1. Definition
business analytics (BA)
This was last updated in August 2010
Editorial Director: Margaret Rouse
http://searchbusinessanalytics.techtarget.com/definition/business-ana
報告人 陳衍華
2012.07.04
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2. BA
• BA is used to gain insights that inform business
decisions and can be used to automate and
optimize business processes.
• Data-driven companies treat their data as a
corporate asset and leverage it for competitive
advantage.
• Successful business analytics depends on
data quality, skilled analysts who understand the
technologies and the business and an
organizational commitment to data-driven
decision making
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3. BA (Cont.)
• Exploring data to find new patterns and
relationships (data mining)
• Explaining why a certain result occurred
(statistical analysis, quantitative analysis)
• Experimenting to test previous decisions
(A/B testing, multivariate testing)
• Forecasting future results (
predictive modeling, predictive analytics)
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4. BA (Cont.)
• Once the business goal of the analysis is
determined, an analysis methodology is
selected and data is acquired to support
the analysis
• Analytic tools range from spreadsheets
with statistical functions to complex data
mining and predictive modeling
applications
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5. BI vs BA Business Intelligence Business Analytics
What happened? Why did it happen?
Answers the When? Will it happen again?
questions: Who? What will happen if we
change x?
How many? What else does the
data tell us that
never thought to
ask?
Reporting (KPIs, Statistical/Quantitative
Includes: metrics) Analysis
Automated Data Mining
Monitoring/Alerting
(thresholds) Predictive Modeling
Dashboards
Scorecards Multivariate Testing
OLAP (Cubes, Slice &
Dice, Drilling) 5
Ad hoc query

6. In-Memory Analysis
Delivering Insights
at the Speed of Thought
BY WAYNE ECKERSON
Director of Research, Business Applications and
Architecture Group, TechTarget, December 2011
報告人 陳衍華
2012.07.04
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7. THE PURPOSE OF THIS REPORT
• profile the capabilities of next-
generation business intelligence (BI) tools
with emphasis on new visual analysis
tools
• and in-memory processing.
• interviews with BI practitioners and
briefings with sponsors of this report.
• also based on a survey of 240 BI
professionals
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8. BI framework 2020
Casual
Power & Casual User – 80%
user
Power User- 20%
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9. • Continuous intelligence
– Accelerates the delivery of information to users, and in some
cases, correlates events and triggers alerts when it’s time for
humans to intervene
• Analytics intelligence
– gives power users a variety of desktop analysis tools to explore
and analyze data in an unfettered fashion so they can answer
unanticipated questions.
• content intelligence
– both casual and power users can access and analyze
to include semi-structured and unstructured data.
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10. Reporting vs. Analysis
• At the highest level, the two primary BI
applications—reporting and analysis—are
fundamentally different applications with
very different types users and unique
workloads, design frameworks and
architectures.
• Top down and Bottom up
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11. Reporting Versus Analysis: Distinct Workloads, Users and Architectures
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12. Top down
• Reporting
– monitors business activity using metrics that are aligned with
strategic goals and objectives
• To design reports and dashboards—visual exception
reports
– need to know in advance the questions casual users are going
to ask
– will differ depending on their roles in the organization.
• To create reports
– the typical organization first builds a data warehouse or data
mart that contains a model of how
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13. Bottom up
• analysis is a “bottom-up” activity in which
analytical experts use a variety of tools
• power users often need to access a variety of
data sources, explore and merge the data
• analyze the results and present their findings in
a concise and comprehensive way to business
executives and managers.
• answering unanticipated business questions
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14. Misplaced expectations
• .The challenges that most organizations
experience with BI tools
– often have less to do with vendor products
than with customer expectations about the
products.
• Recognize that you need both top-down
• and bottom-up BI tools and that these
tools need to work together, not against
each other.
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15. Next-Generation BI Capabilities
• Top-down capabilities
• Bottom-up capabilities
• Self-service
• END-USER CHARACTERISTICS
– enable users to change what they see on the screen without IT
or power-user involvement
– Interactive , Visual, Flexible, Analytical, Predictive, Collaborative,
Mobile
• IT CHARACTERISTICS
– Fast, Deploys quickly, Any data source, Scalable, Reusable,
Maintainable, Manageable, Comprehensive, Portable
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16. Top-Down and Bottom-Up Approaches to Self-Service BI
Self-service BI promises to provide business users with easy-to-use tools that enable them
to get the information they want, when and how they want it without IT or power-user
intervention.
Functionality on
Demand
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17. Mapping Types of Users to Self-Service
Hierarchies
Both casual users
and power users both
consume and produce
reports and analyses,
but power users exploit
more advanced
features.
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18. In-Memory Databases vs. Intelligent Caches
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19. In-Memory Databases vs. Intelligent Caches (cont.)
• Intelligent caches speed response times for pre-run
queries
– still giving users access to data stored in remote databases (of
any size).
• In-memory databases speed response times for all
queries running against a downloaded data set
– but don’t provide direct access to remote data.
• Some tools use a hybrid approach users can choose to
query remote data or download data to a local server or
desktop to improve query performance.
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20. 報告完畢
敬請指教
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