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BI0-132 Cognos 8 BI Metadata Model Developer

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BI0-132 exam Dumps Source : Cognos 8 BI Metadata Model Developer

Test Code : BI0-132
Test denomination : Cognos 8 BI Metadata Model Developer
Vendor denomination : Cognos
exam questions : 72 real Questions

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Cognos Cognos 8 BI Metadata

Cognos eight a success With users | killexams.com real Questions and Pass4sure dumps

Cognos eight successful With clients

users boom performance and usability improvements beget Cognos eight a a total lot greater desirable equipment

  • by way of Stephen Swoyer
  • 09/21/2005
  • From a competitive viewpoint, the collection eight commerce intelligence (BI) suite Cognos Inc. introduced remaining week turned into not always earth-shattering. in spite of everything, one in barnone its greatest selling points is integration: it’s the first Cognos unencumber according to the enterprise’s ReportNet structure; it boasts a unified user interface (UI); and it can provide what Cognos says is seamless integration between and among its BI services.

    but Cognos isn’t the primary supplier to bring as tons. On the integration entrance, anyway, the BI tremendous is a puny bit late to the party: company Objects SA delivered a unified version of its BI and reporting paraphernalia earlier this year, as did MicroStrategy Inc. in the meantime, facts mining and statistical evaluation champ SAS Institute Inc, long a peripheral BI participant, delivered what it calls a unified edition of its BI stack 18 months ago.

    but collection eight nevertheless has the makings of a vastly significant unlock. That’s as a result of Cognos purchasers can’t boom adequate decent things about it; and everybody is aware of the customer is king.

    basically, users are decidedly passionate about Cognos 8’s integration, and a lot of cite further efficiency and usability improvements that they deem aid beget the suite a plenty more fascinating package. From a consumer point of view, anyway, collection eight looks to live a winner.

    Take Louis Barton, director of facts warehousing for Cullen/Frost Bankers Inc., a financial maintaining commerce primarily based within the Southwest. an extended-time person of Cognos’ Impromptu reporting device, Cullen/Frost upgraded to the business’s ReportNet providing eventual 12 months. due to this fact, Barton says, sequence eight appears a herbal evolution, UI-smart, at the least. “It became frequent. It was less complicated, principally within the administration [of the BI tools]. I even accommodate lots of technical americans who toil for me... [and] they’re telling me that many things—primarily Metrics manager—are less demanding to administrate as a result of the UI being a lot more seamless than it become earlier than.”

    On the customer aspect, Barton says, Cognos eight addresses a couple of oft-lamented user ache elements. “One leading enviornment of frustration for us become now not being capable of accommodate the degree of integration between ReportNet and PowerPlay. these were the two biggies in their commerce that introduced us eighty % of the cost that they received from BI. So doing a ReportNet off of a cube is going to live big for us,” Barton says.

    Integration is only the tip of the spear, some users say. after all, Cognos’ ReportNet turns two this month—an eternity within the technology world. And in spite of the fact that Cognos refreshed that product with a 1.1 liberate, the novel Cognos eight BI suite fixes a number of of the revamped ReportNet’s shortcomings, too. “To accomplish drilling in ReportNet 1.1, you had to create two reviews, after which you’d drill via from one report to the different. You create a abstract file, and then you create a drill report and then you combine them via drilling,” explains David Wheat, supervisor of resolution pilot systems with United Agri products. “[But in Cognos 8] which you can deploy drill paths on the metadata layer: you profile them as soon as, after which ReportNet can permit these or disable [them]. The drill-up and drill-down capacity is far more superior than it was in 1.1; they can opt for if they are looking to accomplish the metadata layer, and accommodate the statistics live conscious that there’s a drilling choice.”

    furthermore, says John Hazenthal, director of competencies functions and facts management for transportation and logistics professional Schneider national Inc., the novel edition of ReportNet is a better performer than its predecessors. “One improvement they really noticed [with ReportNet] is the PDF-rendering. They pretty an nasty lot accomplish barnone of their reporting with PDF. In collection 7, what they discovered turned into that the PDF rendering changed into very CPU-intensive. it might actually rob an entire CPU for a portion of time whereas it become doing the PDF-rendering. They’ve completed loads of toil in Cognos 8 and that they’ve really mounted this, together with another performance enhancements,” he suggests.

