reporting Developer
Test Code : COG-706
Test Name : IBM Cognos Financial Statement Reporting Developer
Vendor Name : IBM
Q&A : 60 Real Questions
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BEDFORD, Mass., can also 10, 2016 (GLOBE NEWSWIRE) -- Datawatch corporation (NASDAQ-CM: DWCH) nowadays introduced the instant availability of Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics. past this 12 months, Datawatch published that IBM (NYSE: IBM) would resell Datawatch Monarch to convey superior and quicker records access and self-provider data preparation (prep) to its clients. beginning nowadays, those users can leverage Monarch to prep less, analyze greater and harness the vigor of IBM’s cognitive computing capabilities across the widest range of records sources.
statistics that offers the most analytical value has historically been locked away in in the past inaccessible multi-structured and unstructured files, corresponding to textual content stories, net pages, PDFs, JSON and log info. And, in lots of situations, an organization’s supply statistics is diverse and infrequently items itself in an evaluation-equipped layout. subsequently, hours are spent on guide facts retrieval and prep procedures.
The Datawatch Monarch self-carrier records prep solution makes it possible for statistics analysts and universal business users to unexpectedly access, manipulate and mix facts from basically any source. statistics can then be prepared for analysis in Watson Analytics and Cognos Analytics in a fraction of the time that it takes the usage of spreadsheets and different manually-intensive measures.
“the vast majority of strategic enterprise decisions are made on incomplete or outdated tips, due to records retrieval challenges and time-intensive guide prep strategies,” spoke of Michael Morrison, president and CEO of Datawatch. “here's an unlucky reality given the affect these choices can have on a company’s final analysis and boom abilities. Monarch allows for Watson Analytics and Cognos Analytics users to acquire not only the appropriate counsel, however all the suggestions, required to attain a holistic view of the company, after which without problems and abruptly put together it for evaluation. instead of spend hours on mundane prep work, clients can now devote their time to performing evaluation that quickens resolution making and drives business value.”
IBM VisionDan Potter, Datawatch’s chief marketing officer, is scheduled to latest on new advances in self-provider statistics prep on the upcoming IBM vision convention in Orlando, Florida. Potter will discuss how self-provider facts prep permits users, chiefly these in monetary and operational efficiency management, to leverage a much broader range of information, and reap faster and more accurate results. He’ll additionally reveal how an optimized facts file will also be organized for direct import into Watson Analytics and Cognos Analytics. Potter’s session will take vicinity on Wednesday, might also eleven, at 11 a.m. ET.
To be taught more about Datawatch Monarch for Watson Analytics and Cognos Analytics, go to: http://www.datawatch.com/ibm-analytics.
About Datawatch CorporationDatawatch organisation (NASDAQ-CM: DWCH) allows typical clients to obtain magnificent outcomes with their facts. simplest Datawatch can unlock statistics from the widest diversity of sources and put together it for use in visualization and analytics tools, or for different company techniques. When real-time visibility into all of a sudden altering data is essential, Datawatch additionally permits users to analyze streaming information, even within the most worrying environments, similar to capital markets. companies of all sizes in additional than 100 nations global use Datawatch items, together with ninety three of the Fortune one hundred. The enterprise is headquartered in Bedford, Massachusetts, with places of work in big apple, London, Frankfurt, Stockholm, Singapore and Manila. To study greater about Datawatch or download a free edition of its business utility, please visit: www.datawatch.com.
