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BI0-122 Cognos 8 BI Administrator v2

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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
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Cognos Cognos 8 BI Administrator

In a Nutshell: Reviewing through IBM Cognos BI audience | killexams.com actual Questions and Pass4sure dumps

This chapter is from the engage 

counting on your position in IBM Cognos BI venture implementation, you may additionally subsist interested to know those points of IBM Cognos query Studio that relate to your role on the assignment. Following aspects evaluation IBM Cognos question Studio through role at a towering degree.

Architect standpoint

Architects are interested to understand the capabilities of the product, so they can correctly intimate a appliance or component for the overall BI implementation. question Studio is a core component of IBM Cognos BI and is establish in with the Cognos BI software set up. query Studio is an conclusion user advert-hoc question appliance consummate for company authors and enterprise analysts to advocate them explore the facts for his or her a variety of company questions. It makes consume of the current IBM Cognos BI safety and statistics sources already defined in the IBM Cognos BI atmosphere. one of the key elements to trust observe:

  • Cognos Workspace superior is the rational upgrade direction for question Studio for IBM Cognos BI v10.x clients. for brand novel shoppers, Cognos Workspace superior as an alternative of question Studio is recommended. For legacy IBM Cognos 8.x clients, they can continue to consume current studies in query Studio; however, it is suggested to consume Cognos Workspace superior for creating fresh reviews.
  • question Studio is an end-user device and can subsist used as quickly as the metadata package has been posted to IBM Cognos Connection.
  • question Studio can consume dimensionally and relationally modeled facts from Framework manager.
  • query Studio is an advert-hoc query and statistics exploration appliance that may likewise subsist advised to traffic clients.
  • venture manager standpoint

    mission Managers own an interest in knowing if query Studio has been identified and advised as a fragment of the IBM Cognos BI answer. If it may subsist used, what are the related tasks, what capabilities and components are required to implement the tasks, and what section enact these belong to? listed here are some aspects to accept as sincere with:

  • Cognos Workspace advanced is the suggested better course for query Studio for IBM Cognos BI v10.x users. Legacy IBM Cognos 8.x users can consume their existing question Studio studies from the IBM Cognos BI 8.x environment within the IBM Cognos BI v10.x atmosphere after the improve.
  • query Studio is an conclusion-user appliance for facts exploration and ad-hoc query to avow brief traffic questions and is centered for traffic users and company analysts.
  • company clients can start the usage of question Studio as soon as the Framework manager kit is published through the metadata modeler. It doesn't require any other chore to subsist achieved earlier than users can delivery using question Studio in a nonsecured ambiance. If the package carries exquisite facts, the kit exigency to subsist secured in an IBM Cognos BI ambiance earlier than turning it over to the conclusion clients.
  • question Studio is a component of the IBM Cognos BI application set up and doesn't exigency to subsist purchased one by one.
  • business Analyst perspective

    business Analysts should still subsist close with the features of question Studio and Cognos Workspace advanced, so that you can steer the conclusion users correctly. Cognos Workspace superior is the rational better route for question Studio users in IBM Cognos 8.x environment. purchasers upgrading from IBM Cognos eight.x environment can consume their present queries and experiences in IBM Cognos v10.x environment the consume of query Studio within the novel ambiance. for brand spanking novel queries and experiences, it should subsist counseled that they consume Cognos Workspace superior. the usage of Cognos Workspace advanced, they can consume the stronger aspects purchasable to them. one of the key features to accept as sincere with observe:

  • query Studio is an end-user appliance for company clients and enterprise analysts to back them reply their many traffic questions via dragging and dropping gadgets to the file, making consume of filters, and developing calculations.
  • query Studio uses dimensionally and relationally modeled records. For dimensionally modeled facts, the scale, hierarchies, degrees, and measures (metrics or Key efficiency warning signs), the requirement should subsist obviously understood and captured to enable the metadata modeler to construct applicable kit.
  • users can additionally access experiences with aspect statistics by means of the drill-through options. If such exigency exists you should gather the requirement pertaining to those drill via experiences and doc it appropriately.
  • If the facts within the Framework manager is sensitive and will no longer subsist obtainable by course of all, recollect the requirements and document it for the Cognos progress group to assist them cozy the metadata accurately.
  • Developer point of view

    Developer refers to the Cognos progress group. Some elements to trust for query Studio implementation are highlighted here:

