Business Intelligence and Analytics

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Business Intelligence and Analytics

Introduction to Business Intelligence and Analytics

Business Intelligence (BI) and Analytics involve collecting, analyzing, and presenting data to support decision-making and strategic planning. This module introduces the core concepts of BI and Analytics, including data warehousing, data mining, and the role of BI in business strategy.

Data Warehousing and ETL Processes

Learn about data warehousing concepts and Extract, Transform, Load (ETL) processes. Understand how to design and implement a data warehouse, and how to perform ETL tasks to integrate data from various sources.

Data Visualization and Reporting

Explore techniques for visualizing data and creating reports. Learn to use BI tools like Tableau, Power BI, or QlikView to build interactive dashboards, charts, and reports that help in data analysis and decision-making.

Advanced Analytics Techniques

Discover advanced analytics techniques such as predictive analytics, prescriptive analytics, and data mining. Learn how to apply statistical models and machine learning algorithms to extract insights and make data-driven decisions.

Business Intelligence Tools and Platforms

Understand various BI tools and platforms available in the market. This section covers popular tools like Microsoft Power BI, Tableau, and IBM Cognos, including their features, benefits, and use cases.

Data Modeling and Analysis

Learn the principles of data modeling and how to create data models that represent business processes and data relationships. Explore techniques for analyzing and interpreting data to support business objectives.

Performance Management and KPIs

Discover how to develop and track Key Performance Indicators (KPIs) and performance metrics. Learn how to use these indicators to monitor business performance, set targets, and drive strategic initiatives.

Big Data Analytics

Explore the concept of big data and its implications for analytics. Learn about big data technologies, such as Hadoop and Spark, and how to process and analyze large datasets to uncover insights.

Data Governance and Security

Understand the importance of data governance and security in BI and Analytics. Learn about data quality management, data privacy regulations, and best practices for securing sensitive information.

Real-World BI and Analytics Case Studies

Review real-world case studies and examples of how Business Intelligence and Analytics are applied in various industries. Learn from practical scenarios to understand how BI solutions drive business success.

Best Practices and Future Trends

Discover best practices for implementing BI and Analytics solutions. Explore emerging trends in the field, including AI integration, real-time analytics, and the evolving landscape of data technology.

Business Intelligence and Analytics Course Syllabus

1. Introduction to Business Intelligence (BI)

  • Overview of Business Intelligence: Definition, Benefits, and Evolution
  • Role of BI in Decision Making and Business Strategy
  • Components of BI Architecture: Data Sources, ETL (Extract, Transform, Load), Data Warehousing, Reporting, and Analytics

2. Data Fundamentals for BI

  • Introduction to Data Management: Data Governance, Quality, Integration, and Cleansing
  • Data Warehousing Concepts: Star Schema, Snowflake Schema, Data Mart
  • Data Modeling: Dimensional Modeling, OLAP (Online Analytical Processing), Data Cubes

3. ETL Processes in BI

  • Extracting Data: Data Extraction Techniques and Tools
  • Transforming Data: Data Transformation Techniques (Cleaning, Aggregation, Normalization)
  • Loading Data: Loading Techniques and Strategies into Data Warehouses or Data Marts

4. BI Tools and Platforms

  • Overview of BI Tools: Tableau, Power BI, QlikView, MicroStrategy
  • Comparing BI Tools: Features, Capabilities, and Suitability for Different Use Cases
  • Hands-on with BI Tools: Creating Reports, Dashboards, and Visualizations

5. Data Visualization Techniques

  • Principles of Data Visualization: Visual Perception, Effective Storytelling
  • Designing Effective Dashboards: Layout, Interactivity, Usability
  • Advanced Visualizations: Heatmaps, Treemaps, Geographical Maps

6. Reporting and Analytics

  • Types of BI Reports: Operational Reports, Ad-Hoc Reports, Analytical Reports
  • Analytical Techniques: Descriptive, Diagnostic, Predictive, Prescriptive Analytics
  • Advanced Analytics: Machine Learning, AI-Driven Analytics, Forecasting

7. Advanced BI Concepts

  • Big Data Analytics: Introduction to Hadoop, Spark, and NoSQL Databases
  • Real-Time BI and Streaming Analytics: Implementing Real-Time Data Processing
  • Mobile BI: Designing BI Solutions for Mobile Devices

8. Data Mining and Text Analytics

  • Introduction to Data Mining: Clustering, Association Analysis, Classification
  • Text Analytics: Sentiment Analysis, Text Mining Techniques
  • Implementing Data Mining Models in BI Solutions

9. Performance Management and KPIs

  • Key Performance Indicators (KPIs): Definition, Selection Criteria, and Measurement
  • Implementing Balanced Scorecards and Dashboards: Aligning KPIs with Business Objectives
  • Performance Management Frameworks: OKRs (Objectives and Key Results), SMART Goals

10. BI Deployment and Governance

  • BI Project Management: Planning, Execution, and Monitoring BI Projects
  • BI Governance: Policies, Security, Compliance, and Data Privacy
  • Change Management in BI Implementations: Handling Resistance and Ensuring Adoption

11. Business Intelligence Case Studies and Applications

  • Industry Use Cases: Examples from Retail, Healthcare, Finance, etc.
  • Case Studies: Analyzing Successful BI Implementations and Lessons Learned
  • Practical Applications: Applying BI Techniques to Solve Business Problems

12. Emerging Trends in BI and Analytics

  • AI-Driven BI: Cognitive Analytics, Natural Language Processing (NLP)
  • IoT (Internet of Things) Analytics: Leveraging IoT Data for BI Insights
  • Blockchain in BI: Use Cases and Implications for Data Integrity

13. Business Intelligence Certifications and Career Development

  • Overview of BI Certifications: Tableau, Microsoft Power BI, Qlik Sense Certifications
  • Certification Exam Tips and Resources
  • Career Development in Business Intelligence and Analytics

Training

Basic Level Training

Duration : 1 Month

Advanced Level Training

Duration : 1 Month

Project Level Training

Duration : 1 Month

Total Training Period

Duration : 3 Months

Course Mode :

Available Online / Offline

Course Fees :

Please contact the office for details

Placement Benefit Services

Provide 100% job-oriented training
Develop multiple skill sets
Assist in project completion
Build ATS-friendly resumes
Add relevant experience to profiles
Build and enhance online profiles
Supply manpower to consultants
Supply manpower to companies
Prepare candidates for interviews
Add candidates to job groups
Send candidates to interviews
Provide job references
Assign candidates to contract jobs
Select candidates for internal projects

Note

100% Job Assurance Only
Daily online batches for employees
New course batches start every Monday
Download Syllabus