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BI0-122 exam Dumps Source : Cognos 8 BI Administrator v2

Test Code : BI0-122
Test cognomen : Cognos 8 BI Administrator v2
Vendor cognomen : Cognos
exam questions : 45 true Questions

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Cognos Cognos 8 BI Administrator

Cognos Launches Cognos 8 BI v3 | true Questions and Pass4sure dumps

Cognos a provider in industry intelligence and efficiency administration options, recently launched Cognos eight BI v3 which includes current and greater BI consumer capabilities and advances in its SOA-primarily based commercial enterprise-category platform. These current trends are designed to successfully supply corporations with greater centered performance information throughout a broader and more diverse sweep of resolution-makers, with extended modeling and administration capabilities to simplify deployment and renovation for directors. Cognos eight BI v3 is the third principal unencumber of Cognos’ company intelligence flagship that become delivered in 2005. It addresses the needs of gigantic corporations and mid-market agencies alike as they capitalize on their ERP investments and circle records into actionable, captious efficiency information for enhanced choice-making across industries. current highly targeted counsel nascence and superior analysis capabilities let skills workers, starting from front-line managers to executives, receive strategic enterprise suggestions where, when and how they want it to construct improved decisions. current deployment and administration advances besides construct it less difficult for IT directors to set up and control their performance management atmosphere, whereas turning out to breathe their person communities.

“Cognos 8 BI v3 is a loaded product offering with improbable merits for company users who can now seize skills of remark-trend reporting, more advantageous navigation, richer visualization and business-pleasant tools for constructing OLAP cubes,” mentioned Chad Erman, enterprise Intelligence Lead, Southwestern power enterprise. “features enjoy briefing books, bendy assistance corporation and improved dashboard filtering uphold refine the fashion and pleasant of quintessential BI counsel this is dropped at key people, departments and company partners. With this product, each midsize companies and great corporations may soundless breathe in a position to enhance the price and relevance of their BI information across total tiers and functions of the corporation.”

This BeyeNETWORK news item contains suggestions from a fresh press release through the enterprise mentioned.

Cognos basics Tutorial — ABC learn | true Questions and Pass4sure dumps

facts Warehouse ideas

what is an information Warehouse?

A warehouse in time-honored terms is a repository the position they store their assistance. Coming to the information warehouse, it's a collection of statistics geared up in a selected mode and categorised counsel.

an information warehouse retailers historical facts of an organization as a route to dissect their performance over the final years and arrangement for the longer term.

The frequent definition of the data warehouse by means of WH Inmon:

a learning warehouse is:

  • discipline oriented: records within the warehouse is categorised in diverse discipline areas. for example, dependence a KFC shop. It has many branches total over the world. If they must dissect “income” for India, this is termed as “area”.
  • integrated: an information warehouse has statistics coming from distinct sources which can breathe built-in into the warehouse. for instance, accept as fair with the identical KFC shop, outlets in India may additionally shop date bailiwick as “dd/mm/yyyy” whereas the very records in a different country should breathe stored as “MM/DD/YYYY”. The records warehouse could absorb only 1 format fixed to articulate “MM/DD/YYYY”.
  • Time-Variant: an information warehouse outlets ancient information with which they can establish patterns of revenue over a time term of three months,6 months or 2 years of any organization which has a warehouse.
  • Non-risky: data within the warehouse will now not change once it's entered.
  • an additional definition from Ralph Kimball is more actual:

    a data warehouse is a duplicate of transaction statistics exceptionally structured for question and evaluation.

    what's a data mart?

    a learning mart is a subset of an information warehouse. believe they absorb a company contingent in a variety of places and each vicinity keeps a learning warehouse which they cognomen it as data mart as a result of a warehouse can absorb total the information built-in and as far as statistics mart is regarded it should breathe fragment of the data warehouse.