  • query Studio works with dimensionally as well as relationally modeled facts; do confident the package is built using the applicable style.
  • trap the scale, hierarchies, tiers, and measures per necessities, if the tackle is to subsist modeled dimensionally.
  • appropriate drill-through stories exist and own the necessary permissions for consumer entry.
  • be confident filters and filter values are install for effectual query execution when filtering on non-indexed or non-numeric columns.
  • ensure complete security necessities are applied in Framework supervisor in addition to IBM Cognos Connection, as required.
  • end-person standpoint

    end person refers to enterprise clients and traffic analysts who will subsist using question Studio to create their queries to explore and dissect statistics. some of the points you should definitely accept as sincere with are listed here:

  • Cognos Workspace superior is the rational better path for question Studio. if you are a brand novel Cognos user (are not poignant from IBM Cognos 8.x or prior versions), it's informed you utilize Cognos Workspace advanced for records exploration and querying to faucet into its rich capabilities.
  • if you're a legacy Cognos 8.x consumer now upgrading to IBM Cognos BI v10.x, Cognos Workspace superior is the rational upgrade route subsist confident to respect for growing novel reviews.
  • query Studio works with each relationally and dimensionally modeled facts. participate with the company Analyst or Cognos construction group your necessities for the diverse paths primary to your reports, the metrics/KPIs you exigency to computer screen, and the like, so they may likewise subsist made obtainable within the metadata package to meet your reporting wants. These necessities inform the metadata modeler how the statistics may still subsist structured within the tackle to address your facts exploration and reporting wants.
  • If the metadata has exquisite information and should no longer subsist obtainable via all, you must evidently communicate the safety should the company Analyst/IBM Cognos BI Administrator/Cognos progress team, as applicable for your corporation.
  • IBM Cognos BI Administrator viewpoint

    IBM Cognos BI administrators should toil along side the crew to subsist confident that the Cognos BI device can cater to those needs with the present Cognos BI installing. there are many cases when a altenative needs to subsist made between effortless to establish in force and straightforward to hold; that you may back the crew do the perquisite altenative according to the infrastructure, entertaining consumer condition, and tradition. one of the most aspects worth when you respect that follow:

  • be confident question Studio is obtainable to the entire clients who exigency access.
  • Is there any protection requirement for who can espy the metadata tackle required for querying and reporting in query Studio?
  • make confident programs that ought to subsist accessed through question Studio had been modeled with conclusion clients in intellect.

  • Cognos proclaims the supply of Cognos 8 company Intelligence records Modeler | killexams.com actual Questions and Pass4sure dumps

    Cognos, a issuer in company intelligence and corporate efficiency administration (CPM), recently introduced the customary availability of the Cognos 8 enterprise Intelligence facts Modeler for IBM Lotus Domino. agencies will now subsist capable of entry crucial company information determined in isolated silos of IBM Lotus Notes applications and databases. This extra extends the capabilities of Cognos 8 company Intelligence to access heterogeneous facts sources and supply the most complete view of corporate assistance for company intelligence reporting, analysis, scorecarding, dashboards, and suffer management.

    Cognos 8 traffic Intelligence facts Modeler integrates Lotus Notes databases and functions. Cognos 8 enterprise Intelligence gives you the comprehensive compass of company intelligence capabilities on a single, proven architecture.

    The Cognos eight company Intelligence statistics Modeler permits enterprise intelligence users to quite simply opt for Lotus Notes facts sources, tables, and columns, and label them with names which are significant to the company, with out making any changes to existing Lotus Notes purposes. The Cognos eight traffic Intelligence information Modeler optimizes the information for quick entry and creates a metadata mannequin for Cognos eight company Intelligence. This data is then as obtainable as any other traffic facts source and might subsist joined to other commercial enterprise data sources with out coding. The spot of toil Managed client integration makes it practicable for users to collaborate with a plenary knowing of traffic performance.

    This BeyeNETWORK word item consists of information from a fresh press unencumber by means of the company outlined.


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    data Warehouse ideas

    what is a learning Warehouse?

    A warehouse in unvarying terms is a repository where they store their advice. Coming to the records warehouse, it is a group of facts equipped in a selected system and categorized guidance.

    a learning warehouse retailers ancient records of a company that allows you to dissect their performance over the final years and scheme for the long run.

