Certified Business Intelligence Professional
- Offered byVSkills
Certified Business Intelligence Professional at VSkills Overview
Duration | 12 hours |
Total fee | ₹3,499 |
Mode of learning | Online |
Credential | Certificate |
Certified Business Intelligence Professional at VSkills Highlights
- Earn a certificate of completion from Vskills
- Get Lifelong e-learning access
Certified Business Intelligence Professional at VSkills Course details
- Job seekers looking to find employment in MIS or analytics department of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.
- Vskills Business Intelligence certification tests the candidates on various areas in business intelligence which includes knowledge of planning, designing, implementing and maintaining the organization’s data warehouse, data mining, data analytics and data intelligence for better decision making
- This certification will teach you the basics of business intelligence, it's application & usefulness to businesses
- You will gain the skills to improve performance using data, statistical & quantitative analysis & predictive modeling to make important decisions
- With such advances, organisations can make decisions more effectively about pricing, marketing, products and more than they have ever been able to in the past
Certified Business Intelligence Professional at VSkills Curriculum
Introduction
Evolution
Need and benefits
Technical terms
Integration
BI life cycle and management systems functions
ERP and BI
SCM and BI
E-commerce and BI
Data Management
Data Management
Reporting and Querying
BI and MDM
Knowledge Management
OLAP (Online analytical processing)
Evolution, Features and functions
Multidimensional analysis
Data drill-in and drill-up
OLAP Models (ROLAP and MOLAP) and applications
Dashboards
EIS
KPI
BI Dashboard
Data Warehousing
Dimensional modeling and metadata
ETL
Data Analytics
Concepts and terminologies
Techniques used (neural network, statistics, fuzzy logic, genetic algorithms
Value Proposition
Business intelligence economics
Cost Matrix, SLA and ROI
Risk Mitigation
Requirement Assessment
Business problem assessment
Focusing pertinent information
Desired outcome specification
Design
Data and architecture design
Hardware and Software Selection
Generate data warehouse matrix
Dimensional modeling and ETL
Implementation
Physical Design
Physical Storage (SAN, RAID, etc.)
Indexing (B-Tree, Clustered, etc.)
Data partitioning and clustering for performance
Analytics criteria selection
OLAP tools and data slicing or dicing
Post-Implementation
Security Policy, user privileges and security tools
Backup and Recovery
Monitoring and managing data growth
Performance Measurement
Observing dashboards
Assessing KPI and scorecard
Advanced BI
Future Trends
Case Studies