BUSINESS ANALYTICS

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Chapter 6
Pages 256-272 289-292 Also pages 3-15 of the
e-Book

• BUSINESS ANALYTICS
• AND DATA VISUALIZATION

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Business Analytics

• Analytics
• The science of analysis
• Business Analytics (BA)
• The application of models to analyze business
  data. BA involves using DSS tools, especially
  models, in assisting decision makers essentially
  a form of OLAP decision support

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This is a nice overview slide for BA. Many of
these topics are actually covered over multiple
chapters.
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Online Analytical Processing (OLAP)

• An information system that enables the user,
  while at a PC, to query the system, conduct an
  analysis, and so on.
• Drill-down
• The investigation of information in detail
  (e.g., finding not only total sales but also
  sales by region, by product, or by salesperson).

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OLAP versus OLTP

• OLTP concentrates on processing repetitive
  transactions in large quantities and conducting
  simple manipulations
• OLAP involves examining many data items complex
  relationships
• OLAP may analyze relationships and look for
  patterns, trends, and exceptions

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Types of OLAP

• Multidimensional OLAP (MOLAP)
• OLAP implemented via a specialized
  multidimensional database (or data store) that
  summarizes transactions into multidimensional
  views ahead of time
• Relational OLAP (ROLAP)
• The implementation of an OLAP database on top of
  an existing relational database

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Reports and Queries

• Ad hoc query
• A query that cannot be determined prior to the
  moment the query is issued
• Structured Query Language (SQL)
• A data definition and management language for
  relational databases. SQL front ends most
  relational DBMS

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Measures

• A summarizable numerical value that you use to
  monitor how well the business doing.
• eg. How many units of the product were sold?
• What is total sales revenue?
• How many defective products were made?
• How many people responded to an ad?
• One may use different aggregation techniques when
  presenting the values of measures
• eg. Sum, Average, Max, Min

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Dimensions

• The different characteristics by which the
  measure values may be presented to the
  decision-maker
• Eg. No. of units sold may be presented by region,
  by product, by salesperson, and by time (four
  dimensions)

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Cube

• A measure and its associated dimensions
• Eg. The cube below shows the number of units
  sold measure along the product, region and
  calendar year dimensions

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Web Analytics

• The application of business analytics activities
  to Web-based processes, typically e-commerce
• Clickstream data
• Data that provide a trail of the users
  activities and show the users browsing patterns
  (e.g., which sites are visited, which pages, how
  long)
• Clickstream analysis
• The analysis of the above data
• Highly useful in designing Web sites helps to
  keep customer on the site, to make purchases, and
  revisit the site later

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Advanced BA

• Data mining and predictive analysis
• Data mining
• Predictive analysis
• Use of tools that help determine the probable
  future outcome for an event or the likelihood of
  a situation occurring. These tools also identify
  relationships and patterns
• This topic will be further developed in Chapter
  7