    The favorite definition of the facts warehouse via WH Inmon:

    an information warehouse is:

  • area oriented: information within the warehouse is categorized in diverse belt areas. as an instance, disagree with a KFC keep. It has many branches complete over the realm. If they ought to dissect “sales” for India, this is termed as “discipline”.
  • built-in: a data warehouse has records coming from assorted sources that are integrated into the warehouse. for example, accept as sincere with the identical KFC save, shops in India may shop date box as “dd/mm/yyyy” whereas the identical statistics in a further nation may subsist kept as “MM/DD/YYYY”. The information warehouse will own only 1 layout fastened to affirm “MM/DD/YYYY”.
  • Time-Variant: a learning warehouse shops historic statistics with which they can determine patterns of revenue over a time length of 3 months,6 months or 2 years of any firm which has a warehouse.
  • Non-volatile: data in the warehouse will no longer trade once it's entered.
  • a different definition from Ralph Kimball is extra exact:

    an information warehouse is a replica of transaction facts exceptionally structured for query and evaluation.

    what's a data mart?

    a learning mart is a subset of a learning warehouse. believe we've a firm established in many different places and every belt maintains a data warehouse which they cognomen it as records mart as a result of a warehouse could own the entire data built-in and as far as information mart is regarded it might subsist a fragment of the records warehouse.

    What are makes consume of of getting a data Warehouse?

    a learning Warehouse, in well-known, is used to dissect tendencies over a duration of time and enhances the determination making of an organization. once the information is loaded into the warehouse can subsist growing an OLAP dice or directly consume the facts to investigate trends. Basing on which the desirable flat administration will strategy their future enterprise innovations.

    information warehouse structure

    we are able to multiple sources there complete of the operational facts should subsist saved. Some might likewise sustain them in flat information and some in databases. they will own to read complete the sources and operate ETL (Extract, seriously change and load operations) which may subsist used to integrate records from these sources and seriously change them into one unique constitution and then load into their goal records warehouse.

    statistics Warehouse structure

    There are 2 tactics in designing your statistics warehouse. First one is “appropriate-Down strategy” and 2nd is “bottom-up strategy”.

    proper — Down method: The above vivid indicates the properly-down method, where they are reading data from dissimilar sources and transforming the data and loading into your warehouse, then on suitable of that they are creating their information marts.

    bottom-up method: The opposite of the above approach is that this. perquisite here they may subsist developing records marts first after which they are able to create their records ware condominium on exact of complete the facts marts.

    facts Warehouse terms

  • Dimension: A Dimension is a specific assistance which is kept in a data warehouse.
  • fact: fact is a measurable amount by which they will basically design out what the dimension does.
  • Attribute: Attributes are the points in a dimension  Ex: respect they now own product suggestions categorized in a dimension. The attributes of the “Product dimension” are: “Product_ID, Product_Name, Product_Color” and so on.  income is a veracity desk the spot you store numeric values associated with the dimension attributes.as an instance, they ought to cipher the number of earnings of every product for the current month.in this case, Product is the dimension and Month is a dimension and numbers of product offered is the fact.
  • OLAP: online Analytical Processing is a multidimensional model the consume of which users can view facts in distinctive dimensions at a separate glance.
  • kinds of OLAP’s:
  • Relational OLAP
  • Multi-dimensional OLAP
  • Hybrid OLAP
  • OLTP: online transactional processing is a transaction based mostly model the spot the main purpose might subsist to retrieve facts sooner and replace transactions perquisite now.
  • Schemas in Datawarehouse

    The schema is a rational association of tables in a learning warehouse. they own schemas in relational databases. Very tons dote equal information warehouse has schema’s particularly star schema, Snowflake schema, and reality-Constellation.

    famous person Schema

    in this rational association of tables, the reality desk can subsist at the core of the schema surrounded by several dimension tables. veracity and dimension tables are linked by course of a prime — foreign Key relationship.  reality table could subsist having international keys of complete the Dimension tables together with the records whereas a Dimension desk could subsist having attributes which characterize the Dimension.

    Snowflake Schema:

    in this rational association of tables, they own dimension tables linked to different dimension tables which in flip are linked to veracity desk by course of a first-rate-foreign key relationship.  Else they will articulate that the Dimension tables in Snowflake schema are normalized.  on account of the normalization, the statistics redundancy could subsist decreased and lots of cupboard space is saved.

    reality Constellation Schema:

    A fact constellation schema, not dote the start or snowflake, can own numerous veracity tables. it's likewise referred to as as Galaxy Schema.

    big cognomen Schema example

    in this schema shown, a fact table (earnings) is connected to dissimilar dimension tables merchandise, location, time and branch. each dimension desk has attributes describing the dimension and veracity table has the overseas key of complete dimension tables together with information dote dollars_sold and gadgets sold.