    Hazenthal and other clients additionally cite advancements within the novel edition of Cognos Metrics manager. “there accommodate been some concerns with granularity of the Cognos Metrics supervisor metrics. What they had with chain 7 with Cognos Metrics supervisor, if you define your metrics for one enterprise unit at a month-to-month stage, they yield other company contraptions that might requisite to remark it at a weekly level. The granularity became greater at a worldwide [level], so if you define it month-to-month and that they wish to remark it weekly, you had to accomplish some particular issues to beget that happen.”

    Cullen/Frost’s Barton says he likes the brand novel Metrics supervisor’s UI. “The person interface [in chain 7] changed into a bit of awkward because you had to mosey to discrete monitors and different paths to accomplish what you crucial to do, and now it’s one lone route that allows you to streamline [its use],” he says.

    Requiem for Impromptu

    Cognos Impromptu may additionally no longer live the most powerful, flexible, or intuitive of reporting tools—therefore the impetus for ReportNet—however it’s noiseless typical in lots of corporations. When the Cognos 8 BI suite formally ships in November, although, the company’s next-gen ReportNet utensil will formally supplant Impromptu—which skill that the only upgrade course for valued clientele should live from Impromptu to ReportNet. It’s an unenviable circumstance, to live sure, however some Impromptu clients learn philosophical about it.

    Many cite the Cognos eight suite’s ReportNet architectural underpinnings and ReportNet-like UI, and boom Impromptu users will secure working towards in a ReportNet-like ambiance as a recollect of route. similarly, many routine to help to ReportNet as portion of their Cognos eight migration plans. of these, most look at the least okay with Cognos’ determination, even if it is going to very nearly definitely involve migration issues of 1 variety or one more.

    “We came on board with Cognos in late 1999, and the products we’re using are PowerPlay and the Impromptu client. They haven’t in reality upgraded to ReportNet, [although] they these days did buy ReportNet for operational reporting. We’re embedding the ReportNet reports inside their operational equipment’s purposes, so they’re known as without detain from the operational gadget,” says Schneider national’s Hazenthal.

    For his half, Hazenthal says he’s okay with Impromptu’s dying. He says ReportNet can live more convenient to manipulate, for starters, and—in aggregate with the revamped PowerPlay device (which is now called evaluation Studio)—should noiseless live a a total lot extra efficient solution. on the identical time, he stresses, for businesses like Schneider countrywide, Impromptu-to-ReportNet migration very nearly definitely gained’t live a cakewalk—inspite of the migration paraphernalia Cognos has made available.

    “[ReportNet] is something that’s very appealing to us. however they at present accommodate well over 1,000 [Cognos] Objects in construction. once I analyze migrating [Impromptu Web Reports] and [Cognos Query] to ReportNet, it’s going to live a protracted task,” he comments. adds Hazenthal. “we've about three,300 [Impromptu and PowerPlay] clients internal and external, so most of here is barnone web-enabled. they accommodate immediate to 9,000 Cognos Objects in their creation environment.”

    Mike Reeves, a supervisor for client tips functions with a renowned staffing company, has a in a similar way philosophical standpoint. despite the competencies migration considerations, the upgrade from Impromptu to ReportNet should live well value it, he says. “without doubt Impromptu is a very potent tool, nevertheless it’s not whatever which you can apportion in the hands of a person who doesn’t spend it ordinary, whereas in ReportNet and Cognos eight that you could try this very intuitively,” he comments. “[ReportNet is] a total lot extra intuitive, and you can prepare it in a way [so the user] can constitution their event.”

    Reeves says his enterprise’s exterior valued clientele is frequently a total lot happier with ReportNet—once the migration from Impromptu is finished. “For some of their customers, they’re barnone the time going to live the class of consumer that wants guidance pushed out to them. They accomplish accommodate a pretty genuine majority of their valued clientele that … just like the capacity to expect questions, and what it makes it workable for them to accomplish in Cognos eight is construct their own stories, store them, and that they can link and supply drill-via capabilities. It’s not something they deserve to live specialists on: it’s very intuitive.”

    concerning the creator

    Stephen Swoyer is a Nashville, TN-based freelance journalist who writes about know-how.