secure Harbor statement below the deepest Securities Litigation Reform Act of 1995Any statements contained during this press unencumber that don't describe historical information may additionally constitute forward-searching statements as that term is defined within the deepest Securities Litigation Reform Act of 1995. such a statements contained herein, together with but now not constrained to these relating to product performance and viability, are in response to current expectations, however are field to a couple of dangers and uncertainties that may cause precise outcomes to vary materially from expectations. The elements that may cause actual future effects to vary materially from current expectations consist of here: swift technological change; Datawatch’s dependence on the introduction of latest items and product enhancements and viable delays in those introductions; acceptance of latest products through the market, competition within the application business commonly, and within the markets for next generation analytics in selected; and Datawatch’s dependence on its major products, proprietary software expertise and software licensed from third parties. additional assistance on factors that could cause precise outcomes to differ from those predicted is distinct in a variety of publicly-available files, which consist of, however don't seem to be restrained to, filings made by using Datawatch now and again with the Securities and exchange commission, including however no longer limited to, these acting in the enterprise’s Annual report on form 10-okay for the yr ended September 30, 2015. Any ahead-searching statements may still be regarded in mild of those components.
© 2016 Datawatch organization. Datawatch and the Datawatch brand are trademarks or registered logos of Datawatch organization within the united states and/or different nations. All other names are emblems or registered emblems of their respective organizations.
Media Contact: Amanda Beaupre advertising and marketing Communications supervisor, Datawatch email@example.com 978-275-8387 Twitter: @datawatch
IBM has distinct utility company intelligence products together with Cognos Analytics (previously Cognos company Intelligence), Cognos TM1, Cognos express, and Cognos Disclosure management. IBM Cognos enterprise Intelligence entrance-end can connect with SAP for HANA integration from IBM Cognos 10.2.1.9 onwards through JDBC facts supply connectivity (IBM, n.d.). established in 1966, Jabil Circuit, Inc is likely one of the biggest electronic accessories manufacturing services establishments overlaying a wide-range of enterprise areas reminiscent of provide chain administration, digital circuits, design engineering, logistics, telecommunications, and semiconductor accessories for computing. GE is without doubt one of the biggest clients for Jabil Circuit (Universe, n.d.).
historical past of the problem
organisations want ultimate mile statistics analytics on their monetary operations. After performing procurement of substances, construction of accomplished goods, inventory administration, deliver chain administration, growing revenue orders, deliveries, transportation administration, superior delivery notifications, shipping, managing instruments administration, invoice creation, finally the enterprise has to operate the fiscal shut taking the sophisticated facts from the disparate records sources of the aforementioned company procedures. In an enterprise useful resource Planning equipment, all of the above business strategies are unified in one database with a structured layout. youngsters, companies conducting the enterprise transactions in distinct database programs and spreadsheets will ought to spend a number of hours to bring together the records to consolidate the commonplace ledger postings, money circulation, and money flow (Srilu, 2013).
The records that comes into Excel spreadsheets may additionally not have validation system to check the enter of the values except checking numeric, alphanumeric combos. There is no ordinary pre-described configuration install in Excel Spreadsheet migrated from yet another system. this can create problems for a corporation to consolidate and migrate the information from Excel spreadsheets into economic statements for every month end. Excel spreadsheets can drastically decelerate the enterprise boom and the revenues of the commercial enterprise. If the business can not visualize the earnings and regional breakdown of the key efficiency warning signs, they aren't in a position to predict the increase plan for the next quarter or subsequent month. this can have an effect on deliver chain operations, advanced planning optimization, and company network collaboration, company network planning. in the conclusion, the corporation will endure losses. Jabil was plagued by these basic issues to shut the finance of the companies on time (Thomson, 2012).
Jabil applied IBM enterprise Analytics, IBM Cognos enterprise Intelligence, IBM Cognos enterprise standpoint, IBM Cognos Controller, and IBM Cognos TM1 to beat the economic shut conundrums. IBM company Analytics includes a bevy of analytics options for corporations.
clever and Intuitive Analytics
Jabil applied IBM Cognos Analytics, the right arm of IBM business Analytics company Intelligence Analytics. The answer from Cognos Analytics presents the financial enterprise groups to create the analytics studies on their own. they can access the statistics points from BI Analytics through distinct sources, and with elementary drag and drop concepts they could build the self-serviceable experiences. company groups can entry IBM Cognos even when they are mobile or operating browser-based mostly equipment on the information superhighway. Streamlined workflow offers a number of notifications for the corporation teams to action their selected projects (IBM, n.d.).