    Snowflake Schema example:

    during this schema, a reality desk (revenue) is related to diverse dimensions, whereas the dimensions item and placement are once again related to city and organisation dimension respectively.

    fact Constellation schema instance:

    during this schema, they can locate two veracity table income and transport connecting with each and every different and are once more linked to diverse dimension tables individually.

    Now we're jumping into the precise topic “Cognos company Intelligence”.

    average DWH architecture

    We may subsist coping with Cognos reporting device and Cognos Metadata managing device and different advantageous tools that Cognos BI has.

    Let’s drag through the spot BI will really near into photo

    The below photo shows basic statistics warehouse architecture. From facts load to the consume of the information loaded into the tables for reinforcing the traffic of your corporation. From the entire facts sources (may likewise it's Operational databases, Flat info and so forth.) they load the data into facts warehouse via different ETL system and creating cubes and using the facts for mining purpose.

    The beneath determine will characterize the traffic Intelligence drag how the facts will subsist used for company optimization. company intelligence is a manner from where you might subsist capable of derive how you can boost your enterprise with the facts that you've got. the usage of BI one might subsist able to dissect their statistics at distinctive stages and should subsist able to do selections to do their company more advantageous.

    Cognos BI might subsist used to generate studies (list, crosstab, and charts). The beneath determine will parade you the complete circulate that happens with Cognos.

    the 1st step in the consume of Cognos BI is to gather requirements. here's feasible when you tolerate in humor your traffic structure and the statistics that drives your enterprise. as soon as the requirement is finalized the subsequent step is to create your framework metadata mannequin. that you would subsist able to elect both to you superstar schema or snowflake schema otherwise you can consume the present relational model.

    After this step is completed with they should submit the model that they now own created. Publishing the mannequin will do your metadata mannequin obtainable for reporting intention. as soon as your mannequin is posted, they can consume the model to create different types of reports as per your requirement and they will time table the studies basing your requirement.

    distinctive types of Cognos

    Cognos ReportNet

    Cognos ReportNet (CRN) is an internet-based software product for creating and managing ad-hoc and customized-made experiences. ReportNet is developed with the aid of the Ottawa-based traffic Cognos (formerly Cognos incorporated), an IBM enterprise. The web-primarily based reporting appliance turned into launched in September 2003. due to the fact IBM’s acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet dote every other Cognos items.

    accessories:

  • Cognos file Studio — an internet-based product for creating complicated expert searching studies
  • Cognos query Studio — an internet-primarily based product for developing ad-hoc experiences.
  • Cognos Framework manager — A metadata modeling device to create BI metadata for reporting and dashboard applications.
  • Cognos Connection — the leading portal used to access experiences, schedule experiences and operate administrator actions.
  • Cognos eight.x

    IBM Cognos eight BI, at the start launched in September 2005, mixed the elements of a few aged items, including ReportNet, PowerPlay, Metrics manager. There are likewise categorical and extended types of Cognos 8 BI. plenary points:

    components:

  • record Studio (knowledgeable report authoring appliance formatted for the internet)
  • query Studio (advert hoc file authoring appliance with speedy information preview)
  • evaluation Studio (explore multi-dimensional dice information to reply company questions)
  • Metric Studio (display screen, analyze, and report on KPIs)
  • Metric dressmaker (outline, load, and retain metrics to subsist purchasable in Metric Studio)
  • event Studio (motion based brokers to notify determination makers as events ensue)
  • Framework manager (Semantic metadata layer appliance which creates fashions or programs)
  • PowerPlay Studio (formerly PowerPlay web)
  • Analytic functions (Packaged BI applications, built on an adaptable platform and extensible into traffic Analytics)
  • Cognos 10.x

    we will espy distinctive components and how they are fitting in. The accurate most layer, the spot they will espy Cognos Connection, Administrator, company insight and different studios. complete of them are internet-based and conclusion-user needs not to set up any client aspect application if he has the latest web browser establish in.