    Cognos collection 8 Is huge Hit with consumers | killexams.com real Questions and Pass4sure dumps

    news

    Cognos collection eight Is broad Hit with valued clientele
  • by way of Stephen Swoyer
  • 09/26/2005
  • From a competitive viewpoint, the sequence 8 commerce intelligence suite Cognos introduced ultimate week became now not always earth-shattering. in spite of everything, one among its greatest promoting points is integration: it’s the primary Cognos unencumber based on the business’s ReportNet architecture; it boasts a unified consumer interface; and it provides what Cognos says is seamless integration between and amongst its BI services.

    however Cognos isn’t the first dealer to convey as plenty. On the combination front, anyway, the BI massive is a puny bit late to the birthday party: enterprise Objects SA delivered a unified version of its BI and reporting tools previous this year, as did MicroStrategy. meanwhile, facts mining and statistical analysis champ SAS Institute, long a peripheral BI participant, delivered what it calls a unified version of its BI stack 18 months in the past.

    but chain eight nonetheless has the makings of a vastly noticeable release. That’s as a result of Cognos shoppers can’t boom adequate respectable things about it; and everyone is aware of the customer is king.

    basically, clients are decidedly enthusiastic about Cognos 8’s integration, and a lot of cite extra efficiency and value improvements they feel advocate beget the suite a a total lot greater attractive package. From a client viewpoint, anyway, sequence eight appears to live a winner.

    Take Louis Barton, director of data warehousing for Cullen/Frost Bankers, a economic retaining enterprise. A longtime consumer of Cognos’ Impromptu reporting tool, Cullen/Frost upgraded to the business’s ReportNet providing eventual yr. subsequently, Barton says, sequence 8 appears a natural evolution, UI-shrewd, as a minimum. “It turned into common. It turned into more straightforward, notably in the administration [of the BI tools]. I even accommodate loads of technical people who toil for me...[and] they’re telling me that many issues—specifically Metrics supervisor—are more convenient to administrate because of the UI being a lot more seamless than it was before.”

    On the customer aspect, Barton says, Cognos eight addresses a couple of oft-lamented user ache facets. “One leading enviornment of frustration for us became not being able to accommodate the diploma of integration between ReportNet and PowerPlay. those were both biggies in their company that introduced us 80 p.c of the cost that they received from BI. So doing a ReportNet off of a cube is going to live broad for us,” Barton says.

    Integration is only the tip of the spear, some clients say. after all, Cognos’ ReportNet turns 2 this month—an eternity within the expertise world. And in spite of the fact that Cognos refreshed that product with a 1.1 liberate, the novel Cognos 8 BI suite fixes a few of the revamped ReportNet’s shortcomings, too.

    “To accomplish drilling in ReportNet 1.1, you needed to create two stories, and then you’d drill via from one document to the different. You create a abstract file, after which you create a drill report, and then you connect them through drilling,” explains David Wheat, supervisor of choice aid systems with United Agri items. “[But in Cognos 8] that you can install drill paths on the metadata layer: you define them as soon as, and then ReportNet can permit those or disable [them]. The drill-up and drill-down skill is far more advanced than it turned into in 1.1; they are able to opt for if they want to accomplish the metadata layer, and accommodate the information live aware that there’s a drilling option.”

    furthermore, says John Hazenthal, director of potential services and facts administration for transportation and logistics specialist Schneider national, the novel edition of ReportNet is a higher performer than its predecessors. “One improvement they really noticed [with ReportNet] is the PDF-rendering. They pretty a mighty deal accomplish barnone of their reporting with PDF. In chain 7, what they discovered turned into that the PDF rendering became very CPU-intensive. it will literally rob an entire CPU for a portion of time whereas it was doing the PDF-rendering. They’ve accomplished lots of toil in Cognos 8, and that they’ve definitely mounted this, along with another efficiency enhancements,” he shows.

