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£1,495
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UK Wide
Full day
All levels
Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance.
You will learn how to:
Specify a data warehouse schema
Identify the data and visualization to be used for data mining and Business Intelligence
Design a Business Intelligence user interface
Introductions
Agenda
Expectations
The challenge of decision making
What is Business Intelligence?
The Business Intelligence value proposition
Business Intelligence taxonomy
Business Intelligence management issues
Data warehousing
Data and information
Information architecture
Defining the data warehouse and its relationships
Facts and dimensions
Modeling, meta-modeling, and schemas
Alternate architectures
Building the data warehouse
Extracting
Transforming
Loading
Setting up the data and relationships
Dimensions and the Fact Table
Implementing many-to-many relationships in data warehouse
Data marts
What is OLAP?
OLAP and OLTP
OLAP functionality
Multi-dimensions
Thinking in more than two dimensions
What are the possibilities?
OLAP architecture
Cubism
Tools
OLAP variations - MOLAP, ROLAP, HOLAP
BI using SOA
Applications of Business Intelligence
Applying BI through OLAP
Enterprise Resource Planning and CRM
Business Intelligence and financial information
Data access
Push-pull data access
Types of decision support systems
Designing the front end
Presentation formats
Dashboards
Types of dashboards
Common dashboard features
Briefing books and scorecards
Querying and Reporting
Reporting emphasis
Retrofitting
Talking back
Key Performance Indicators
Report Definition and Visualization
Typical reporting environment
Forms of visualization
Unconstrained views
Data mining
What is in the mine?
Applications for data mining
Data mining architecture
Cross Industry Standard Process for Data Mining (CISP-DM)
Data mining techniques
Validation
The business analyst role
Business analysis and data analysis
Five-step approach
Cultural impact
Identifying questions
Gathering information
Understand the goals
The strategic Business Intelligence cycle
Focus of Business Intelligence
Design for the user
Iterate the access
Iterative solution development process
Review and validation questions
Basic approaches
Building ad-hoc queries
Building on-demand self-service reports
Closed loop Business Intelligence
Coming attractions - future of Business Intelligence
Best practices in Business Intelligence