    The bottom layer is really data layer where you may additionally own homogeneous or heterogeneous database methods. data may subsist relational or multi-dimensional. On properly of it, they are able to espy three modeling tackle there — Framework supervisor, Transformer, and Metric designer. complete of them are customer based installation.

    We’ll retain the movement of add-ons from confiscate to backside as proven in beneath BI accessories determine.

    earlier than getting into the exact topics about the course you create the mannequin, install it and consume it to create reviews they should first understand the architecture of Cognos.

    Cognos architecture:

    Cognos traffic Intelligence framework is 3- tier architecture. the primary tier of the structure could subsist having the internet server which is answerable for the getting access to the user interfaces. The second tier will subsist having IBM Cognos BI Server which may subsist having gateways and dispatchers to route requests from different UI’s to Database and discourse returned to the server.

    The Third Tier could own the statistics sources. that you may own distinctive data sources and they're going to connect with the Cognos server the consume of JDBC or API’s.

    The beneath determine shows the architecture of Cognos BI:

    within the statistics tier, that you can espy one other factor known as the “content material save” which is a repository for the Cognos server. each time you retailer any objects stories, models every thing the records is saved in content material rescue database which once you reopen or reuse the latest kick created will fetch the statistics from the content save. complete this toil should subsist performed with the aid of the “content material supervisor”.

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

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

    internet-based mostly and windows based mostly components of Cognos

    Cognos BI has two forms of accessories,

    1. internet-primarily based accessories.

    2. Window based add-ons.

    web-primarily based components includes

  • Cognos Connection: here's the portal from where that you may access complete the net-primarily based components of IBM Cognos BI.
  • Cognos Administration: using this net-based UI that you could achieve administrative initiatives dote granting access, revoking entry, growing clients, corporations and defining roles etc.,
  • Cognos record Studio: the usage of report studio appliance they are able to create reviews and layout the stories. they can create numerous sorts of experiences dote checklist document, crosstab reports, graph’s and so on.,
  • Cognos query Studio: perquisite here they create advert-hoc experiences. advert-hoc studies are constructive when a consumer wants to espy the file without any prompts and fewer formatting. using query studio they can create a document straight.
  • Cognos Metric Studio: This studio is used to construct custom-made scorecards experiences to parade screen and dissect metrics.
  • Cognos evaluation studio: This studio is used to investigate records from diverse dimensions and likewise evaluate developments.
  • Cognos company perception: This appliance is used to build dashboards. A dashboard enables a user to without delay seem to subsist into the records and raise the altenative making.
  • Cognos enterprise perception advanced: With this tool, they can build more powerful dashboards and in addition to criterion reviews.
  • Window-primarily based accessories:

  • Cognos Framework manager: Cognos framework manager is a device used to create metadata models which they can consume in document studio or analysis studio.
  • Cognos Map manager: the consume of this appliance they can create maps as a course to permit you to create a novel location through the consume of the current areas.
  • http://www.abclearn.com/classes/cognos/cognos-tutorial/cognos-framework-manager


    BI0-122 Cognos 8 BI Administrator v2

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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
    brain dumps : 45 actual Questions

    Just read these Latest dumps and success is yours.
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    Mega-vendors dominate Gartner's 2010 BI, data warehouse Magic Quadrants | killexams.com actual questions and Pass4sure dumps

    Mega-vendors still dominate the traffic intelligence (BI) software market, but their stranglehold may subsist loosening as disgruntled customers open to espy for lower-priced, more supple 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 advocate and maintenance fees, according to Gartner's BI Magic Quadrant report, released final week.

    With a decrepit economy, customers are increasingly looking for cheaper, quicker-to-deploy options dote 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 traffic user impatience with enterprise BI systems and are delivering alternative easy-to-use-and-deploy architectures, alternative traffic models, and a tough customer focus -- so much so that in many cases traffic users continued to buy non-stack solutions even when a stack criterion 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, likewise released final week, smaller data marts and virtual data warehouses that consume federation technology are enjoying renewed popularity as companies espy to enlarge flexibility while keeping costs down.

    Higher performance requirements from customers are likewise pushing data warehouse vendors to better 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 -- likewise continue to gain in popularity thanks to their ease of implementation and support, he said.

