Business Intelligence

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Business Intelligence

• Center of Excellence for IT at Bellevue College

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What is Business Intelligence (BI)?

• IT-enabled business decision making based on
  simple to complex data analysis processes
• Database development and administration
• Data mining
• Data queries and report writing
• Data analytics and simulations
• Benchmarking of business performance
• Dashboards
• Decision support systems

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Why BI?

• Make more informed business decisions
• Competitive and location analysis
• Customer behavior analysis
• Targeted marketing and sales strategies
• Business scenarios and forecasting
• Business service management
• Business planning and operation optimization
• Financial management and compliance

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Gartner Reveals Five Business Intelligence
Predictions for 2009 and Beyond

• Through 2012, more than 35 of the top 5,000
  global companies will regularly fail to make
  insightful decisions about significant changes in
  their business and markets
• By 2012, business units will control at least 40
  of the total budget for BI
• By 2010, 20 of organizations will have an
  industry-specific analytic application delivered
  via software as a service (SaaS) as a standard
  component of their BI portfolio
• In 2009, collaborative decision making will
  emerge as a new product category that combines
  social software with BI Platform capabilities
• By 2012, one-third of analytic applications
  applied to business processes will be delivered
  through coarse-grained application mashups
• Gartner Research, Jan 2009, http//www.gartner.com
  /it/page.jsp?id856714

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Technologies Supporting BI

• Database systems and database integration
• Data warehousing, data stores and data marts
• Enterprise resource planning (ERP) systems
• Query and report writing technologies
• Data mining and analytics tools
• Decision support systems
• Customer relation management software
• Product lifecycle and supply chain management
  systems

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Moving the Control of BI into the Hands of the
Users BI 2.0

• Leveraging new Web 2.0 technologies to
• Enhance the presentation layer and data
  visualization
• Provide information on-demand and greater
  customization
• Increase ability to create corporate and public
  data mashups
• Allow interactive user-directed analysis and
  report writing

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Examples of BI Careers

• BI careers cross over all industries
• BI solution architects and integration
  specialists
• Business and BI analysts
• BI application developers and testers
• Data warehouse specialists
• Database analysts, developers and testers
• Database support specialists

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BI Skill and Knowledge Clusters

• Database theory and practice
• Data mining and relational report writing
• Enterprise data and information flow
• Information management and regulatory compliance
• Analytical processing and decision making
• Data presentation and visualization
• BI technologies and systems
• Value chain and customer service management
• Business process analysis and design
• Transaction processing systems
• Management information systems

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Critical Technology Knowledge and Skills

• Knowledge of database systems and data
  warehousing technologies
• Ability to manage database system integration,
  implementation and testing
• Ability to manage relational databases and create
  complex reports
• Knowledge and ability to implement data and
  information policies, security requirements, and
  state and federal regulations

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Critical Business and Customer Skills and
Knowledge

• Understanding of the flow of information
  throughout the organization
• Ability to effectively communicate with and get
  support from technology and business specialists
• Ability to understand the use of data and
  information in each organizational units
• Ability to present data in a user-centric
  framework
• Ability to understand the decision making process
  and to focus on business objectives
• Ability to train business users in information
  management and interpretation

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Multidimensional Analysis

• For rapid analysis and display of large amounts
  of data
• On-Line Analytical Processing (OLAP)
• Multidimensional/ hyper cubes
• OLAP operations Slice, Dice, Drill Down/Up,
  Roll-up, Pivot
• OLAP vendors and products

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Data Warehousing

• Basics of data warehousing design and management
• Data warehouse architectures
• Data marts and data stores
• Data structures and data flow
• Dimensional modeling
• Extract, clean, conform and deliver
• Server management tools to package, backup and
  restore
• Database server activity monitoring and
  performance optimization

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Data Mining

• Data mining the extraction of predictive
  information from large databases.
• Data trend, connection and behavior pattern
  analysis
• Data quality
• Data mining tools
• Predictive and business analytics
• Descriptive and decision models
• Statistical techniques and algorithms

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Data Visualization

• Data representations
• Information graphics
• Data representation techniques and tools
• Visual representation trends and best practices
• Interactivity in data representation
• Tools and applications
• The user perspective on information presentation
• http//www.smashingmagazine.com/2007/08/02/data-vi
  sualization-modern-approaches/

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Working with Business and User Requirements

• Capturing and documenting the business
  requirements for BI solution
• Translating business requirements into technical
  requirements
• BI project lifecycle and management
• Key Performance Indicators (KPIs), actions, and
  stored procedures
• User education and training
• Data-based decision making
• Effective communication and consultation with
  business users

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Sample Role Business Intelligence (BI)
Specialist

• Business Intelligence (BI) Specialist works with
  business users to obtain data requirements for
  new analytic applications, design conceptual and
  logical models for the data warehouse and/or data
  mart and communicate physical designs to the
  database group. The BI specialist also develops
  processes for capturing and maintaining metadata
  from all data warehousing components.

