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COG-632 - IBM Cognos 10 BI Metadata Model Developer - Dump Information

Vendor : IBM
Exam Code : COG-632
Exam Name : IBM Cognos 10 BI Metadata Model Developer
Questions and Answers : 53 Q & A
Updated On : April 22, 2019
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COG-632 IBM Cognos 10 BI Metadata Model Developer

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Exam Questions Updated On :


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COG-632 exam Dumps Source : IBM Cognos 10 BI Metadata Model Developer

Test Code : COG-632
Test Name : IBM Cognos 10 BI Metadata Model Developer
Vendor Name : IBM
Q&A : 53 Real Questions

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IBM IBM Cognos 10 BI

IBM Cognos company Intelligence 10.2.0 Reporting on IMS | killexams.com Real Questions and Pass4sure dumps

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IBM Cognos Analytics is named a winner within the 2019 huge business Innovation Award | killexams.com Real Questions and Pass4sure dumps

The IBM Cloud, information and AI design crew is excited to announce that IBM Cognos Analytics has been named a winner within the 2019 large company Innovation Award. here's thrilling information for our group as IBM Cognos Analytics is certainly one of our most multifaceted products, with many designers and groups engaged on all aspects it. we are honored to have this award show off this mission, and the hard work our team has carried out on it.

what's IBM Cognos Analytics?

IBM Cognos Analytics is an AI-powered statistics exploration and presentation device that enhances the workflow of enterprise clients. The device contains the means to create compelling visualizations and dashboards, make AI-powered selections for facts analysis, and scale the records analytics method at the level that a enterprise calls for.

IBM Cognos includes an AI assistant (left), and a aspect Panel (correct), to support interpret the chart being considered. The Assistant helps natural language exploration, while the aspect Panel offers extra device-generated plain-language suggestions to augment the chart. explore reduces the guesswork linked to facts exploration via surfacing the strongest relationships to your information, which is displayed in the network chart, and providing recommended beginning elements for more information exploration, which are proven within the thumbnails.

The AI-powered toolset in IBM Cognos Analytics enhances users’ skill to get the absolute best insights from their records. The toolset comprises innovations like a herbal language based mostly digital assistant, as well as a knowledge exploration device that finds relationships within records and suggests information visualizations. These effective information equipment enable enterprise clients to get greater tips from their information and easily pinpoint deeper, underlying trends that may additionally in any other case require a better level records skilled to decipher.

Storytelling elements in IBM Cognos Analytics present the capacity to imagine and monitor statistics with unique and fascinating visuals.

The presentation tools in IBM Cognos Analytics offer advanced and visually engaging information visualizations, permitting clients to communicate the ideas in the back of their facts in innovative and compelling methods. The application includes equipment to create distinct charts and graphs in addition to motion pix, assisting to add a narrative aspect to the style the facts is displayed. These enjoyable experiences permit the person to communicate their insights in a more artistic approach, cut back user interpretation error, and display the story behind their facts rather than simply sharing floor stage counsel.

“IBM Cognos Analytics turned into at all times an excellent reporting and dashboarding tool. What made the most fresh release one of these soar forward become the introduction of predictive analytics, AI and a whole new means of exploring data and discovering patterns and relationships the clients didn’t comprehend existed. What i love about it's that Cognos does so a whole lot of the heavy lifting when it involves analytics and soar-frogs you to the answers you need most.” — Anne Stevens, Design Lead

A win for design is a win for businessIBM Cognos Analytics being identified by using a business award shows simply how a whole lot design can carry cost to the world of business. Our team’s center of attention on outstanding person experiences and user research pushed design of this product, demonstrates that design method and execution matters for company consequences. I’m excited to see design proceed to have an affect on our utility products and see the broader implications this has for our users, valued clientele and partners.

in regards to the massive company Innovation AwardsThe company Intelligence group changed into situated with the mission of recognizing proper ability and superior performance within the company world. These awards are judged by using business executives with immense experience and skills. The firm’s entertaining scoring equipment selectively measures performance across diverse enterprise domains and rewards those organizations whose achievements in reality stand out.