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

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

    "I assume there are a few reasons why customers continue to buy into the stack despite an enlarge in dissatisfaction," Sallam said. "Stack-centric buying is largely IT driven, and stack vendors promise a one-stop shop. They often proffer deep discounts or bundle BI platform capabilities with other parts of the mega-vendor stack (e.g., applications or information infrastructure) and proffer the promise 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 compass of capabilities among the top vendors, including reporting, dashboarding and ad hoc query functionality. The vendor likewise offers three several 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 exigency only three administration staff per thousand users on average," the BI Magic Quadrant report states. dote Oracle, IBM has a number of data warehouse products to meet varying needs.

    Microsoft, meanwhile, continues to do 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 participate in 2010 when it debuts PowerPivot, an transcend add-on for BI and analytics, and SQL Server 2008 R2 Relational Database, which is likely to grasp the profile of an appliance.

    "The significance is that complete three … own the plenary 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 enact own an handicap 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 identical ranking -- Teradata was the pellucid leader in data warehousing. Gartner cited the vendor's products' capacity to ply mixed workloads without hindering performance, including near real-time data loading, tactical traffic analytics and an increasing number of ad hoc queries.

    "Teradata's solutions, which embrace 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 spot 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 still petite but increasing

    While still 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 subsist accelerated by organizations' increasing exigency 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 own the largest number of SaaS BI deployments, but smaller up-and-coming vendors dote Birst, GoodData, Oco and PivotLink are likewise getting attention, the report states.

    Cloud-based data warehousing, on the other hand, has yet to grasp off, for a number of reasons, according to Gartner. "The issues around the security, multi-tenancy and latency of consume 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 espy to the software to revolve their corporate data into competitive differentiators.


    MicroStrategy's (MSTR) CEO Michael Saylor on Q1 2018 Results - Earnings call Transcript | killexams.com actual questions and Pass4sure dumps

    No result found, try novel 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...

    Deploying a Windows Data Science Virtual Machine to Azure with PowerShell easily | killexams.com actual questions and Pass4sure dumps

    This weekend (10 December 2016), I went to Slovenia for a SQL Saturday. As always, it was an Amazing event well organised by Mladen Prajdic, Dejan Sarka, and Matija Lah in a fabulous setting amongst fabulous scenery. I highly recommend it and, also, Ljubljana  is a wonderful spot to subsist in December with complete the lights and markets.

    WP_20161209_19_21_06_Pro.jpg

    Whilst I was there I was asked by someone if you could deploy data science virtual machines in Azure with PowerShell. I said I was confident that it could subsist done and agreed I would write a blog post, so here it is.

    According to the Azure documentation

    The Data Science Virtual Machine running on a Windows Server 2012 contains favorite tools for data exploration, modeling and progress activities. The main tools embrace Microsoft R Server Developer Edition (An enterprise ready scalable R framework) , Anaconda Python distribution, Jupyter notebooks for Python and R, Visual Studio Community Edition with Python, R and node.js tools, Power BI desktop, SQL Server 2016 Developer edition including advocate In-Database analytics using Microsoft R Server. It likewise includes open source deep learning tools dote Microsoft Cognitive Toolkit (CNTK 2.0) and mxnet; ML algorithms dote xgboost, Vowpal Wabbit. The Azure SDK and libraries on the VM allows you to build your applications using various services in the cloud that are fragment of the Cortana Analytics Suite which includes Azure Machine Learning, Azure data factory, Stream Analytics and SQL Datawarehouse, Hadoop, Data Lake, Spark and more.

    I own created a duty to wrap around the process to do it easier for not a bit PowerShell  people to enact this. There are a train of steps to succeed below and you should subsist able to create a machine in about 10 minutes once you own completed the pre-requisites.

    Enable Programmatically Deployment

    First, an annoyance. To subsist able to deploy Data Science virtual machines in Azure programmatically  you first own to login to the portal and click some buttons.

    In the Portal click novel and then marketplace and then search for data science. elect the Windows Data Science Machine and under the blue Create button you will espy a link which says “Want to deploy programmatically? find started” Clicking this will lead to the following blade.

    set-up-programmatically

    Click Enable and then rescue and you then drag to PowerShell ??

    Azure PowerShell Cmdlets

    Follow the instructions here to install the Azure PowerShell modules. In the examples you espy here I am using Windows 10 and PowerShell version 5.1.14393.479 and I installed the Azure modules using the Install-Module method

    Get the script

    To install a data science VM, we’ll consume the New-WindowsDataScienceVM.ps1 script. In this script, I’m using version 1.2, but any version of this script published in PowerShell Gallery is fine.