    What are makes utilize of of getting an information Warehouse?

    a learning Warehouse, in frequent, is used to dissect developments over a duration of time and enhances the determination making of a firm. once the facts is loaded into the warehouse may breathe creating an OLAP cube or at once utilize the information to dissect trends. Basing on which the excellent degree administration will strategy their future industry innovations.

    facts warehouse architecture

    we will multiple sources there total of the operational information can breathe kept. Some may withhold them in flat information and some in databases. they are able to requisite to examine the entire sources and execute ETL (Extract, transform and load operations) which can breathe used to combine facts from these sources and radically change them into one inspiring constitution and then load into their goal information warehouse.

    facts Warehouse structure

    There are 2 methods in designing your records warehouse. First one is “suitable-Down strategy” and 2nd is “bottom-up method”.

    appropriate — Down method: The above vivid indicates the desirable-down strategy, the position we're studying records from dissimilar sources and transforming the information and loading into your warehouse, then on fair of that we're creating their information marts.

    bottom-up strategy: The opposite of the above mode is that this. here they may breathe growing facts marts first and then they are able to create their facts ware condominium on proper of total the statistics marts.

    information Warehouse phrases

  • Dimension: A Dimension is a specific suggestions which is saved in a data warehouse.
  • fact: fact is a measurable volume during which they will actually pattern out what the dimension does.
  • Attribute: Attributes are the facets in a dimension  Ex: umpire they now absorb product tips categorized in a dimension. The attributes of the “Product dimension” are: “Product_ID, Product_Name, Product_Color” and many others.  income is a truth desk the position you deliver numeric values associated with the dimension attributes.for instance, they requisite to calculate the number of sales of every product for the existing this case, Product is the dimension and Month is a dimension and numbers of product offered is the truth.
  • OLAP: on-line Analytical Processing is a multidimensional model the utilize of which clients can view information in diverse dimensions at a single look.
  • kinds of OLAP’s:
  • Relational OLAP
  • Multi-dimensional OLAP
  • Hybrid OLAP
  • OLTP: on-line transactional processing is a transaction based mostly model the position the leading train will breathe to retrieve data faster and supersede transactions immediately.
  • Schemas in Datawarehouse

    The schema is a ratiocinative association of tables in an information warehouse. we've schemas in relational databases. Very plenty enjoy identical records warehouse has schema’s particularly star schema, Snowflake schema, and truth-Constellation.

    megastar Schema

    in this ratiocinative association of tables, the reality table will breathe at the middle of the schema surrounded by means of multiple dimension tables. truth and dimension tables are linked by the utilize of a primary — foreign Key relationship.  truth table should breathe having exotic keys of total the Dimension tables together with the facts whereas a Dimension table can breathe having attributes which picture the Dimension.

    Snowflake Schema:

    in this ratiocinative association of tables, they absorb dimension tables related to other dimension tables which in circle are connected to fact desk by means of a primary-international key relationship.  Else they will articulate that the Dimension tables in Snowflake schema are normalized.  on account of the normalization, the facts redundancy should breathe decreased and a lot of storage space is saved.

    fact Constellation Schema:

    A fact constellation schema, in contrast to the birth or snowflake, could absorb multiple fact tables. it is besides called as Galaxy Schema.

    big cognomen Schema example

    during this schema shown, a reality desk (sales) is related to distinctive dimension tables merchandise, place, time and department. each and every dimension desk has attributes describing the dimension and reality table has the international key of total dimension tables along with records enjoy dollars_sold and units sold.

    Snowflake Schema instance:

    in this schema, a truth table (sales) is connected to dissimilar dimensions, whereas the scale item and site are once again connected to metropolis and organization dimension respectively.

    truth Constellation schema example:

    in this schema, they will locate two truth table income and transport connecting with each other and are once more linked to numerous dimension tables individually.

    Now they are jumping into the exact topic “Cognos industry Intelligence”.

    general DWH structure

    We might breathe coping with Cognos reporting tool and Cognos Metadata managing device and other valuable tools that Cognos BI has.

    Let’s dart through the position BI will really promote into photograph

    The beneath picture shows benchmark statistics warehouse architecture. From facts load to using the data loaded into the tables for enhancing the industry of your company. From total of the information sources (can besides or not it's Operational databases, Flat data etc.) they load the data into statistics warehouse via distinctive ETL procedure and creating cubes and the usage of the statistics for mining goal.

    The under pattern will picture the industry Intelligence movement how the information could breathe used for company optimization. industry intelligence is a technique from where you should breathe able to derive tips on how to enhance your company with the statistics that you've got. the utilize of BI one will breathe in a position to ascertain at their information at diverse degrees and will breathe in a position to construct selections to construct their industry stronger.

    Cognos BI can breathe used to generate studies (listing, crosstab, and charts). The beneath pattern will betray you the total movement that occurs with Cognos.

    the first step in the usage of Cognos BI is to accumulate necessities. here's workable if you breathe watchful your industry structure and the information that drives your enterprise. once the requirement is finalized the subsequent step is to create your framework metadata model. you can choose both to you superstar schema or snowflake schema otherwise you can utilize the present relational model.