Congrats to the IBM Cognos Analytics crew for all of your hard work and accomplishments.


IBM's Cognos 10: Combining Collaboration, Analytics for more suitable enterprise Intelligence | killexams.com Real Questions and Pass4sure dumps

IBM_logo_2009.jpg For a long time now, users had been asking what large Blue plans on doing with all the acquisitions in enterprise intelligence and analytics house (information, site) it made.

The unlock of Cognos 10, which combines social networking, collaboration, analytics and pursuits mobile workers, goes a way to answering that.

Pushed by means of the increase of cell transactions and estimates that the cellular workforce will globally reach 1.19 billion by 2013, IBM has combined the technology of Cognos, a company they received in 2007, with Lotus Connections, launched in 2007 at Lotusphere, and is at present in version 2.5.

added to all this is the statistical engine, which IBM purchased all the way through the SPSS acquisition in 2009, which allows users to embed algorithms into their experiences from IBM's SPSS utility.

IBM and Analytics

IBM is also releasing a number of different complimentary software applications that allows you to birth realizing the enterprise intelligence ambitions that the enterprise outlined when it bought Cognos all these years in the past. The other new applications encompass:

  • DB2 10: a brand new database that may mix previous, latest and future data to deliver a single view of assistance via time
  • IBM InfoSphere Server: A server that gives users the potential to combine every kind of records as smartly because the means to look the fine of records before it is used.
  • The value of Cognos for BI

    The launch of Cognos 10 is so massive in IBM’s business intelligence method that it's hailing the unencumber as “probably the most tremendous analytics offering seeing that the acquisition of Cognos . . .” Taking a step back in time, when IBM bought Cognos it announced that within the business they noticed the way forward for business intelligence. They underlined that imaginative and prescient with the U.S.$ 5bn IBM paid for the business.

    enterprise intelligence refers to the shooting, integration and presentation of assistance. performance administration is using assistance to assess the performance of commercial enterprise sectors, divisions, product strains and every thing else which can also be boiled down into numbers.

    the mixing of those two domains ensures a clearer photo of the place the firm basically stands, eradicating a great deal of the bad statistics and suggestions, which is certain to distort the important thing decision-makers vision. and that's what Cognos 10 does -- it gives the tools for determination support and reporting equipment, in addition to all of the normal enterprise bells and whistles.

    IBM, Lotus Connection and Cognos

    Add to this Lotus Connection, which brings with it social collaboration, and also you get some thought of what IBM is launching here.

    just to refresh your minds, IBM Lotus Connections is a social utility for company. It empowers business professionals to advance,  nurture, and remain in contact with a community of their colleagues and respond right away to company alternatives. Future enhancements consist of:

  • improvements to how consumer generated content material is moderated
  • Compliance and auditing capabilities
  • Deeper integration with WebSphere Portal and SharePoint
  • extended cellular support
  • combine Lotus Connections utility with Cognos’s company analytics and one unified experience with intuitive navigation capabilities and simplified person experience looks.

    IBM, SPSS and Analytics

    The other foremost aspect during this free up comes from the mixing of IBM’s SPSS Modeler, which IBM bought in another acquisition, with the BI atmosphere. Now a part of Cognos' file-authoring capabilities, it enables clients to gain insights from historic statistics. With it, they could carry predictive indicators into dashboards to deliver forward-searching perception concerning risk, profitability and other situations.

    the new liberate strikes from traditional codecs of studies and charts, now supporting developed-in photographs and video clips that are interactive and supply broader analysis in a versatile format that can also be accessed on most cell devices. With the brought analytics capabilities, users can also check counsel from elementary, actual-time tips to superior, predictive “what if” analysis.