business Key efficiency symptoms
IBM enterprise performance administration gives the insights to measure the performance of the business in entirety by means of bridging the gaps found between the provide chain management operations and the monetary closing of the corporate books. It offers alternatives to build advanced planning for the company to contain techniques to task the trends of the statistics into the long run by using looking at the old patterns of the statistics in each company community. This gives forecasting for deliver chain operations to fabricate the products into the marketplace for various segments and shoppers. corporations that can look at the premonitory watch indicators notifications and traits can set the tempo for business boom for every quarter to show the records insights into revenues. EPM can also video display the undertaking plans constructed with particular fiscal budgets for a bevy of a portfolio of mission options spanning a couple of items to establish a knowledge-pushed corporation. The scorecards of EPM also suggests the areas where the felony and regulatory requirements for the enterprises in getting ready the financial statements (IBM, n.d.).
IBM Prescriptive Analytics performs diagnosis on the employer typical performance with strategic management innovations. The diagnosis leads to offering counseled options to explain, have a look at, record, and act. company workflow optimization drives automation of some decisions. C-level executives can control the enterprise-oriented decisions. These choices can doubtlessly arise on reviewing the brand loyalty of the shoppers related to selected items for both launching a brand new product or increase an present product within the company. The prescriptive evaluation also can faucet into the localization of the movements organized with the aid of the company catering a bevy of native markets (IBM, n.d.).
IBM business Intelligence gives predictive analytics for performing remaining mile facts mining analytics via wrangling the information with exploratory strategies to take into account the company views from quite a lot of key efficiency indicators of company strategies spawning from deciding to buy the raw materials via fiscal close. firms need insights to plot at the least 18 months ahead of their advanced planning optimization for deliver chain administration approaches. This can also be performed through a few forecasting fashions and utilized statistical strategies on the information and glean the statistics via text-primarily based analytics to create fashion-based models for the longer term. This helps to predict and forecast the variety of products to launch on the industrial shelves for each retailer in the market with who Jabil is conducting the enterprise transactions. essentially, Jabil manufactures digital components to bring together various digital devices, telecommunication, and network gadget. This requires granularity of the market trends and the predictive analytics also can hook as much as connect with R language for leveraging any extra statistical programs. IBM’s Apache Spark can function the analytics in-memory in contrast to Apache Hadoop that places IBM ahead of the pack on file-based mostly programs. Integration of Apache Spark with IBM predictive analytics and R can enhance the gadget further (IBM, n.d.).
Governance, Compliance, and chance administration
corporations performing companies throughout the globe need to meet regulatory compliance requirements when buying and selling with different nations. The hazards can arise from the tax laws or customs obligations levied by other international locations throughout the globe. To stability the exchange dangers, the company transactions conducted within the business resource planning gadget or via dissimilar database systems deserve to be audited. IBM has the analytics solutions for managing the chance. The possibility administration analytics will scan in the course of the database of the supplier and find out the risks involved via true-time analytics for understanding the ever-increasing hazards in the transactions (IBM, n.d.).
though, Jabil implemented not the entire above options. despite the fact, a majority of the IBM Analytics options had been carried out. The merits derived with the aid of Jabil via IBM Analytics options supplied miraculous insights to achieve the operational excellence for financial close and manufacturing plant life to run their company successfully. The answer will also be utilized to several different industries which are within the manufacturing of semiconductor, high-tech, telecommunications, storage contraptions, and network equipment. The manufacturing procedure includes a specific manner mannequin to prepare the built-in design of the circuits and chips. The master statistics management built by means of Jabil through their analytics, and commercial enterprise performance administration to display screen the important thing efficiency symptoms may also be utilized to numerous different industries which are under an analogous category. The success of Jabil will also be a possible probability for leisure of the industries in that section to observe in response to the requirements analysis and implementation of Jabil.
