Business Intelligence Training

Business Intelligence Online Training

Introduction To Business Intelligence Training Course:

The Business intelligence in short called as BI. It is a collection of decision support technologies for the enterprise aimed at enabling the knowledge workers such as executives, managers, &  analysts to make better & faster decisions. To  define  theoretically Business Intelligence is  the use of high class software or the business applications or the use of values to make better decisions for the company. Based on the newest technologies, The Business Intelligence  systems are essential for the decisional level efficiency, but also for improving the relations with the clients, employees & suppliers by facilitating the decisional process, increasing  the productivity of employees, lower costs, increasing the relationship with the partners & the business development. To understand the importance of BI, register with Global Online Trainings for Business Intelligence Training

  • Evolution, need and benefits of business intelligence
  • Business intelligence technical terminologies
  • Describing the business intelligence lifecycle and the functions of different management systems
  • Illustrating the dependability and integration of ERP, SCM & E-commerce with BI
Data Management
  • Detailing the process of data management in an organization
  • Describing the Usage of BI for Reporting & Querying
  • Understanding knowledge management and master data management (MDM) application in BI for data management
Online analytical processing
  • Explaining the evolution, features and functions of OLAP
  • Multidimensional analysis for OLAP implementation
  • Illustrating the concept of data drill-in and drill-up
  • Various OLAP models as ROLAP & MOLAP and their applications
  • Understanding executive information system, key performance indicator (KPI) and dashboards for BI management and control
Data Warehousing
  • Explaining the process of data design & dimensional modeling in data warehousing
  • Explaining the process of managing the metadata & focusing on the upcoming trends
  • Detailing the need and techniques for extract, transform & load (ETL)
Data Mining
  • Introduction to the concept of data mining and various techniques like neural networks, decision trees, etc.
Data Analytics
  • Introduction to the concepts and technical terminologies used in data analytics
  • Detailing the different techniques used for the data analytics like neural network, statistics, fuzzy logic, genetic algorithms, etc.
Value Proposition
  • Understanding data mining & warehousing economics and viability derivation
  • Illustrating concepts of cost matrix, SLA & ROI applied to the data warehousing
  • Describing the importance of risk mitigation in data mining & warehousing
Requirement Assessment
  • Understanding the process for assessing the business problem
  • Explaining the technique to specify desired outcomes & focus pertinent information
  • Illustrating the data design and architecture design process
  • Considerations for hardware and software selection for BI
  • Detailing the steps to generate data warehouse matrix & analyze dimensional modeling and ETL for BI
  • Detailing the process of physical design for implementing the BI
  • Explaining the various physical storage techniques like SAN, RAID, etc.
  • Different indexing techniques like B-Tree, clustered, etc. for optimization
  • Understanding partitioning of data & clustering for improved the performance
  • Illustrating steps to select analytics criteria and usage of OLAP tools with data slicing/dicing in implementing BI
  • Detailing the concepts & implementation of security policy, user privileges & usage of different security tools
  • Describing the process for backup and recovery of data
  • Illustrating the process to monitor & managing data growth in BI
Performance Measurement
  • Describing the technique for performance management by observing dashboards , assessing key performance indicators & using scorecard
BI Advanced
  • Illustrating the future trends in BI as cloud computing, collaboration and mobility
  • Detailing various case studies of BI