    in short, the release gives business users not simply with advice about what's occurring to their business or products within the current, it also integrates what has came about in the past, presenting an extrapolated version of what is going to turn up sooner or later. Then, in the course of the social collaboration point, it shares the guidance with whoever wants it, each time they need it, and through cell guide, where ever they need it.

    the use of interfaces taken from accepted Cognos environments, clients can engage with every different in precise time communities, wikis and blogs, submit documents and reports, tap into determination networks, and another collaborative feature obligatory to move counsel to clients who want it.

    over the last 5 years, IBM has invested greater than US$ 14 billion in 24 analytics acquisitions. introduced at the guidance on Demand convention in Las Vegas, IBM noted Cognos 10 could be obtainable as of subsequent week when clients will be able to see the place all that got firepower has been used.


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    Make Room for Gartners BI and Analytics Platforms MQ Leaders

    Twenty four is a crowd -- yet that’s how many vendors made it into Gartner’s Magic Quadrant for Business Intelligence (BI) and Analytics circa 2015.

    For enterprises that are shopping for BI and Analytics solutions, choice may seem like a good thing until you consider what evaluating that many vendors might look like -- most of us wouldn’t even consider trying on 24 pairs of jeans.

    To be fair, this is how many BI and analytics vendors met Gartner’s criteria, and that’s no easy feat. Gartner defines BI and Analytics as a “software platform that delivers 13 critical capabilities across three categories -- enable, produce and consume -- in support of four use cases for BI and analytics.”

    Use cases range from centralized BI Provisioning, to decentralized analytics, to governed data discovery to providing OEM embedded APIs. 

    Required capabilities in the “Enable” category include: Business User Data Mashup and Modeling, Internal Platform Integration, BI Platform Administration, Metadata Management, Cloud Deployment, and Development and Integration.

    The “Produce” category considers Free-Form Interactive Exploration, Analytic Dashboards and Content, IT-Developed Reporting and Dashboards, and Traditional Styles of Analysis.

    The “Consume” category looks at Mobile, Collaboration and Social Integration, and Embedded BI. 

    The common trends Gartner analysts uncovered center around decentralized and bimodal governed data discovery approaches to BI and a call for self-service capabilities beyond data discovery and interactive visualization of IT-curated data sources.

    It’s worth noting that most BI and Analytics vendors are placed in the same quadrant as in 2014, but several have changed positions within them because of their more limited vision or ability to execute.

    2015-19-March-Gartner-BI-Analytics-MQ.png

    Gartner Magic Quadrant for Business Intelligence and Analytics Platforms

    Tableau Leads the Pack

    It should come as no surprise that Tableau’s results last quarter thrilled investors. Why? Because enterprise IT bosses, business analysts and quants all love the results its products produce. Tableau is the product to beat in the discovery space and no one else even comes close.

    Moreover, as we’ve written time and time again, Tableau users love Tableau -- they are literally enthused when they talk about it. Not just that, but you can also take data from someplace like an Excel file and make beautiful visualizations that tell stories.

    On the downside, Gartner’s report says that Tableau’s dashboards, traditional styles of analysis, metadata management, development and integration, BI platform administration, embedded BI and collaboration are weaknesses. It could also use a few improvements when used in centralized environments.

    These may, or may not, be functions and features that Tableau wants to provide.

    It’s also worth asking if any particular vendor can be the “go to” for every BI and Analytics endeavor.

    SAS Wins When it Comes to Completeness of Vision

    SAS has been around since 1966 so appearing as the most visionary vendor in the Leaders quadrant is impressive. Not only that, but SAS is also further to the right on the “Completeness of Vision” axis than any other vendor, even those in the Visionaries quadrant. It’s worth considering, though, that SAS offers what Gartner calls a “vast array” of integrated components, so they’re not exactly comparing it apples-to-apples when it comes to vendors like Tableau. 