IBM (n.d.). Cognos Analytics. Retrieved November 9, 2015, from http://www.ibm.com/analytics/us/en/technology/items/cognos-analytics/
IBM (n.d.). Cognos company Intelligence 10.2.1. Retrieved December 28, 2015, from http://www-969.ibm.com/application/reports/compatibility/readability-studies/report/html/prereqsForProduct?deliverableId=1330380859450#!
IBM (n.d.). commercial enterprise performance management. Retrieved November 9, 2015, from http://www-03.ibm.com/software/items/en/class/efficiency-management
IBM (n.d.). Predictive Analytics. Retrieved November 10, 2015, from http://www.ibm.com/analytics/us/en/know-how/predictive-analytics/
IBM (n.d.). Prescriptive analytics. Retrieved November 9, 2015, from http://www-03.ibm.com/application/products/en/class/prescriptive-analytics
IBM (n.d.). chance management. Retrieved November 10, 2015, from http://www.ibm.com/analytics/us/en/company/chance-management.html
Srilu (2013). SAP modules overview and company procedures. Retrieved November 9, 2015, from http://www.slideshare.web/srilu999/sap-modules-overview-and-enterprise-procedures
Thomson, S. (2012). IBM Analytics gives Jabil more suitable insight Into economic performance. Retrieved November 9, 2015, from http://www-03.ibm.com/utility/businesscasestudies/us/en/corp?synkey=M525334P42483U27
Universe, F. (n.d.). Jabil Circuit, Inc. historical past. Retrieved November 9, 2015, from http://www.fundinguniverse.com/enterprise-histories/jabil-circuit-inc-heritage/
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The biggest additions to IBM Cognos Report Studio in version 10 have been Active Reports and Statistics objects. These two new ways of presenting data provide many new options for report authors to create reports that match the analytical needs of the user community. Entire classes have been created to focus on the creation of reports using these formats.
Other capabilities in IBM Cognos 10 Report Studio include the integration of external data sources and the ability to save Report Studio reports to be used directly by Business Insight Advanced authors. Using external data sources in Report Studio has been a customer request since IBM Cognos tools moved to a web-based architecture. This enhancement gives the report consumer new opportunities to process just the information needed for a specific situation. By using a common report definition between applications, users who aren't accustomed to complex reports can receive assistance to build reports that have features beyond those normally available to Business Insight Advanced users.
While the features I've discussed to this point are promoted as key features, other useful options in version 10 will increase the effectiveness of reports to your users. Some of these features were previously available through complex programming by the report developer, but IBM Cognos Business Intelligence now makes this job much easier. As a report writer and instructor who can appreciate the ability to create report designs designed to tell a story, I want to highlight 10 of these new features.Alternative Text
The Alternative Text property has been added to graphical objects, such as images and charts, to allow screen readers to translate the text (see Figure 1). Another aspect of this feature that's applied in various properties is to provide localized text without using conditional formatting.Colored Regions, Plot Area Fill, Material Effects
The Colored Regions, Plot Area Fill, and Material Effects properties allow charts to have more creative designs in order to enhance the overall presentation of the charts. Mixed with other chart presentation options, these features help report developers to give new polish to the presentation of content. Figure 2 shows the additional gradient options that are now available, along with the new properties for the charts.New Gradient Fill Types
Moving beyond simple linear gradients, some new fill types provide more choices for enhanced presentations. Backgrounds behind pages, objects, and selected areas can now display a number of gradient designs. The fill types include rectangular frames and embedded circular gradients, with many parameters to customize the blending of colors (see Figure 3).Chart Combinations (Primary Axis, Secondary Axis, Primary Bottom, Secondary Bottom)
IBM Cognos 8 Business Insight had the ability to set Y1 and Y2 axes. Now combination charts can be stacked with two more axes for better analysis of related numbers. These options can be integrated into dashboard design to enhance the presentation of related measures. Figure 4 shows a chart with the additional axes selected.Query Calculations in Query Explorer Replace Calculated Member, Calculated Measure, Set Expression, and Intersection (tuple)
In IBM Cognos 8 Report Studio, different objects were created for each of the dimensional functions. Now they're all bundled into the Query Calculations (see Figure 5). This option simplifies the toolbox for report authors, while emphasizing that dimensional queries can have enhanced calculations.Summarize Small Slices and Exploded Slices
