Ch 6: Business Intelligence and Analytics
Business analytics - ANS-extensive use of data/quantitative analysis to *support
fact-based decision making within organizations*
Business analytics can be used to: - ANS-- Gain a better understanding of current
business performance
- Explain results
- Optimize current operations
- Forecast future business results
- Reveal new business patterns/relationships
Business intelligence (BI) - ANS-Includes a *wide range of applications, practices, and
technologies for the extraction/transformation/integration/visualization/analysis
interpretation/presentation of data TO SUPPORT IMPROVED DECISION MAKING*
Data used in BI is often: - ANS-*pulled from multiple sources* and may come from
sources (internal and external) to the organization
Data can be used to build: - ANS-large collections of data = *data warehouses, data
marts, and data lakes*
*BI & analytics* are used to achieve a number of benefits: - ANS-- Detect fraud
- Improve forecasting
- Increase sales
- Optimize operations
- Reduce costs
Data scientists are individuals who combine: - ANS-- *Strong business acumen*
- A deep *understanding of analytics*
- A healthy *appreciation of the limitations of their data/tools/techniques to deliver real
improvements*
Data scientists - ANS-- *View a situation from many angles*
- Determine *what data/tools can help further an understanding of the situation*
- Often *work in a team setting* with business managers and specialists - Are
highly *inquisitive*
*Educational requirements for being a data scientist* are quite rigorous: - ANS--
, Requires a *mastery of STATISTICS, MATH, and COMPUTER PROGRAMMING*
- Positions *may require an advanced degree*
Many schools offer *career-focused courses, degrees, certificates in analytical-related
disciplines* such as: - ANS-- Database management
- Predictive analytics
- BI (Business intelligence)
- Big data analysis
- Data mining
Job outlook for data scientists is extremely bright - ANS-TRUE
Components Required for *Effective BI and Analytics*: - ANS-- Existence of a *solid
data management program*, *including *data governance*
- *Creative data scientists*
- *Management team: must have a STRONG COMMITMENT to data-driven decision
making* (MOST VITAL)
Data *governance* - ANS-*defines the roles, responsibilities, and processes* for
ensuring that data can be trusted/ used by the entire organization
Business Intelligence and Analytics Tools - ANS-- Spreadsheets
- Reporting/querying tools
- Data visualization tools
- Online analytical processing (OLAP)
- Drill-down analysis
- Linear regression
- Data Mining
- Dashboards
Business managers often import data into a spreadsheet program - ANS-TRUE
*spreadsheets be used to perform operations on the data based on formulas created by
the end user*
*spreadsheets are also used to create reports/graphs based on that data*
Excel *Scenario* Manager: - ANS-Used to perform "what-if" analysis to evaluate various
alternatives
Business analytics - ANS-extensive use of data/quantitative analysis to *support
fact-based decision making within organizations*
Business analytics can be used to: - ANS-- Gain a better understanding of current
business performance
- Explain results
- Optimize current operations
- Forecast future business results
- Reveal new business patterns/relationships
Business intelligence (BI) - ANS-Includes a *wide range of applications, practices, and
technologies for the extraction/transformation/integration/visualization/analysis
interpretation/presentation of data TO SUPPORT IMPROVED DECISION MAKING*
Data used in BI is often: - ANS-*pulled from multiple sources* and may come from
sources (internal and external) to the organization
Data can be used to build: - ANS-large collections of data = *data warehouses, data
marts, and data lakes*
*BI & analytics* are used to achieve a number of benefits: - ANS-- Detect fraud
- Improve forecasting
- Increase sales
- Optimize operations
- Reduce costs
Data scientists are individuals who combine: - ANS-- *Strong business acumen*
- A deep *understanding of analytics*
- A healthy *appreciation of the limitations of their data/tools/techniques to deliver real
improvements*
Data scientists - ANS-- *View a situation from many angles*
- Determine *what data/tools can help further an understanding of the situation*
- Often *work in a team setting* with business managers and specialists - Are
highly *inquisitive*
*Educational requirements for being a data scientist* are quite rigorous: - ANS--
, Requires a *mastery of STATISTICS, MATH, and COMPUTER PROGRAMMING*
- Positions *may require an advanced degree*
Many schools offer *career-focused courses, degrees, certificates in analytical-related
disciplines* such as: - ANS-- Database management
- Predictive analytics
- BI (Business intelligence)
- Big data analysis
- Data mining
Job outlook for data scientists is extremely bright - ANS-TRUE
Components Required for *Effective BI and Analytics*: - ANS-- Existence of a *solid
data management program*, *including *data governance*
- *Creative data scientists*
- *Management team: must have a STRONG COMMITMENT to data-driven decision
making* (MOST VITAL)
Data *governance* - ANS-*defines the roles, responsibilities, and processes* for
ensuring that data can be trusted/ used by the entire organization
Business Intelligence and Analytics Tools - ANS-- Spreadsheets
- Reporting/querying tools
- Data visualization tools
- Online analytical processing (OLAP)
- Drill-down analysis
- Linear regression
- Data Mining
- Dashboards
Business managers often import data into a spreadsheet program - ANS-TRUE
*spreadsheets be used to perform operations on the data based on formulas created by
the end user*
*spreadsheets are also used to create reports/graphs based on that data*
Excel *Scenario* Manager: - ANS-Used to perform "what-if" analysis to evaluate various
alternatives