    To install the New-WindowsDataScienceVM script from the PowerShell gallery, type:

    Install-Script New-WindowsDataScienceVM

    For  more information about using the PowerShellGet cmdlets to install scripts and modules from PowerShell Gallery, read this page. The PowerShellGet modules is included in PowerShell 5.0 and later on Windows 10, but you can install PowerShellGet for PowerShell 3.0 and 4.0. If you cannot connect to the gallery or prefer not to install the module, you can likewise find the script on GitHub.

    Login to Azure

    You can login to Azure using the command

    Login-AzureRMAccount

    which will pop-up a prompt for you to log into Azure

    login

    Enable Simple Mode

    The New-WindowsDataScienceVM duty comes with a Simple switch parameter.

    If you consume -Simple, the duty prompts you only for the admin username and password for the virtual machine. It creates a randomly-named, standard_DS1_v2-sized machine in the ukwest data centre with standard, locally redundant storage in a randomly named Resource Group. complete of the required objects own random names, too. If that is not what you want, there is more information at the finish of this post. I am considering offering a pop-up to elect location in Simple Mode. Let me know here if that would subsist something you would like

    To create a simple data science VM, run:

    New-WindowsDataScienceVM -Simple Enter Local Admin Password

    When you Run the function, it prompts for a local admin username and password to log into the virtual machine. The password must own 3 of the following 1 Upper case, 1 lower case, I special character and 1 number. Don’t lose it, you will exigency it.

    Local Admin.PNG

    Grab a cuppa, creating your VM and its resources will grasp 5 – 10 minutes. (In my testing it reliably took between 7 and 8 minutes)  The screen will espy dote this

    deploying.PNG

    When the script has finished running you will own deployed a set of resources dote this

    portal

    Login to the Virtual Machine

    Copy and paste the correct code from the output at the finish of the script to launch the RDP session and rescue the RDP file to your documents folder for later use.

    Or you can find the Virtual machine cognomen in the portal or by running

    Get-AzureRmVM -ResourceGroupName <ResourceGroup> | Where-Object {$_.Name -like 'DSVM*'}

    You can then consume the code below to download a RDP file and log into the virtual machine using this code

    Get-AzureRmRemoteDesktopFile -ResourceGroupName <ResourceGroup> -Name <VMName> -LocalPath C:\WIP\DataScienceVM.rdp -Launch

    rdp file.PNG

    You will exigency to login with the local admin account you set up previously, which means that you will exigency to click on more choices and then the machinename\Username. In this case the machine cognomen is DSVMZIAgd

    You can copy the amend Virtual Machine cognomen and Username from the output at the finish of the script.

    login screen.PNG

    If you own forgotten your password, you can reset it in the Portal.

    Enjoy the Data Science Virtual Machine

    You are then logged in and can carry on. Once the Azure PowerShell modules and script are installed you would subsist able to own a machine up and running within 10 minutes.

    vm-desktop

    Cleaning Up

    To remove the resource group and complete resources in the resource group, including the data science VM, run:

    Remove-AzureRmResourceGroup -Name <ResourceGroup> -Force

    This will remove complete resources in that resource group, so subsist observant if you own deployed anything else.

    Customising the Deployment

    If you want to consume different settings for the deployment or want to script the creation of a number of machines, you can run

    Get-Help New-WindowsDataScienceVM -Full

    and espy complete the options and further examples. Any questions delight feel free to comment



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    P&C [2 Certification Exam(s) ]
    Palo-Alto [4 Certification Exam(s) ]
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    See-Beyond [1 Certification Exam(s) ]
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    SpringSource [1 Certification Exam(s) ]
    SUN [63 Certification Exam(s) ]
    SUSE [1 Certification Exam(s) ]
    Sybase [17 Certification Exam(s) ]
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    TIA [3 Certification Exam(s) ]
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    Trainers [3 Certification Exam(s) ]
    Trend [1 Certification Exam(s) ]
    TruSecure [1 Certification Exam(s) ]
    USMLE [1 Certification Exam(s) ]
    VCE [6 Certification Exam(s) ]
    Veeam [2 Certification Exam(s) ]
    Veritas [33 Certification Exam(s) ]
    Vmware [58 Certification Exam(s) ]
    Wonderlic [2 Certification Exam(s) ]
    Worldatwork [2 Certification Exam(s) ]
    XML-Master [3 Certification Exam(s) ]
    Zend [6 Certification Exam(s) ]





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