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Top 10 trends in BusinessIntelligence for 2010R .K .M A N O J J
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SYNOPSISIntroduction
1. Increased data and business intelligence program governance
2. Enterprise-wide data integration: A good investment
3. The promise of semantic technologies
4. Expanding use of advanced analytics
5. Narrowing the gap between operational systems and the data warehouse
6. Data warehousing and business intelligence: A new generation drives new priorities
7. Growing impact and opportunity of Complex Event Processing
8. Growing importance of integrating and analyzing unstructured/semi-structured data
9. Social computing and the next frontier for business intelligence
10. Growing interest in cloud computing for business intelligence
Conclusion
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INCREASEDDATAAND BUSINESS INTELLIGENCEPROGRAM
GOVERNANCE
BI is becoming more pervasive
Inter organizational collaboration and Cross departmental
integration
Top initiavives: Data quality, Advanced analytics, Data governance and MDM
Intent to invest within 12 months
Formal governance 53 percent MDM 52 percent BI competency center 45 percent Standard taxonomy 40 percent
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ENTERPRISE-WIDEDATA INTEGRATION:A GOOD
INVES
TMEN
T For many years, data warehouse and BI
environments were built one application, onereport, one data mart at a time.
Their efforts demonstrate the cost savings of acomprehensive data integration approach replacingmultiple isolated redundant projects.
BlueCross BlueShield (BCBS) of Kansas City
Benefiting 4,0005,000 offices.
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THEPROMISEOFSEMANTIC TECHNOLOGIES
Semantic Web3, which isan extension of the Web,information is given a
well-defined meaning sothat computers can relateinformation in ameaningful way andinterpret and act on itappropriately
Commercial application ofthis technology is
becoming more
widespread. Semantic
technologies are beingused today to:
Automate product
reclassification.Enable accurate and
consistent diagnosis andTreatment across a
hospital managementcommunity.Perform dependency
analysis for managing andreconfiguring software
assets.
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NARROWING THE GAP BETWEENOPERATIONALSYSTEMS
ANDDA
TAWARE
HO
USE
Traditional data warehouses often do not provideup-to-the-minute data or results of analysis that istimely enough for making operational decisions
Where activie data ware housing has beenattempted and the results are brittle and resistantto change due to labour intensive
The EDW will evolve to be more virtualized,
distributed and real time, transparentlyprovisioning data from diverse formats and servingapplications with in-database and in-streamanalysis and execution.
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Growing interest in cloud computingfor business intelligence
Cloud computing customers do not own the physicalinfrastructure, instead avoiding capital expenditure
by renting usage from a third-party provider.
They consume resources as a service and pay onlyfor resources that they use.
As BI solutions increase in complexity,organizations find it more difficult and expensive tofind and keep skilled in-house personnel.
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To manage cost and complexity, organizationshave begun to run IT like a services business
The promise of cloud computing, either privateor public, is shared resources, standardtechnology, and automated provisioning
processes. For both in-house IT shops andoutsourced service providers, this candramatically reduce operating costs and offernew capabilities
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EXPANDING USEOFADVANCEDANALYTICS
Advanced analytics is the critical enabler in turningdata into insight.
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Data warehousing and business intelligence:A newgeneration drives new priorities
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Data warehousing and business intelligence:A newgeneration drives new priorities
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Growing impact and opportunity of Complex EventProcessing
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Growing importance of integrating and analyzingunstructured/semi-structured data
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Soci
al computing
and the next frontier for businessintelligence
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Soci
al computing
and the next frontier for businessintelligence