Introduction

• Understanding the evolution, need and benefits of business intelligence
• Explaining various technical terminologies used with business intelligence

Integration

• Describing the business intelligence lifecycle and the functions of different management systems in an organization
• Illustrating the dependability and integration of ERP, SCM and E-commerce with BI

Data Management

• Detailing the process of data management in an organization
• Describing the Usage of BI for Reporting and Querying
• Understanding knowledge management and master data management (MDM) application in BI for data management

OLAP (Online analytical processing)

• Explaining the evolution, features and functions of OLAP
• Detailing the multidimensional analysis for OLAP implementation
• Illustrating the concept of data drill-in and drill-up
• Describing the various OLAP models as ROLAP and MOLAP and their applications

Dashboards

• Understanding executive information system (EIS), key performance indicator (KPI) and dashboards for BI management and control

Data Warehousing

• Describing the process of data design and dimensional modeling in data warehousing
• Explaining the process of managing metadata and focusing on the upcoming trends
• Detailing the need and techniques for extract, transform and load (ETL)

Data Analytics

• Describing the concepts and technical terminologies used in data analytics
• Detailing the different techniques used for data analytics like neural network, statistics, fuzzy logic, genetic algorithms, etc.

Value Proposition

• Understanding data mining and warehousing economics and viability derivation
• Illustrating concepts of cost matrix, SLA and ROI applied to data warehousing
• Describing the importance of risk mitigation in data mining and warehousing

Requirement Assessment

• Understanding the process for assessing the business problem
• Explaining the technique to specify desired outcomes and focus pertinent information

Design

• Illustrating the data design and architecture design process
• Describing considerations for hardware and software selection for BI
• Detailing the steps to generate data warehouse matrix and analyze dimensional modeling and ETL for BI

Implementation

• Detailing the process of physical design for implementing BI
• Explaining the various physical storage techniques like SAN, RAID, etc.
• Describing the different indexing techniques like B-Tree, clustered, etc. for optimization
• Understanding partitioning of data and clustering for improved performance
• Illustrating steps to select analytics criteria and usage of OLAP tools with data slicing or dicing in implementing BI in an organization

Post-Implementation

• Detailing the concepts and implementation of security policy, user privileges and usage of various security tools
• Describing the process for backup and recovery of data
• Illustrating the process to monitor and manage data growth in BI

Performance Measurement

• Explaining the technique for performance management by observing dashboards , assessing key performance indicators and using scorecard

Advanced BI

• Illustrating the future trends in BI as cloud computing, collaboration, mobility, etc.
• Detailing various case studies of BI

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