    That being said, SAS Visual Analytics -- which has been around for just a few years -- is gaining traction against data discovery leaders partly because it has done a good job of differentiating itself and partly because its pricing model is more appealing. Gartner also praises SAS’s forward thinking in areas such as embedded advanced analytics within SAS Visual Analytics, ease of navigation between SAS Visual Analytics and SAS Visual Statistics, and integration across the SAS platform and other core analytics which makes governed data discovery simpler.

    Within the Enterprise, SAS doesn’t seem to be as widely deployed as it could be because of cost, but Gartner says the vendor is addressing the issue. This could be a win for SAS not only in deeper penetration at current customer sites but its ability to win business at smaller companies.

    Improved Vision and Execution for SAP

    SAP sits almost neck and neck with SAS in the Leaders quadrant. Gartner likes its vision, citing the direction it is taking with SAP Lumira and its simplified strategy for BI platform components.

    What’s especially notable is that Gartner researchers found that SAP is the BI standard (81 percent) in the companies in which it is used. (In other words, it’s not one of several tools). SAP has an advantage in this regard, because in many cases those companies also use SAP’s widely deployed ERP systems. SAP does, however, claim to have BI and Analytics customers who don’t use its ERP products.

    That being said, SAP’s BI tools offering leaves plenty of room for improvement in terms of customer experience at almost every level -- ranging from the buying process, to the UI, to providing business user data discovery capabilities.

    We should note that SAP’s new management team has pledged to take action on all of these fronts. We should have an indication on how that’s going by this time next year.

    Watson Gives IBM Vision, But There’s More to Consider

    Gartner says that the Enterprise likes the pitch that IBM Watson analytics makes but that it’s still too early to see how widely adopted it becomes. On the other hand, IBM Cognos, IBM’s integrated BI platform (it offers capabilities for Web-based ad hoc query, report and dashboard authoring and consumption, OLAP, scorecarding, production reporting, scheduling, alerting, data discovery and mobile) is embedded and sold in over 130 IBM applications. What a great way to gain market presence.

    IBM’s challenge is the same one that many legacy vendors face with their existing (and quite often market leading) products -- delivering a positive customer experience and meeting important business-user-centric market requirements. 

    Qlik Rules Where It Plays

    Some of the vendors that rank lower (actually further left on the “Completeness of Vision" axis) in Gartner’s Leaders quadrant do so because they are more narrowly focused. Qlik falls into that category. It has two BI & Analytics products based on an in-memory associative search engine.

    Gartner calls QlikView,

    a mature, self-contained, tightly integrated development platform used by IT or more technical users for building intuitive and interactive dashboard applications faster and easier than traditional BI platforms.” 

    Qlik’s newer product, Qlik Sense (released in September 2014) is business user friendly and provides a  way for them to build their own dashboards while giving IT the ability to govern, manage, scale and embed them. Gartner likes what it sees in it.

    Qlik’s challenge, according to Gartner, will be in selling and supporting two products at once without sacrificing customer experience.

    Business-User Enablement, A Clear Focus for Microsoft

    Microsoft is big enough and smart enough to leverage SQL Server and SharePoint to support IT-developer-centric data management, reporting and administration requirements and to provide Power BI for end users. Gartner likes the approach and the possibilities that it holds, stating that Microsoft has,

    a clear understanding of the market's desire for a platform that can support systems-of-record requirements and deliver easy-to-use data discovery capabilities, with support for promotability of business-user content and governance.”

    Though Power BI has yet to be widely adopted (its new availability in browser should help), it could alleviate a lot of problems. But Microsoft would still need to simplify its license models for that to happen.

    According to Gartner,

    the fact that many of the newer capabilities that are important to buyers in this market require current versions of Office, SQL Server and SharePoint adds to the complexity and represents a barrier to adoption for many organizations that are on older versions and are not yet willing to buy Office 365 and deploy BI and analytics in the cloud.”

    Further, it says that the workflow between Power Query, Power View and Power Pivot is not yet completely seamless. Not only that, but there are also questions about the role of SharePoint dashboards and Reporting and the fact that the latter is not supported in Azure.