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Sample Role Business Intelligence Developer

• Business Intelligence Developer is responsible
  for designing and developing Business
  Intelligence solutions for the enterprise. The
  Developer works on-site at the corporate head
  quarters. Key functions include designing,
  developing, testing, debugging, and documenting
  extract, transform, load (ETL) data processes and
  data analysis reporting for enterprise-wide data
  warehouse implementations. Responsibilities
  include working closely with business and
  technical teams to understand, document, design
  and code ETL processes working closely with
  business teams to understand, document and design
  and code data analysis and reporting needs
  translating source mapping documents and
  reporting requirements into dimensional data
  models designing, developing, testing,
  optimizing and deploying server integration
  packages and stored procedures to perform all ETL
  related functions develop data cubes, reports,
  data extracts, dashboards or scorecards based on
  business requirements.

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Sample Role Business Intelligence Report
Developer

• The Business Intelligence Report Developer is
  responsible for developing, deploying and
  supporting reports, report applications, data
  warehouses and business intelligence systems.
  Primary responsibilities include creating and
  automating quality control processes and methods,
  providing maintenance and enhancement of data
  warehouse reports, creating ad hoc data warehouse
  queries, solving data related reporting issues
  and documenting all reports created. The report
  developer must have experience in user facing
  roles (e.g. gathering requirements, establishing
  project objectives, leading meetings) and in
  developing, selecting and conducting user
  training as needed. The Developer also
  participates in all aspects of data warehouse
  projects including conceptualization, design,
  construction, testing, selection, deployment and
  post-support implementation.

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Resources

• http//www.spscc.ctc.edu/academics/programs/busine
  ss-intelligence/class-description.html
• http//bellevuecollege.edu/business/info_bus_intel
  ligence.html
• http//www.austincc.edu/techcert/microsoftbusintel
  l.php
• http//www.sju-online.com/programs/business-intell
  igence-curriculum.asp
• http//www.setfocus.com/MastersProgram/curriculum_
  businessintelligence.aspx
• Top 5 On-Premise CRM Software Systems
  http//www.crmsoftware360.com/crmsoftware.htm

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Definitions

• Data mining is the process of extracting hidden
  patterns from data. As more data is gathered,
  with the amount of data doubling every three
  years data mining is becoming an increasingly
  important tool to transform this data into
  information. It is commonly used in a wide range
  of profiling practices, such as marketing,
  surveillance, fraud detection and scientific
  discovery.
• Dashboards Typically, information is presented
  to the manager via a graphics display called a
  Dashboard. A BIS (Business Intelligence System)
  Dashboard serves the same function as a cars
  dashboard. Specifically, it reports key
  organizational performance data and options on a
  near real time and integrated basis. Dashboard
  based business intelligence systems do provide
  managers with access to powerful analytical
  systems and tools in a user friendly environment.
• Enterprise resource planning (ERP) is a
  company-wide computer software system used to
  manage and coordinate all the resources,
  information, and functions of a business from
  shared data stores.
• Online analytical processing, or OLAP is an
  approach to quickly answer multi-dimensional
  analytical queries. OLAP is part of the broader
  category of business intelligence, which also
  encompasses relational reporting and data
  mining.  The typical applications of OLAP are in
  business reporting for sales, marketing,
  management reporting, business process management
  (BPM), budgeting and forecasting, financial
  reporting and similar areas. The term OLAP was
  created as a slight modification of the
  traditional database term OLTP (Online
  Transaction Processing)
• Multidimensional/ hyper cubes A group of data
  cells arranged by the dimensions of the data. For
  example, a spreadsheet exemplifies a
  two-dimensional array with the data cells
  arranged in rows and columns, each being a
  dimension. A three-dimensional array can be
  visualized as a cube with each dimension forming
  a side of the cube, including any slice parallel
  with that side. Higher dimensional arrays have no
  physical metaphor, but they organize the data in
  the way users think of their enterprise. Typical
  enterprise dimensions are time, measures,
  products, geographical regions, sales channels,
  etc. Synonyms Multi-dimensional Structure,
  Cube, Hypercube
• OLAP operations Slice, Dice, Drill Down/Up,
  Roll-up, Pivot
• See this site for all these definitions
  http//altaplana.com/olap/glossary.htmlSLICE AND
  DICE