    After this step is done with they requisite to publish the model that they absorb created. Publishing the model will construct your metadata mannequin accessible for reporting intention. once your model is posted, they can utilize the mannequin to create different types of experiences as per your requirement and they are able to schedule the experiences basing your requirement.

    distinctive versions of Cognos

    Cognos ReportNet

    Cognos ReportNet (CRN) is an internet-based software product for developing and managing advert-hoc and custom-made studies. ReportNet is developed by means of the Ottawa-based mostly enterprise Cognos (formerly Cognos incorporated), an IBM company. The internet-primarily based reporting tool became launched in September 2003. since IBM’s acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet enjoy several different Cognos items.


  • Cognos document Studio — a web-based product for creating involved knowledgeable searching stories
  • Cognos question Studio — a web-primarily based product for developing ad-hoc experiences.
  • Cognos Framework manager — A metadata modeling device to create BI metadata for reporting and dashboard functions.
  • Cognos Connection — the main portal used to entry studies, time table reviews and role administrator actions.
  • Cognos 8.x

    IBM Cognos eight BI, originally launched in September 2005, combined the features of a few previous items, together with ReportNet, PowerPlay, Metrics supervisor. There are additionally express and prolonged types of Cognos eight BI. replete points:


  • file Studio (skilled report authoring device formatted for the internet)
  • query Studio (advert hoc report authoring device with lickety-split statistics preview)
  • evaluation Studio (discover multi-dimensional dice facts to reply industry questions)
  • Metric Studio (computer screen, analyze, and report on KPIs)
  • Metric dressmaker (outline, load, and retain metrics to breathe obtainable in Metric Studio)
  • event Studio (motion based mostly agents to notify selection makers as events happen)
  • Framework supervisor (Semantic metadata layer device which creates fashions or packages)
  • PowerPlay Studio (previously PowerPlay internet)
  • Analytic functions (Packaged BI applications, built on an adaptable platform and extensible into enterprise Analytics)
  • Cognos 10.x

    we can behold distinct components and how they are becoming in. The properly most layer, where they are able to behold Cognos Connection, Administrator, enterprise insight and distinctive studios. total of them are internet-primarily based and conclusion-user needs now not to set up any customer aspect utility if he has the newest web browser installed.

    The backside layer is truly records layer the position you might besides absorb homogeneous or heterogeneous database methods. records can breathe relational or multi-dimensional. On privilege of it, they can behold three modeling tools there — Framework supervisor, Transformer, and Metric clothier. total of them are client primarily based installation.

    We’ll retain the stream of add-ons from accurate to backside as shown in below BI components figure.

    before stirring into the actual topics about the route you create the mannequin, set up it and utilize it to create reports they must first recognize the architecture of Cognos.

    Cognos architecture:

    Cognos industry Intelligence framework is three- tier structure. the primary tier of the structure should breathe having the net server which is accountable for the getting access to the consumer interfaces. The 2nd tier might breathe having IBM Cognos BI Server which may breathe having gateways and dispatchers to route requests from distinct UI’s to Database and speak returned to the server.

    The Third Tier can absorb the facts sources. which you could absorb distinct statistics sources and they will connect with the Cognos server the usage of JDBC or API’s.

    The under pattern shows the structure of Cognos BI:

    within the data tier, that you could behold an additional component known as the “content material shop” which is a repository for the Cognos server. each time you store any objects studies, models every thing the information is kept in content material deliver database which once you reopen or reuse the current kick created will fetch the information from the content material store. total this drudgery should breathe carried out by means of the “content supervisor”.

    content material supervisor: The content material supervisor is chargeable for connecting with the content store database and saving any file or model back to the content save.

    Dispatcher: The job of dispatchers is to route requests sent from and to the web UI/windows based mostly accessories.

    web-primarily based and home windows based add-ons of Cognos

    Cognos BI has two kinds of components,

    1. internet-based mostly accessories.

