Data Management, Visualization and Business Intelligence

1. An Introduction to Data Literacy 

Objective: Familiarize participants with the importance of data in decision-making and the basic terminologies and concepts of data management.

• Key topics:
  • Understanding data types and formats
  • Importance of data in modern business
  • Data-driven decision making
  • Dimensional analysis
  • Basic types of visualization charts and graphs
  • Basics of reports, dashboards, and storytelling

2. An Introduction to Relational Database Management Systems (RDBMS) 

Objective: Introduce RDBMS and their role in storing and managing structured data.

• Key topics:
  • RDBMS concepts
  • Tables, keys, and relationships
  • Introduction to popular RDBMS (e.g., MySQL, PostgreSQL)
  • Database different schemas.
  • An introduction to ETL diagrams.
  • DDL and DML languages in SQL to build, modify, and drop relationships.

3. SQL: A Practical Introduction for Querying Databases 

Objective: Teach participants to write SQL queries to manipulate and retrieve data from relational databases.

• Key topics:
  • SQL basics: SELECT, INSERT, UPDATE, DELETE
  • JOIN operations and relationships
  • Filtering and grouping data
  • Aggregating and sorting data
  • Subqueries and complex queries
  • CTEs and views concepts.
  • Optimizing Query Performance

4. Data Warehouse Fundamentals 

Objective: Provide an overview of data warehousing and its significance in large-scale data management.

• Key topics:
  • Data warehouse architecture
  • ETL (Extract, Transform, Load) processes
  • Data marts and OLAP cubes
  • Design and populate a data warehouse, and model and query data using CUBE, ROLLUP, and materialized views.
  • Identify popular data analytics and  business intelligence tools and vendors and create data visualizations using IBM Cognos Analytics.
  • How to design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard?

5. Getting Started with Tableau 

Objective: Introduce Tableau as a powerful data visualization tool to turn raw data into actionable insights.

• Key topics:
  • Basics of Tableau interface
  • Connecting Tableau to Data Sources
  • Building basic charts, dashboards, and reports
  • Visual best practices

6. Data Integration, Data Storage, & Data Migration 

Objective: Explore techniques for integrating, storing, and migrating data across different systems.

• Key topics:
  • Understand Tableau’s fundamental concepts, significance in data visualization, diverse product range and key features crucial for data professionals.
  • Analyze and evaluate the capabilities of Tableau Public as a powerful Business Intelligence (BI) tool for data visualization and analysis.
  • Implement relationships between data tables, use Tableau calculations for analytics, empower user interaction, and apply filters and highlighting.
  • Develop expertise in Tableau dashboard design principles, organize visual elements effectively, and apply best practices for interactive dashboards.

7. Data Privacy, Security, Governance, Risk, and Compliance 

Objective: Provide knowledge on data privacy, security measures, and compliance with legal frameworks.

• Key topics:
  • Understanding data privacy laws (GDPR, CCPA)
  • Develop and implement effective data privacy and security strategies.
  • Understand and apply security measures to protect and govern organizational data.
  • Conduct risk assessments and implement appropriate risk management practices.
  • Navigate and comply with relevant legal and regulatory compliance requirements.

8. Data Management Capstone Project 

Objective: Apply the knowledge gained from the previous modules in a practical, real-world scenario.

• Participants will:
  • Integrate valuable applied data management skills employers need for a wide range of data-related roles in a culminating project.
  • Gain hands-on experience using industry-specific data tools including Excel, SQL, PostgreSQL, Tableau, etc.
  • Demonstrate best practices and apply those methodologies through industry-standard processes, data design, governance, security, and reporting.
  • Showcase your ability to solve problems relevant to working with data that you can discuss with colleagues and prospective employers.

• Equip participants with foundational and intermediate knowledge of data management principles.
• Provide hands-on experience with relational databases, SQL, and data integration tools.
• Introduce best practices for data privacy, security, and governance.
• Offer practical knowledge of data warehousing and visualization tools such as Tableau.
• Develop problem-solving skills through a capstone project that integrates learned concepts.

• Professionals in business, IT, or related fi elds looking to enhance their data management skills.
• Data analysts, business analysts, and database administrators seeking intermediate-level knowledge of data management and visualization tools.
• Individuals transitioning to data-related roles who have a basic understanding of data concepts.
• Team leaders and managers aiming to implement eff ective data strategies in their organizations.