    Hazenthal and different users also cite improvements in the novel version of Cognos Metrics supervisor. “there were some considerations with granularity of the Cognos Metrics manager metrics. What they had with sequence 7 with Cognos Metrics manager, in case you define your metrics for one enterprise unit at a monthly level, they accommodate other company instruments that could are looking to remark it at a weekly degree. The granularity was extra at a worldwide [level], so in case you define it monthly and that they are looking to remark it weekly, you needed to accomplish some special issues to beget that happen.”

    concerning the writer

    Stephen Swoyer is a contributing editor for enterprise techniques. He can also live reached at stephen.swoyer@spinkle.net.


    Cognos Launches Cognos 8 BI v3 | killexams.com real Questions and Pass4sure dumps

    Cognos a issuer in commerce intelligence and efficiency management options, these days launched Cognos eight BI v3 which comprises novel and more advantageous BI consumer capabilities and advances in its SOA-primarily based commercial enterprise-class platform. These novel traits are designed to effectively give groups with more focused performance counsel across a broader and more discrete ambit of decision-makers, with extended modeling and administration capabilities to simplify deployment and renovation for administrators. Cognos eight BI v3 is the third main release of Cognos’ commerce intelligence flagship that was delivered in 2005. It addresses the needs of giant businesses and mid-market corporations alike as they capitalize on their ERP investments and revolve facts into actionable, primary performance tips for improved determination-making throughout industries. novel particularly focused tips delivery and superior evaluation capabilities let abilities worker's, starting from entrance-line managers to executives, receive strategic commerce counsel where, when and the way they want it to beget better decisions. novel deployment and administration advances additionally beget it less demanding for IT directors to deploy and maneuver their efficiency management atmosphere, while transforming into their user communities.

    “Cognos 8 BI v3 is a wealthy product providing with efficient benefits for company clients who can now rob expertise of observation-style reporting, enhanced navigation, richer visualization and enterprise-friendly tools for pile OLAP cubes,” stated Chad Erman, commerce Intelligence Lead, Southwestern power enterprise. “aspects like briefing books, bendy tips company and better dashboard filtering aid refine the style and high-quality of integral BI suggestions it is brought to key people, departments and company partners. With this product, each midsize corporations and massive organisations should live in a position to enhance the cost and relevance of their BI suggestions throughout barnone tiers and features of the company.”

    This BeyeNETWORK advice detail carries recommendation from a coincident press free up by the company outlined.


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    Cognos 8 BI Metadata Model Developer

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    Data Warehouse Concepts

    What is a Data Warehouse?

    A warehouse in common terms is a repository where they store their 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 routine for the future.

    The accepted 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, deem a KFC store. It has many branches barnone over the world. If they accommodate 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, deem the identical KFC store, stores in India may store date sphere as “dd/mm/yyyy” whereas the identical data in another country will live stored as “MM/DD/YYYY”. The data warehouse will accommodate only one format fixed to boom “MM/DD/YYYY”.
  • Time-Variant: A data warehouse stores historical data with which they can identify patterns of sales over a time term 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 they accommodate an organization established in many different locations and each location maintains a data warehouse which they muster it as data mart because a warehouse will accommodate barnone the data integrated and as far as data mart is considered it will live a portion of the data warehouse.

    What are uses of having a Data Warehouse?

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

    Data warehouse Architecture

    We will multiple sources there barnone the operational data will live stored. Some may store them in flat files and some in databases. They will accommodate to read barnone the sources and fulfill ETL (Extract, Transform and Load operations) which will live used to integrate data from these sources and transform them into one unique structure and then load into their 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 they are reading data from multiple sources and transforming the data and loading into your warehouse, then on top of that they are creating their data marts.

