Introduction to Business Intelligence
Business Intelligence and Information Exploitation: Improving Decision making process, Why Business Intelligence, Advantage of Information Asset, Actionable Intelligence.
Value of B.I. : Value Drivers and Information Use, Performance Metrics and Key Performance Indicators, Horizontal&Vertical Use Case s for Business Intelligence,
Business Intelligence Roadmap & Environment
A Business Intelligence Strategy, The Business Intelligence and Analytics Spectrum, The Business Intelligence Roadmap- Planning the B.I. Plan, Aspects of a Business Intelligence and Analytics, The Organizational B.I.Framework, Services and System Evolution, Management Issues,
Business Processes and Information Flow: Analytical Information Needs and Information Flows, Information Processing and Information Flow, Information Processing and Information Flow, Modelling Frameworks,
The Data Warehouse Environment
The Structure of the Data Warehouse, Subject Orientation, Granularity, Partitioning as a Design Approach, Structuring Data in the Data Warehouse, Data Homogeneity
/ Heterogeneity, Reporting and the Architected Environment,
The Data Warehouse and Design
Beginning with Operational Data, Data/Process Models and the Architected Environment, The Data Warehouse and Data Models, dimensional modelling process, Star schema, Snow flake schema, and Fact Constellation schema, Grain of dimensional model, transactions, Recurring Snapshots, Accumulating Snapshots, Dimensions (SCD types, conformed dimensions), Facts (additive, semi-additive, non-additive), Hierarchy in dimensions, parent child relationships, Many-Many Dimensional relationship, Multi Valued Dimensions and Dimension Attributes, Distributed Data Warehouse, External/Unstructured Data and the Data Warehouse.
ETL Data Structures & Architecture. Extracting process- Building the Logical Data Map, Integrating Heterogeneous Data Sources, Mainframe Sources, Flat Files, XML Sources, Web Log Sources. Cleaning and Conforming- : Design Objectives & cleaning deliverables, Data Quality, Data profiling, Data enrichment, data duplication,
concept and Change data capture, Transformation concept, lookups, time lag, formats, consistency, Loading concept, Initial and Incremental loading, late arriving facts, ETL & Metadata- Defining Metadata, Business Metadata, Technical Metadata, ETL-Generated Metadata,
Metadata Layer, Presentation Layer, Data Layer, Use of different layers and overall Reporting architecture, Various report elements such as Charts, Tables, prompts Data aggregation: Table based, Materialized views, Query rewrite, OLAP, MOLAP, Dashboards, Ad-hoc reports, interactivity in analysis (drill down, drill up), Security: report level, data level (row, column), Scheduling
Self Learning Module
Big data like HIVE, PIG and DW appliances like Netezza, Teradata, Smart Change data capture using log based techniques, Real time BI, Operational BI, Embedded BI, Agile BI, BI on cloud, BI applications (Case study on BI tools like: QlikView, Pentaho, Tableau, MyReport, Spotfire, OR any other BI tool)