Data has emerged as a new asset class that is yet to be fully leveraged by businesses to create new value. Consumers and businesses alike create terabytes of data every day that remains largely uncaptured and underutilized due to lack of skills and competencies in harnessing its true value.
Data is a vital input in achieving customer engagement, delivery of exceptional user experience, opportunity discovery, process improvement, decision support and business performance improvement.
Suboptimal data skills or lack thereof, and weak data culture in organizations remain the single largest impediments to the realization of unlocked value in data. As businesses continue to grapple with what decision models to adopt, the need for data science as competence is expected to rise exponentially.
The primary objective of the course is to impart participants with knowledge on:
- fundamentals of business intelligence and data analytics
- data and types of data – Context: structured and unstructured data
- best practices in data handling and management
- data ethics – data protection, data privacy ,etc.
- data collection, hygiene and preparation of datasets (pre-processing)
- hypothesis development (problem definition/use case development)
- data analysis and analytics tools – Tableau and PowerBI
- data visualization
- analysis interpretation
- communicating insights
- Data Analysts
- Business Analysts
- Business Users
- Line Managers
- Business Intelligence (BI) Developers
- Database Administrators, and Data Enthusiasts
After successful completion of this course, participants should be able to:
- conceptualize business problems
- determine the right data required for a given business problem
- perform data wrangling/preparation
- perform exploratory data analysis
- visualize and interpret data/Data storytelling
- communicate insights
- unlock the value in data
- understand the Ethics of data management/handling
Programme Structure & Delivery
The duration is 5 days.
The mode of delivery is physical.
|Day 1: Introduction to Business Intelligence (BI) & Data Analytics
Fundamentals of BI
- Introduction to Data Science
- Data Science Concepts
- Data Science roles, skillsets
- Why Business Intelligence?
|Data Management Best Practices
- Best Practices to implement BI projects
- Data story-telling concepts and use cases
- The role of Data Science in business
- Introduction to Cloud
- Data Governance and Master Data Management
|Day 3: Using BI to Improve Organizational Performance
- The role of business processes
- Becoming Data Driven
- Defining Winning KPIs
- Approach to Implementation (KPIs)
|Day 4: Hands-on Session
- Hands-on Session, Data Visualization using Tableau
|Day 5: Hands-on Session
- Hands-on Session, Data Visualization using Power-BI