    There also seem to be difficulties with the customer experience. Gartner says that they have “historically found it difficult to engage directly with Microsoft during the sales cycle, which was a major complaint from IT but is an even greater concern for Microsoft as it attempts to appeal to business buyers that have high expectations of simplified license models and purchase options.” 

    Other Leaders to Consider

    We should note that these are but six of the nine MQ Leaders (we took the top 3 from the “Completeness of Visions" Axis and the top 3 from the “Ability to Execute”). Oracle, Information Builders and Microstrategy were also named Leaders.


    Cognos Basics Tutorial — ABC LEARN | killexams.com real questions and Pass4sure dumps

    Data Warehouse Concepts

    What is a Data Warehouse?

    A warehouse in general terms is a repository where we store our information. Coming to the data warehouse, it is a collection of data organized in a specific manner and categorized information.

    A data warehouse stores historical data of an organization so that they can analyze their performance over the past years and plan for the future.

    The popular definition of the data warehouse by WH Inmon:

    A data warehouse is:

  • Subject oriented: Data in the warehouse is categorized in different subject areas. For example, consider a KFC store. It has many branches all over the world. If we have to analyze “sales” for India, this is termed as “subject”.
  • Integrated: A data warehouse has data coming from multiple sources which are integrated into the warehouse. For example, consider the same KFC store, stores in India may store date field as “dd/mm/yyyy” whereas the same data in another country will be stored as “MM/DD/YYYY”. The data warehouse will have only one format fixed to say “MM/DD/YYYY”.
  • Time-Variant: A data warehouse stores historical data with which we can identify patterns of sales over a time period of 3 months,6 months or 2 years of any organization which has a warehouse.
  • Non-Volatile: Data in the warehouse will not change once it is entered.
  • Another definition from Ralph Kimball is more precise:

    A data warehouse is a copy of transaction data specifically structured for query and analysis.

    What is a Data mart?

    A data mart is a subset of a data warehouse. Suppose we have an organization established in many different locations and each location maintains a data warehouse which we call it as data mart because a warehouse will have all the data integrated and as far as data mart is considered it will be a part of the data warehouse.

    What are uses of having a Data Warehouse?

    A Data Warehouse, in general, is used to analyze trends over a period of time and enhances the decision making of an organization. Once the data is loaded into the warehouse will be creating an OLAP cube or directly use the data to analyze trends. Basing on which the top level management will approach their future business strategies.

    Data warehouse Architecture

    We will multiple sources there all the operational data will be stored. Some may store them in flat files and some in databases. We will have to read all the sources and perform ETL (Extract, Transform and Load operations) which will be used to integrate data from these sources and transform them into one unique structure and then load into our target data warehouse.

    Data Warehouse Architecture

    There are 2 approaches in designing your data warehouse. First one is “Top-Down approach” and second is “Bottom-up approach”.

    Top — Down Approach: The above image shows the top-down approach, where we are reading data from multiple sources and transforming the data and loading into your warehouse, then on top of that we are creating our data marts.

    Bottom-up Approach: The opposite of the above approach is this. Here we will be creating data marts first and then we will create our data ware house on top of all the data marts.

    Data Warehouse Terms

  • Dimension: A Dimension is a categorical information which is stored in a data warehouse.
  • Fact: Fact is a measurable quantity by which we can actually figure out what the dimension does.
  • Attribute: Attributes are the elements in a dimension  Ex: Suppose we have product information classified in a dimension. The attributes of the “Product dimension” are: “Product_ID, Product_Name, Product_Color” etc.  Sales is a fact table where you store numeric values associated with the dimension attributes.For instance, we have to calculate the number of sales of each product for the current month.In this case, Product is the dimension and Month is a dimension and numbers of product sold is the fact.
  • OLAP: Online Analytical Processing is a multidimensional model using which users can view data in multiple dimensions at a single glance.
  • Types of OLAP’s:
  • Relational OLAP
  • Multi-dimensional OLAP
  • Hybrid OLAP
  • OLTP: Online transactional processing is a transaction based model where the main aim will be to retrieve data faster and update transactions quickly.
  • Schemas in Datawarehouse

    The schema is a logical arrangement of tables in a data warehouse. We have schemas in relational databases. Very much like same Data warehouse has schema’s namely Star schema, Snowflake schema, and Fact-Constellation.