    Bottom-up Approach: The contrary of the above approach is this. Here they will live creating data marts first and then they will create their data ware house on top of barnone 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 they can actually design out what the dimension does.
  • Attribute: Attributes are the elements in a dimension  Ex: Suppose they accommodate 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, they accommodate to cipher 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 lone glance.
  • Types of OLAP’s:
  • Relational OLAP
  • Multi-dimensional OLAP
  • Hybrid OLAP
  • OLTP: Online transactional processing is a transaction based model where the main train will live to retrieve data faster and update transactions quickly.
  • Schemas in Datawarehouse

    The schema is a logical arrangement of tables in a data warehouse. They accommodate schemas in relational databases. Very much like identical 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 live at the seat of the schema surrounded by multiple dimension tables. Fact and dimension tables are linked via a Primary — Foreign Key relationship.  Fact table will live having strange keys of barnone the Dimension tables along with the facts whereas a Dimension table will live having attributes which limn the Dimension.

    Snowflake Schema:

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

    Fact Constellation Schema:

    A fact constellation schema, unlike the start or snowflake, will accommodate 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 strange key of barnone 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 detail and location are again connected to City and Supplier dimension respectively.

    Fact Constellation schema Example:

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

    Now they are jumping into the actual topic “Cognos commerce Intelligence”.

    Overall DWH architecture

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

    Let’s mosey through where BI will actually near into picture

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

    The below design will limn the commerce Intelligence stream how the data will live used for commerce optimization. commerce intelligence is a process from where you will live able to derive methods to enhance your commerce with the data that you have. Using BI one will live able to learn at their data at different levels and will live able to beget decisions to beget their commerce better.

    Cognos BI will live used to generate reports (list, crosstab, and charts). The below design will prove you the entire stream that happens with Cognos.

    The first step in using Cognos BI is to congregate requirements. This is workable when you understand your commerce 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 select either to you star schema or snowflake schema or you can spend the existing relational model.

    After this step is done with they accommodate to publish the model that they accommodate created. Publishing the model will beget your metadata model available for reporting purpose. Once your model is published, they can spend the model to create different types of reports as per your requirement and they 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 utensil was launched in September 2003. Since IBM’s acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet like barnone other Cognos products.

    Components:

  • Cognos Report Studio — A Web-based product for creating involved professional looking reports
  • Cognos Query Studio — A Web-based product for creating ad-hoc reports.
  • Cognos Framework Manager — A metadata modeling utensil to create BI metadata for reporting and dashboard applications.
  • Cognos Connection — the Main portal used to access reports, schedule reports and fulfill 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 utensil formatted for the web)
  • Query Studio (Ad hoc report authoring utensil with instant data preview)
  • Analysis Studio (Explore multi-dimensional cube data to retort commerce questions)
  • Metric Studio (Monitor, analyze, and report on KPIs)
  • Metric Designer (Define, load, and maintain metrics to live available in Metric Studio)
  • Event Studio (Action based agents to notify decision makers as events happen)
  • Framework Manager (Semantic metadata layer utensil which creates models or packages)
  • PowerPlay Studio (formerly PowerPlay Web)
  • Analytic Applications (Packaged BI Applications, built on an adaptable platform and extensible into commerce Analytics)
  • Cognos 10.x

    We can remark different components and how they are fitting in. The top most layer, where they can remark Cognos Connection, Administrator, commerce Insight and different studios. They barnone 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 accommodate homogeneous or heterogeneous database systems. Data may live relational or multi-dimensional. On top of it, they can remark three modeling tools there — Framework Manager, Transformer, and Metric Designer. barnone of them are client based installation.

    We’ll maintain the stream 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 spend it to create reports they accommodate to first know the architecture of Cognos.

    Cognos Architecture:

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

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

    The Below design shows the architecture of Cognos BI:

    In the data tier, you can remark one more component called the “Content Store” which is a repository for the Cognos server. Whenever you redeem any objects reports, models everything the data is stored in Content Store database which once you reopen or reuse the existing demur created will fetch the data from the Content Store. barnone this toil will live performed by the “Content Manager”.

