BUSINESS DRIVEN TECHNOLOGY

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BUSINESS DRIVEN TECHNOLOGY Chapter Eight
Viewing and Protecting Organizational Information
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LEARNING OUTCOMES

• 8.1 Describe the roles and purposes of data
  warehouses and data marts in an organization
• 8.2 Compare and contrast the multidimensional
  nature of data warehouses (and data marts) with
  the two-dimensional nature of databases
• 8.3 Summarize the importance of ensuring the
  cleanliness of information throughout an
  organization

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LEARNING OUTCOMES

• 8.4 Define the relationship between backup and
  recovery
• 8.5 Illustrate the five characteristics of
  adaptable systems

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CHAPTER EIGHT OVERVIEW

• This chapter takes a step beyond databases and
  discusses data warehouses and data mining
• It also discusses the importance of building
  systems that operate efficiently and effectively

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DATA WAREHOUSE FUNDAMENTALS

• Data warehouse a logical collection of
  information gathered from many different
  operational databases that supports business
  analysis activities and decision-making tasks
• The primary purpose of a data warehouse is to
  aggregate information throughout an organization
  into a single repository for decision-making
  purposes

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DATA WAREHOUSE FUNDAMENTALS

• Extraction, transformation, and loading (ETL) a
  process that extracts information from internal
  and external databases, transforms the
  information using a common set of enterprise
  definitions, and loads the information into a
  data warehouse
• Data mart contains a subset of data warehouse
  information

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DATA WAREHOUSE FUNDAMENTALS
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DATA WAREHOUSE FUNDAMENTALS

• Data Warehouse Model

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MULTIDIMENSIONAL ANALYSIS AND DATA MINING

• Databases contain information in a series of
  two-dimensional tables
• In a data warehouse and data mart, information is
  multidimensional, it contains layers of columns
  and rows
• Dimension a particular attribute of information

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MULTIDIMENSIONAL ANALYSIS AND DATA MINING

• Cube common term for the representation of
  multidimensional information

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MULTIDIMENSIONAL ANALYSIS AND DATA MINING

• Data mining the process of analyzing data to
  extract information not offered by the raw data
  alone
• To perform data mining users need data-mining
  tools
• Data-mining tools use a variety of techniques
  to find patterns and relationships in large
  volumes of information and infer rules from them
  that predict future behavior and guide decision
  making
• Include query tools, reporting tools,
  multidimensional analysis tools, statistical
  tools, and intelligent agents

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MULTIDIMENSIONAL ANALYSIS AND DATA MINING
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INFORMATION CLEANSING OR SCRUBBING

• An organization must maintain high-quality data
  in the data warehouse
• Information cleansing and scrubbing a process
  that weeds out and fixes or discards
  inconsistent, incorrect, or incomplete
  information

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KEEPING BUSINESS OPERATIONS RUNNING SMOOTHLY

• Organizations must protect themselves from system
  failures and crashes
• Three primary steps an organization can take to
  protect its systems
• Develop an appropriate backup and recovery
  strategy
• Create a disaster recovery plan
• Build adaptable business systems

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BACKUP AND RECOVERY STRATEGY

• Backup an exact copy of a systems information
• Recovery the ability to get a system up and
  running in the event of a system crash or failure
  and includes restoring the information backup

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DISASTER RECOVERY PLAN

• Disaster recovery plan a detailed process for
  recovering information or an IT system in the
  event of a catastrophic disaster
• Hot site a separate and fully equipped facility
  where the company can move immediately after a
  disaster and resume business
• Cold site a separate facility that does not
  have any computer equipment, but is a place where
  employees can move after the disaster

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DISASTER RECOVERY PLAN

• Disaster recovery cost curve charts
• The cost to the organization of the
  unavailability of information and technology
• The cost to the organization of recovering from a
  disaster over time

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BUILDING ADAPTABLE SYSTEMS

• Five characteristics of adaptable systems
• Flexibility systems must meet all types of
  business changes
• Scalability refers to how well a system can
  adapt to increased demands
• Reliability ensures all systems are functioning
  correctly and providing accurate information
• Availability addresses when systems can be
  accessed by employees, customers, and partners
• Performance measures how quickly a system
  performs a certain process or transaction in
  terms of efficiency IT metrics of both speed and
  throughput

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OPENING CASE STUDY QUESTIONSSearching for
Revenue - Google

• Determine how Google could use a data warehouse
  to improve its business operations
• Explain why Google would need to scrub and
  cleanse the information in its data warehouse
• Identify a data mart that Googles marketing and
  sales department might use to track and analyze
  its AdWords revenue

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OPENING CASE STUDY QUESTIONSSearching for
Revenue - Google

• Describe the fundamentals of a disaster recovery
  plan along with a recommendation for a plan for
  Google
• Describe why availability and scalability are
  critical to Googles business operations

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CHAPTER EIGHT CASEConnecting Austria

• Almost 6 million of the 8 million people in
  Austria have mobile phones, of which T-Mobile
  Austria serves approximately 36
• T-Mobile wants to build stronger relationships
  with its current customers and move away from its
  initial strategy of using a low-priced
  introductory rate plan to attract new customers

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CHAPTER EIGHT CASE QUESTIONS

• Explain how T-Mobile Austria is using information
  from its data warehouse to remain successful and
  competitive in a saturated market
• Identify why information cleansing and scrubbing
  is critical to T-Mobile Austrias data warehouse
  success
• Assess the potential impacts on T-Mobile
  Austrias business if it failed to create a
  disaster recovery plan
• Review the five characteristics of adaptable
  system and rank them in order of importance to
  T-Mobile Austrias business

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BUSINESS DRIVEN TECHNOLOGY UNIT TWO CLOSING
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Unit Closing Case One Harrahs Gambling Big
on Technology

• Identify the effects low-quality information
  might have on Harrahs service-oriented business
  strategy
• Summarize how Harrahs uses database technologies
  to implement its service-oriented strategy
• Harrahs was one of the first casino companies to
  find value in offering rewards to customers who
  visit multiple Harrahs locations. Describe the
  effects on the company if it did not build any
  integrations among the databases located at each
  of its casinos.

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Unit Closing Case One Harrahs Gambling Big
on Technology

• Estimate the potential impact to Harrahs
  business if there is a security breach in its
  customer information
• Explain the business ramifications if Harrahs
  fails to implement a backup policy
• Identify three different types of data marts
  Harrahs might want to build to help it analyze
  its operational performance
• Predict what might occur if Harrahs fails to
  clean or scrub its information prior to loading
  it into its data warehouse

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Unit Closing Case Two Evaluating Swiss Armys
Success

• Why is accurate and reliable data considered a
  system benefit for Swiss Army?
• How would unintegrated information affect Swiss
  Armys ability to operate its business?
• What types of data marts might Swiss Army choose
  to gain business intelligence?

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Unit Closing Case Two Evaluating Swiss Armys
Success

• Explain the disaster recovery cost curve and the
  optimal place for Swiss Army to operate on it
• Assess the importance of backup and recovery
  strategies for Swiss Army