Center of Excellence for IT at Bellevue College

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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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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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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
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By 2012, business units will control at least 40% of the total budget for
BI
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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
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In 2009, collaborative decision making will emerge as a new product category that combines social software with BI Platform capabilities
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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?id=856714

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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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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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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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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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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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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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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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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: 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 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-visualization-modernapproaches/

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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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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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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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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.

 http://www.spscc.ctc.edu/academics/programs/business-intelligence/classdescription.html
 http://bellevuecollege.edu/business/info_bus_intelligence.html
 http://www.austincc.edu/techcert/microsoftbusintell.php
 http://www.sju-online.com/programs/business-intelligence-curriculum.asp
 http://www.setfocus.com/MastersProgram/curriculum_businessintelligence.a
spx
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Top 5 On-Premise CRM Software Systems http://www.crmsoftware360.com/crmsoftware.htm

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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 car’s 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.html#SLICE AND DICE