    Content Manager: The content manager is answerable 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 barnone the web-based components of IBM Cognos BI.
  • Cognos Administration: Using this web-based UI you can fulfill administrative tasks like granting access, revoking access, creating users, groups and defining roles etc.,
  • Cognos Report Studio: Using Report studio utensil they can create reports and format the reports. They can create multiple types of reports like list report, crosstab reports, graph’s etc.,
  • Cognos Query Studio: Here they create ad-hoc reports. Ad-hoc reports are useful when a user wants to remark the report without any prompts and less formatting. Using query studio they 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 commerce Insight: This utensil is used to build dashboards. A dashboard allows a user to quickly learn into the data and enhance the decision making.
  • Cognos commerce Insight Advanced: With this tool, they can build more powerful dashboards and as well as simple reports.
  • Window-based Components:

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


    Too Much Pessimism Discounted Into MicroStrategy Shares | killexams.com real questions and Pass4sure dumps

    No result found, try novel keyword!We are modeling 8.5% margins ... hosts metadata, and performs most administrative tasks, enabling companies to implement their commerce intelligence solution more quickly and simply compared to a trad...

    Data Extraction Methods portion 2 | killexams.com real questions and Pass4sure dumps

    In portion 1 they discussed data extraction which gets the total table every time, and the first 3 methods of incremental data extraction, e.g. using using timestamp columns, using identity column, and using triggers. They will now contend the remaining three, e.g. using transaction date, combination of the above and using off-the-shelf tools, and finally the fixed term method.

    2d. Incremental Extract Using Transaction Date

    If there is no genuine create and update datestamp or timestamp columns in the source table, and it is not workable to apportion triggers in the source system, and there is no identity column either, then their next best option for incremental data extraction is to spend transaction date column. By this I addupto columns which contains the date the transaction happen.

    Generally speaking, there are 2 major categories of tables in an ERP system or commerce system, or as the data warehouse community muster it, OLTP system (in contrast with OLAP that they accommodate in data warehouse system). The first category is the 'master' tables. Tables such as product, customer, supplier, account, status code, product group, store, and disposal site. In the data warehouse star schema, these tables become the dimension tables. The second category is "transaction" tables. Tables such as sales order header, sales order detail, purchase order header, purchase order detail, inventory transaction, account transaction, cost review and disposal. In the data warehouse star schema, these transaction tables become the fact tables.

    If the table they extract is a transaction table, it normally has one or more transaction date columns. In an order header table, it is common to find the following transaction date columns

  • order date - the date the order was placed by the customer
  • system order date - the date the order header record was created
  • estimated delivery date - the date the order suppositious to live out of their door
  • actual delivery date - the date the order really out of their door
  • The contrast between order date and system order date is that: if the order came by fax yesterday and it is typed into the system today, order date will live typed as yesterday whilst the system order date will live today's date. Operator has no control on this column, it is maintained internally by the system. please note that in better ERP systems, to enable partial delivery, the estimated and actual delivery dates are apportion on the order detail table rather than order header table.

    In the above example, system order date is an excellent transaction date. It is guaranteed to live greater than or equal to today. Orders which happened later accommodate later system order date as well. That makes this column, in a way, sequential, just like an identity column. The order date column, on the other hand, can live deceiving, because user can sort a past date on it. This understanding a problem, as they can not live certain which orders near after which orders.

    The basic syntax of the ETL select statement is generally the identical as the ones for datestamp / timestamp column, e.g. SELECT col1, col2 FROM table1 WHERE trans_date_col >= LSED. If they only deals with date (not with time as well), there is puny point constraining the maximum.

    So that's for inserts. How about deletes and updates? Well, simply speaking, they can't secure deletes and updates using transaction dates. They requisite to spend other methods to secure them. This restriction made us often accommodate to combine this routine with fixed term routine (see point 3 below), for example. they download eventual 6 weeks every time, based on transaction date column.

    2e. Combination Of The Above

    Sometimes they requisite to combine the above 4 methods, to suit the condition of the source table, to secure barnone inserts, updates and deletes. Inserts are generally the easiest to get. They can spend barnone for methods to secure inserts: timestamp column, incremental column, triggers and transaction date column. For deletes they can can spend timestamp, incremental column or triggers. To secure updates they can spend CRC and triggers. Yes triggers can live spend to secure barnone 3 kinds of changes, incrementally.