    Star Schema

    In this logical arrangement of tables, the fact table will be at the center of the schema surrounded by multiple dimension tables. Fact and dimension tables are linked via a Primary — Foreign Key relationship.  Fact table will be having foreign keys of all the Dimension tables along with the facts whereas a Dimension table will be having attributes which describe the Dimension.

    Snowflake Schema:

    In this logical arrangement of tables, we have dimension tables connected to other dimension tables which in turn are connected to fact table via a primary-foreign key relationship.  Else we can say that the Dimension tables in Snowflake schema are normalized.  Because of the normalization, the data redundancy will be reduced and a lot of storage space is saved.

    Fact Constellation Schema:

    A fact constellation schema, unlike the start or snowflake, will have multiple fact tables. It is also called as Galaxy Schema.

    Star Schema Example

    In this schema shown, a fact table (sales) is connected to multiple dimension tables item, location, time and branch. Each dimension table has attributes describing the dimension and fact table has the foreign key of all dimension tables along with facts like dollars_sold and units sold.

    Snowflake Schema Example:

    In this schema, a fact table (sales) is connected to multiple dimensions, whereas the dimensions item and location are again connected to City and Supplier dimension respectively.

    Fact Constellation schema Example:

    In this schema, we can find two fact table Sales and Shipping connecting with each other and are again connected to multiple dimension tables individually.

    Now we are jumping into the actual topic “Cognos Business Intelligence”.

    Overall DWH architecture

    We will be dealing with Cognos reporting tool and Cognos Metadata managing tool and other useful tools that Cognos BI has.

    Let’s go through where BI will actually come into picture

    The below image shows overall Data warehouse Architecture. From data load to using the data loaded into the tables for enhancing the business of your organization. From all the data sources (may it be Operational databases, Flat files etc.) we load the data into data warehouse through different ETL process and creating cubes and using the data for mining purpose.

    The below figure will describe the Business Intelligence flow how the data will be used for Business optimization. Business intelligence is a process from where you will be able to derive methods to enhance your business with the data that you have. Using BI one will be able to look at their data at different levels and will be able to make decisions to make their business better.

    Cognos BI will be used to generate reports (list, crosstab, and charts). The below figure will show you the entire flow that happens with Cognos.

    The first step in using Cognos BI is to gather requirements. This is possible when you understand your business structure and the data that drives your business. Once the requirement is finalized the next step is to create your framework metadata model. You can choose either to you star schema or snowflake schema or you can use the existing relational model.

    After this step is done with we have to publish the model that we have created. Publishing the model will make your metadata model available for reporting purpose. Once your model is published, we can use the model to create different types of reports as per your requirement and we will schedule the reports basing your requirement.

    Different Versions of Cognos

    Cognos ReportNet

    Cognos ReportNet (CRN) is a web-based software product for creating and managing ad-hoc and custom-made reports. ReportNet is developed by the Ottawa-based company Cognos (formerly Cognos Incorporated), an IBM company. The web-based reporting tool was launched in September 2003. Since IBM’s acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet like all other Cognos products.