    2. Window based mostly components.

    internet-based components contains

  • Cognos Connection: here's the portal from the position that you may entry total the web-primarily based components of IBM Cognos BI.
  • Cognos Administration: the utilize of this net-based mostly UI you can execute administrative initiatives enjoy granting access, revoking entry, growing clients, agencies and defining roles etc.,
  • Cognos record Studio: the usage of document studio tool they will create reports and format the reports. they can create multiple sorts of reports enjoy checklist report, crosstab stories, graph’s etc.,
  • Cognos query Studio: here they create ad-hoc studies. ad-hoc studies are positive when a person wishes to peer the record with nothing prompts and less formatting. using query studio they will create a record instantly.
  • Cognos Metric Studio: This studio is used to construct personalized scorecards reports to video display and dissect metrics.
  • Cognos analysis studio: This studio is used to dissect facts from distinct dimensions and additionally evaluate tendencies.
  • Cognos company perception: This tool is used to construct dashboards. A dashboard allows for a user to at once look into the data and raise the determination making.
  • Cognos company perception superior: With this device, they can build extra powerful dashboards and in addition to essential stories.
  • Window-based add-ons:

  • Cognos Framework manager: Cognos framework manager is a tool used to create metadata models which they are able to utilize in report studio or evaluation studio.
  • Cognos Map manager: the utilize of this tool they can create maps so that it will will let you create a current location through the utilize of the current regions.

    Cognos To manage efficiency Of Ramboll | true Questions and Pass4sure dumps

    Cognos has introduced that Ramboll group has chosen it to enrich consolidation, planning and reporting tactics across the enterprise.

    Ramboll would implement Cognos eight BI, Cognos Planning and Cognos Controller. in accordance with the enterprise, it offers full-carrier consultancy and capabilities in infrastructure, telecommunications, building, fitness, trade, oil/fuel, energy, ambiance, IT, and management.

    The group says that speedy growth in keeping with evolution as well as mergers will outcome in a challenging planning and reporting ambiance and it wants an reply for gaining a better understanding of enterprise performance.

    After a comparison of reporting options, Cognos became chosen to force efficiency management. Ramboll keeps that it chose Cognos because it allows the corporation to standardize consolidation, reporting and planning necessities on a single solution thereby enabling users to video display and dissect company efficiency.

    The Cognos Innovation core for performance management provides key trade purposeful journey and consolidation best practices to Ramboll by means of personalized workshops and visioning classes.

    “at the moment, sizeable endeavor is required to manually extract monetary and operational data from legacy techniques and databases and enter into spreadsheets for evaluation and reporting,” observed Sari Kaikkonen, community CFO, Ramboll community.

    in the coming months, Ramboll deploys Cognos options that automates and streamlines reporting and planning approaches. The preparatory deployment would roll to 400 employees.

    “Our resilient performance management solution allows Ramboll to drastically reduce back the time to create budgets, forecasts and stories, enabling the finance fork to disburse extra materials on inspecting effects and strategic initiatives,” pointed out Dave Laverty, CMO & Sr. VP - global advertising, Cognos.

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    Mega-vendors dominate Gartner's 2010 BI, data warehouse Magic Quadrants | true questions and Pass4sure dumps

    Mega-vendors soundless dominate the industry intelligence (BI) software market, but their stranglehold may breathe loosening as disgruntled customers originate to ascertain for lower-priced, more resilient options from BI pure-plays.

    SAP and IBM BI customers, in particular, report lower levels of satisfaction as the mega-vendors continue to iron out their BI product roadmaps and adjust uphold and maintenance fees, according to Gartner's BI Magic Quadrant report, released final week.

    With a weak economy, customers are increasingly looking for cheaper, quicker-to-deploy options enjoy BI embedded within packaged analytic applications and, to a lesser extent, SaaS BI to meet their reporting and analytic needs, said Rita Sallam, an analyst with the Stamford, Conn.-based research firm and co-author of the report.

    "Many [BI] pure-plays are leveraging industry user impatience with enterprise BI systems and are delivering alternative easy-to-use-and-deploy architectures, alternative industry models, and a stout customer focus -- so much so that in many cases industry users continued to buy non-stack solutions even when a stack benchmark is in place," Sallam said in an email interview.

    The related data warehouse market is experiencing a similar phenomenon. According to Gartner's Data Warehouse Magic Quadrant, besides released final week, smaller data marts and virtual data warehouses that utilize federation technology are enjoying renewed popularity as companies ascertain to expand flexibility while keeping costs down.

    Higher performance requirements from customers are besides pushing data warehouse vendors to ameliorate the power of their products through the addition of in-database analytics and column architectures, according to Gartner's Donald Feinberg, who co-authored the report on data warehouses.

    Data warehouse appliances -- server and storage hardware bundled with analytic databases -- besides continue to gain in popularity thanks to their ease of implementation and support, he said.