    2f. Using Off-The-Shelf Tools

    Now a days to secure or extract the data out of commerce system is getting easier. Some BI companies accommodate written ETL package for most accepted commerce systems such as SAP, Oracle applications, Siebel, PeopleSoft and J.D. Edwards. In the BI industry, these ETL packages are normally called Data Integration (DI) software. They install the DI software, set some parameters, and off you go. It extracts the data from their commerce systems into their data warehouse. Isn't that wonderful?

    Well in reality it's not as straight forward as that. They noiseless accommodate to accomplish data analysis (profiling) and data property process. They noiseless accommodate to customise it a puny to suit their commerce system and to suit their data warehouse. But they don't start from stratch, most definitely not. Below they try to illustrate the situation by describing a few DI software that are around in the market, along with the links.

  • IBM Web Sphere Information Integration (formerly Ascentia)DataStage extracts, transforms and loads data. ProfileStage analyses source data, creates data model, generate source to target mappings, and generate ETL routine. QualityStage detects data duplication, inconsistencies and missing data. Package Application Connectivity Kits (PACKS) helps connect to SAP R/3 and BW, Oracle, Siebel, PeopleSoft and JD Edwards systems and extract data from them. Supports most RDBMS.
  • Informatica PowerExchange and PowerCenterPowerExchange Changed Data Capture operates within the source environment to detect data updates and to deliver them in real time or batch. PowerCenter transform and load data; it also offers cleansing and profiling. Most RDBMS are supported.
  • BusinessObject DataIntegratorDefine data mapping and transformation. Cleanse (integration with FirstLogic), preview and profile data. Has prebuilt transformations. Creates portable ETL jobs. Integrates with SAP R/3 and BW, Oracle, Siebel, PeopleSoft and JD Edwards. advocate most RDBMS.
  • Pervasive Data Integrator (formerly Data Junction)Extract, transform and load data. Creates ODS. real time or batch execution. Integrates with SAP, Goldmine, Solomon, mighty Plains, Navision, SAS, Market Force, Salesforce, and many accounting packages: AccountMate, ACT, Champion, Platinum , Macola, Peachtree, RealWorld, CYMA, etc. advocate a comprehensive list of RDBMS.
  • Hummingbird GenioExtract, transform and load data. Integrates with SAP.
  • SAS DataFluxExtract, transform and load data. Has data profiling and data property capabilities. Integrates with SAP R/3, Siebel, Oracle Warehouse Builder, Informatica. advocate most RDBMS.
  • Cognos 8 BI Data Integration (formerly DecisionStream)Extract, transform and load data. Integrates with SAP R/3 and Siebel CRM. advocate most RDBMS.
  • DataMirror Transformation ServerUses database log files to capture changed data to deliver them real time.
  • Microsoft SQL Server 2005 Integration Services (formerly DTS)Extract, transform and load data. advocate most RDBMS.
  • CA odds Data TransformerExtract, transform and load data. Integrates with SAP R/3. advocate most RDBMS. Platinum InfoPump, InfoHub, and InfoRefiner were acquired by CA.
  • Oracle Warehouse BuilderExtract, transform and load data. Integrates with SAP (produces ABAP code). Carleton Pasport was acquired by Oracle.
  • Embarcadero DT/StudioExtract, transform and load data. Changed data capture delta agent. Data profiling and metadata import/export. advocate most RDBMS.
  • Sybase Enterprise ConnectReplication Agents for Informix, Oracle, and Adaptive Server Anywhere. advocate most RDBMS.
  • ETI SolutionExtract, transform and load data. Integrates with Siebel, WebSphere MQ and ClickStream. advocate most RDBMS.
  • Ascentia (now IBM) and Informatica are probably the most accepted data extraction tools in the BI market now a days. BusinessObject, Genio and DataFlux are decent, but I prefer to spend SSIS as personal choice. Informatica, DataMirror and Oracle CDC (changed data capture) could live a life saver in some situation where they must extract incrementally. Alkis Simitsis compiled a comprehensive list of ETL tools, which might worth having a learn if you want to explore some of the nice players.

    Vincent Rainardi29th March 2006



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