With pie charts, two improvements include summarizing small slices and exploding slices. These two options greatly improve the presentation of pie charts to emphasize the most important information (see Figure 6). In my classes, these options have been requested for years, and now they're delivered in this release.Trendlines, Category Baselines, and Numeric Baselines
Report Studio functions have now improved on the predictive ability behind charts, without having to use external functions to calculate the numbers (see Figure 7).Series Color Synchronization
With the changes made to enhance series, this feature allows report writers to simplify the legends when the series information is repeated across the combinations. By changing the Series Color property to Match (see the short arrow in Figure 8), the legend shows the different product lines and the nested measures differently (indicated by the longer arrow), increasing the effectiveness of the presentation.Custom Properties for Prompts
As a welcome addition to dimensional functions, the Set Definition option (see Figure 10) allows report authors to create complex subsets that are presented graphically. This feature can make troubleshooting complex sets much easier by providing a more modular approach to set development. This was the best new property for me, since it simplifies the development of sets that had to be full of nested functions.
While Big Data can be useful in fighting fraud, traditional business intelligence tools aren't much help.
If it was easy to detect fraud, there wouldn’t be much of it around. But these days, the sheer volume of information being generated makes it more difficult than ever to detect.
“Organizations today typically have a fragmented approach to dealing with security and fraud risks, which leaves them vulnerable to even more attacks as criminals are quick to find and exploit any points of weakness,” said Ellen Joyner-Roberson, global marketing principal at SAS Security Intelligence Solutions. “As a result, security risks and financial crimes are increasing dramatically due to a weak global economy, growth in organized crime and the increasing sophistication of fraudulent schemes.”Not Your Usual Analytics
Unfortunately, many current analytics systems do not support robust analytical modeling, making it difficult to process and analyze information fast enough to make a difference. Different departments often have disparate data sources and processes, so it’s tough to spot suspicious activity across the enterprise.
In addition, there is a constant struggle to balance tougher anti-fraud efforts with a good customer experience. If vendors stop more transactions that are suspicious in an attempt to reduce fraud losses, they may anger customers trying to complete legitimate transactions.
Banking, insurance, government, health care and retail are obvious targets for con artists. The banking industry, for example, has a big problem with identity theft and account takeover. There, it is critical that decisions are made in real time at the point of sale, which requires a monitoring and analytics approach that can instantly model for behavior changes and stop that transaction without getting it wrong too many times.
Due to such demands, the consensus is that traditional business intelligence (BI) isn’t sophisticated enough. It needs to be backed up by domain-embedded rules and adaptive analytics that can be tailored to different types of fraud or financial crime. Context also plays a vital part, and integrating contextual information from mobile apps and other channels can heighten success. And geospatial and velocity data capture at transaction origination should be backed up by decision making in real time.
“To fight fraud before it causes financial losses, companies are using real-time interdiction (definition: to forbid or debar) capabilities wherever they can, and with raw response times under 200 milliseconds,” said Joyner-Roberson.
Her company developed SAS Security Intelligence to address this market. It comprises various SAS products to address fraud and improper payments, regulatory compliance and security. This includes SAS Fraud Management, SAS Network Analytics, SAS Financial Crimes Suite and SAS Fraud Framework.
SAS Security Intelligence takes an enterprise approach to data management and consolidation, combining data integration, data quality and master data management into a unified environment that brings together cross-channel enterprise data on a single platform. It has the ability to score and decision all transactions in real-time and intercept suspect deals.Haystacks, Needles and Big Data
Big Data only magnifies the problems inherent in tracking down wrongdoers. Just how do you deal with capturing, processing, and storing massive amounts of real-time data so you can learn and adapt to changing behavior patterns?