    Components:

  • Cognos Report Studio — A Web-based product for creating complex professional looking reports
  • Cognos Query Studio — A Web-based product for creating ad-hoc reports.
  • Cognos Framework Manager — A metadata modeling tool to create BI metadata for reporting and dashboard applications.
  • Cognos Connection — the Main portal used to access reports, schedule reports and perform administrator activities.
  • Cognos 8.x

    IBM Cognos 8 BI, initially launched in September 2005, combined the features of several previous products, including ReportNet, PowerPlay, Metrics Manager. There are also Express and Extended versions of Cognos 8 BI. Full features:

    Components:

  • Report Studio (Professional report authoring tool formatted for the web)
  • Query Studio (Ad hoc report authoring tool with instant data preview)
  • Analysis Studio (Explore multi-dimensional cube data to answer business questions)
  • Metric Studio (Monitor, analyze, and report on KPIs)
  • Metric Designer (Define, load, and maintain metrics to be available in Metric Studio)
  • Event Studio (Action based agents to notify decision makers as events happen)
  • Framework Manager (Semantic metadata layer tool which creates models or packages)
  • PowerPlay Studio (formerly PowerPlay Web)
  • Analytic Applications (Packaged BI Applications, built on an adaptable platform and extensible into Business Analytics)
  • Cognos 10.x

    We can see different components and how they are fitting in. The top most layer, where we can see Cognos Connection, Administrator, Business Insight and different studios. They all are web-based and end-user needs not to install any client side software if he has the latest web browser installed.

    The bottom layer is basically data layer where you may have homogeneous or heterogeneous database systems. Data may be relational or multi-dimensional. On top of it, we can see three modeling tools there — Framework Manager, Transformer, and Metric Designer. All of them are client based installation.

    We’ll maintain the flow of components from top to bottom as shown in below BI components figure.

    Before getting into the actual topics about how you create the model, deploy it and use it to create reports we have to first know the architecture of Cognos.

    Cognos Architecture:

    Cognos Business Intelligence framework is 3- tier architecture. The first tier of the architecture will be having the Web server which is responsible for the accessing the user interfaces. The second tier will be having IBM Cognos BI Server which will be having gateways and dispatchers to route requests from different UI’s to Database and communicate back to the server.

    The Third Tier will have the data sources. You can have multiple data sources and they will connect to the Cognos server using JDBC or API’s.

    The Below figure shows the architecture of Cognos BI:

    In the data tier, you can see one more component called the “Content Store” which is a repository for the Cognos server. Whenever you save any objects reports, models everything the data is stored in Content Store database which once you reopen or reuse the existing object created will fetch the data from the Content Store. All this work will be performed by the “Content Manager”.

    Content Manager: The content manager is responsible for connecting with the Content Store database and saving any report or model back to the Content Store.

    Dispatcher: The job of dispatchers is to route requests sent from and to the Web UI/Windows based components.

    Web-based and Windows Based components of Cognos

    Cognos BI has two types of components,

    1. Web-Based components.

    2. Window based components.

    Web-based components includes

  • Cognos Connection: This is the portal from where you can access all the web-based components of IBM Cognos BI.
  • Cognos Administration: Using this web-based UI you can perform administrative tasks like granting access, revoking access, creating users, groups and defining roles etc.,
  • Cognos Report Studio: Using Report studio tool we can create reports and format the reports. We can create multiple types of reports like list report, crosstab reports, graph’s etc.,
  • Cognos Query Studio: Here we create ad-hoc reports. Ad-hoc reports are useful when a user wants to see the report without any prompts and less formatting. Using query studio we can create a report instantly.
  • Cognos Metric Studio: This studio is used to build customized scorecards reports to monitor and analyze metrics.
  • Cognos Analysis studio: This studio is used to analyze data from different dimensions and also compare trends.
  • Cognos Business Insight: This tool is used to build dashboards. A dashboard allows a user to quickly look into the data and enhance the decision making.
  • Cognos Business Insight Advanced: With this tool, we can build more powerful dashboards and as well as simple reports.
  • Window-based Components:

  • Cognos Framework Manager: Cognos framework manager is a tool used to create metadata models which we can use in Report studio or analysis studio.
  • Cognos Map Manager: Using this tool we can create maps which will allow you to create a new region by using the existing regions.
  • http://www.abclearn.com/courses/cognos/cognos-tutorial/cognos-framework-manager



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