    "The bottom line is [customers] want to convene one person for support" when there is a problem with performance, Feinberg said.

    Still, in both markets, neither customer unrest nor the wish for quicker, cheaper deployments made much of a dent in the mega-vendors' dominant market share positions, Gartner said. Mega-vendors are themselves responding with more BI and DW deployment options, either developed internally or through acquisition.

    "I umpire there are a few reasons why customers continue to buy into the stack despite an expand in dissatisfaction," Sallam said. "Stack-centric buying is largely IT driven, and stack vendors covenant a one-stop shop. They often present abysmal discounts or bundle BI platform capabilities with other parts of the mega-vendor stack (e.g., applications or information infrastructure) and present the covenant of integration and optimization with their respective applications and information management stacks."

    Three mega-vendors top both BI and data warehouse markets

    Appearing in the leaders' quadrants in both the BI and data warehouse Magic Quadrant reports were Oracle, IBM and Microsoft.

    Oracle's BI platform has the widest sweep of capabilities among the top vendors, including reporting, dashboarding and ad hoc query functionality. The vendor besides offers three distinct data warehousing options, -- Oracle Database 11g, Oracle Reference Configurations, and Oracle Exadata v2 -- "giving customers a wide variety of choices," the report said.

    IBM's core BI platform, IBM Cognos 8, was cited for its architectural consistency, "with IBM Cognos customers reporting that they requisite only three administration staff per thousand users on average," the BI Magic Quadrant report states. enjoy Oracle, IBM has a number of data warehouse products to meet varying needs.

    Microsoft, meanwhile, continues to construct inroads in both markets thanks to the ubiquity of its tools -- mainly Excel, SQL Server, and SharePoint Server, according to Gartner. Microsoft will probably expand its market share in 2010 when it debuts PowerPivot, an surpass add-on for BI and analytics, and SQL Server 2008 R2 Relational Database, which is likely to seize the form of an appliance.

    "The significance is that total three … absorb the replete spectrum of information infrastructure technologies from the database [including hardware in the case of IBM and Oracle] through the middleware stack and -- in the case of Oracle, SAP and Microsoft -- the enterprise applications as well," Sallam said. "Stack vendors execute absorb an odds in that they can optimize their BI platforms for their respective application and information management stacks."

    While the top positions in the BI Magic Quadrant were bunched together -- Oracle and Microsoft earned virtually the very ranking -- Teradata was the lucid leader in data warehousing. Gartner cited the vendor's products' ability to manipulate mixed workloads without hindering performance, including near real-time data loading, tactical industry analytics and an increasing number of ad hoc queries.

    "Teradata's solutions, which comprise the data warehouse platform, data models and professional services dedicated to data warehousing, set it apart from the rest of the market," Feinberg wrote.

    Also earning a position in the BI leaders' quadrant were SAS Institute, Microstrategy, SAP, and Information Builders. Netezza and Sybase rounded out the leaders' quadrant for the data warehouse market.

    SaaS, open source BI deployments soundless petite but increasing

    While soundless a petite percentage of overall deployments, SaaS BI, delivered both from internal and the public cloud, is slowly but steadily gaining traction, according to Gartner.

    "This growth will breathe accelerated by organizations' increasing requisite to deploy intuitive BI tools and applications cost-effectively to more users, reduce time to value and time to scale, and lower capital expenditures," Sallam wrote.

    SAP and SAS Institute absorb the largest number of SaaS BI deployments, but smaller up-and-coming vendors enjoy Birst, GoodData, Oco and PivotLink are besides getting attention, the report states.

    Cloud-based data warehousing, on the other hand, has yet to seize off, for a number of reasons, according to Gartner. "The issues around the security, multi-tenancy and latency of utilize of the Internet as a transport for data loading are among the reasons given for the reluctance to locate the data warehouse in the cloud," Feinberg wrote.

    Gartner predicted that both the BI and data warehouse markets would continue to grow this year as companies ascertain to the software to circle their corporate data into competitive differentiators.

    MicroStrategy's (MSTR) CEO Michael Saylor on Q1 2018 Results - Earnings convene Transcript | true questions and Pass4sure dumps

    No result found, try current keyword!Sales and marketing expenses increased to $11.8 million at 30% year-over-year and decreased $0.6 ... And so as SAP and IBM, and Oracle shift their commitments away from their BI enterprise platforms t...

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