“The needle in the haystack analogy is particularly appropriate for fraud detection due to the small amount of fraud compared to the whole of legitimate Web traffic,” said Jesse McKenna, head of Threat Research for Silver Tail Systems, RSA. “However, as fraud patterns constantly shift and evolve, so does the needle you are looking for. Today it may be a needle, tomorrow a pushpin or a nail.”
The challenge is that you don’t know exactly what you are looking for other than it will be different than the rest of the pile. While Big Data means you may be able to derive more insights, finding the meaningful data and building detection algorithms that aren't brittle and won't quickly become irrelevant takes a deep understanding of fraud.
That’s where behavioral analytics and adaptive detection methods become important. You need ways to isolate what is different that you may have never seen before.
Analytics apps also have to be of value to fraud investigators, who are the ones with the experience of the real world. Machines can burn through the data mountain to locate unusual occurrences, but they are nowhere near as good as people at evaluating and understanding context. Therefore, the app has to facilitate the people or fraud units it serves, not burden them with delays or lengthy procedures.
RSA’s Silver Tail Systems product suite (consisting of Forensics, Mitigator, and Profile Analyzer tools) provides behavioral analytics, real-time custom rules and mitigation capabilities, as well as a forensics interface for performing investigations.
For example, by monitoring the details of every HTTP/S request that is sent to a website, it learns what normal behavior looks like for the website and can then identify criminal behavior and alert the appropriate teams for investigation. Alternately, it can communicate with other network devices to redirect or terminate the Web session in real-time.
User-based behavioral analytics (in addition to the population-based ones) helps identify when a particular user is deviating from their normal behavior, as is the case with many fraud and account compromise scenarios.
“Silver Tail was created by ex-eBay and PayPal fraud professionals who lived the battle against fraud at a time when they were protecting the two most targeted brands on the Internet,” said McKenna. “Their experiences motivated them to keep up with shifting Web fraud attacks instead of playing catch-up.”Visual Aids
IBM is also involved in fraud analytics via a combination of IBM SPSS Modeler, SPSS Statistics, SPSS Collaboration and Deployment Services, SPSS Data Collection, SPSS Decision Management, IBM Cognos BI, Cognos Express, Cognos Insight, Cognos Disclosure Management and Cognos Financial Statement Reporting.
IBM believes that visualization is a vital part in making sense of analytics information, especially when it comes to facilitating the work of professionals in fraud detection.
“As data volumes continue to go up, BI tasks can benefit greatly from the use of information visualization techniques,” said Don Campbell, CTO, IBM Business Analytics. “Good visual representations can help individuals intuitively understand complex data. Visualization can be a powerful presentation and information consumption interface. But it doesn't stand on its own.”
Graphical representation is also a focus of 21CT, a provider of analytics for investigation and pattern detection. It has released enhanced graph search for its LYNXeon product to help spot cyber attackers and document criminal behavior. The rationale behind the product is that machine -based attacks can be caught by machines, but human-based attacks require specialized tools to help people detect them before the damage is done.
“Health care fraud, notably Medicare, is an enormous problem, costing billions a year,” said Kyle Flaherty, vice president of Marketing at 21CT. “The challenge is not only the enormous amounts of data, but also in the disparate connections within the data. Additionally, fraud has been rampant in this arena and the malicious entities have become sophisticated.”
While regular BI tools provide insight into one slice of the overall information, Flaherty said, they are not good enough for fraud detection, which depends on operational insight and the ability for a human to hunt through visualized data, discover links, and detect overall patterns of activity.
“Fraud detection is a human versus human battle, and BI tools can spit out more data and graphs to help illustrate the problem,” said Flaherty. “In the end you need to be able to hop around the data and investigate.”
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in California, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
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