DATA ANALYTICS & AI FOR FINANCE

A Comprehensive Data Analytics Course
Taught by Leading World Authority

Why Join This Program? 

 

Finance teams today work with huge amounts of data, but many struggle to turn it into clear, actionable insights. This program gives you the skills to: 

  • Understand the full data-to-decisions journey.
  • Apply descriptive, predictive, and prescriptive analytics in finance
  • .Build dashboards and reports that truly support decision-making.
  • Apply strong data governance and quality principles.
  • Present insights in a clear and compelling way to senior leader

Program Snapshot

  • Duration: 12 weeks (24 hours of live teaching)

  • Format: Live online classes + recordings + capstone project

  • Start: Rolling cohorts throughout the year

  • Audience: CFOs, Finance Directors, Controllers, FP&A Managers, and aspiring leaders

  • Certificate: MECA CFO Academy Certificate of Completion

  • Tuition: USD 995 (group and alumni pricing available)

Curriculum Overview

    1. Module 1: Introduction to Data Analytics and Finance Applications

    2. Module 2: Data Quality, Strategy, and Governance

    3. Module 3: Descriptive Analytics – Understanding the past

    4. Module 4: Associative & Inferential Analytics – Testing ideas and relationships

    5. Module 5: Predictive & Prescriptive Analytics – Forecasting and decision-making

    6. Module 6: Data Storytelling & Decision Science – Presenting insights with impact

What's Included in this Course..

MODULE 2

Data Strategy & Governance

Week 3: Data Strategy, Management, and Governance

  • Elements of a Data & Analytics Strategy.
  • Data management vs. data content.
  • 12 dimensions of Data Quality and cost of poor data.
  • Data governance frameworks: policies, principles, standards.
  • Smart data sourcing: sampling, feature engineering, blending, synthetic data, surveys.
MODULE 1

Foundations of Analytics

Week 1: Introduction to Data Analytics

  • The business case for analytics: from anecdotes to insights.
  • The analytics continuum (Descriptive → Predictive → Prescriptive).
  • Building blocks: Data, Algorithms, Assumptions, Ethics.
  • Framing bias and the importance of asking the right questions.

Week 2: Business Data & Enterprise Systems

  • Types of business data: zero, first, second, third party.
  • Data classification: structured, unstructured, reference, master, transactional.
  • Enterprise IT systems: OLTP, OLAP, Middleware, Data Warehouses.
  • The Data Lifecycle (DLC): Capture → Integration → Science → Decision.
 
MODULE 3

Descriptive Analytics

Week 4: Exploratory Analytics – Central Tendency

  • Introduction to Data Science vs Statistics.
  • Measures of central tendency (Mean, Median, Mode, GM, HM).
  • Applications in business: salary analysis, investment growth, profitability.

Week 5: Associative Analytics – Relationships & Correlations

  • Correlation analysis: Pearson, Spearman, etc.
  • Association rules and patterns (Apriori algorithm).
  • Business use cases: cross-selling, customer behavior analysis.

Week 6: Inferential Analytics – Insights from Samples

  • Hypothesis testing (T-tests, ANOVA).
  • Confidence intervals and significance levels.
  • Applications in finance and market analysis.
MODULE 4

Descriptive Analytics

Week 4: Exploratory Analytics – Central Tendency

  • Introduction to Data Science vs Statistics.
  • Measures of central tendency (Mean, Median, Mode, GM, HM).
  • Applications in business: salary analysis, investment growth, profitability.

Week 5: Associative Analytics – Relationships & Correlations

  • Correlation analysis: Pearson, Spearman, etc.
  • Association rules and patterns (Apriori algorithm).
  • Business use cases: cross-selling, customer behavior analysis.

Week 6: Inferential Analytics – Insights from Samples

  • Hypothesis testing (T-tests, ANOVA).
  • Confidence intervals and significance levels.
  • Applications in finance and market analysis.

 

MODULE 5

Communicating & Leading with Data

Week 10: Data Storytelling

  • The 8 stages of communicating analytics findings.
  • Principles of visualization for executives.
  • Designing dashboards, BI reports, and OLTP reports for different audiences.

Week 11: Decision Science – Data-Driven Decision Making

  • Decision frameworks and biases.
  • 40-70 rule of decision making.
  • Balancing intuition vs data-driven insights.

Week 12: Capstone & Future Trends

  • Capstone Project Presentations.
  • Peer review and faculty feedback.
  • Emerging trends: Generative AI, automation, real-time analytics.
Wrap-up: building a data-driven CFO mindset 

Who Should Attend

  • CFOs and senior finance leaders

  • Finance managers preparing for executive roles

  • Professionals who want to use data to improve decision-making

YES, I WANT IN!

Program Snapshot

  • Duration: 12 weeks (24 hours of live teaching)
  • Format: Live online classes + recordings + capstone project
  • Start: Rolling cohorts throughout the year
  • Audience: CFOs, Finance Directors, Controllers, FP&A Managers, and aspiring leaders
  • Certificate: MECA CFO Academy Certificate of Completion
  • Tuition: USD 995 (group and alumni pricing available)

Key Benefits

  • A structured, step-by-step journey across 6 modules.
  • Real-world examples tied directly to finance: P&L, cash flow, risk, growth.
  • Hands-on practice with Excel, Power BI, and optional R/Python.
  • A capstone project where you analyze real data and present your findings.
  • Recognition with a MECA CFO Academy certificate.
FEW SEAGS ARE LEFT!

Special Offer with 30% Discount

Regular Price $695

 

Now only $495

Live Sessions Start on Saturday October 4, 2025

Join Now Only for

$490

Save $210!

ENROLL NOW
14-DAY MONEY-BACK GUARANTEE

If you aren’t completely satisfied with the Data Analytics course, let us know within the first 14-days for a full refund. No questions asked.

Program Faculty - Dr. Preshanth Southekal

Dr. Prashanth Southekal is the Managing Principal of DBP-Institute. He is an experienced technology professional who understands what it takes to run efficient technology based solutions, processes, and organizations. He brings over 20 years of experience in Data and Information Management from companies such as SAP AG, Accenture, Deloitte, P&G, and General Electric. Prashanth has published 2 books on Information Management  including the most recent book - "Data for Business Performance". He lives in Calgary, Canada.
 

Course Takeaways

By the end of the program, you will:

  • Know how to ask the right business questionswith data.
  • Be able to clean and prepare datafor accurate insights.
  • Use analytics tools to spot trends, test ideas, and make forecasts.
  • Create dashboards and presentations that speak to executives.
  • Apply governance and quality to keep data reliable.