PROGRAM DETAILS

Program Overview

The Mastering Big Data and Data Analytics program is an intensive 5-day course tailored specifically for professionals in the finance and accounting sectors who are eager to enhance their data competency in today’s digital era. As the financial landscape becomes increasingly data-driven, the ability to understand, analyze, and extract insights from large datasets has become an essential skill for decision-makers and analysts alike.

This program bridges the gap between traditional financial expertise and modern data analytics by combining theoretical frameworks with hands-on learning. Participants will explore the fundamentals of big data, data mining, and machine learning, and learn how to apply these tools to solve real-world financial problems. The curriculum covers a wide range of topics, including financial data management, predictive analytics, risk modeling, trend analysis, and the integration of AI tools in financial forecasting.

Throughout the program, learners will engage with industry-leading software platforms such as Python, SQL, Power BI, and Excel for data analysis and visualization. Case studies and interactive exercises will simulate practical scenarios, enabling participants to apply analytical techniques in budgeting, auditing, fraud detection, and performance analysis.

By the end of the course, participants will be equipped to turn complex financial data into strategic insights, making them valuable assets in a data-centric finance function.

Learning Objectives

By the end of the training, participants will be able to:

• Understand the fundamentals and strategic value of big data in finance and accounting.
• Identify and work with structured and unstructured financial data sources.
• Use data analytics tools (such as SQL, Python, Excel, and BI platforms) to clean, process, and analyze large datasets.
• Apply descriptive, diagnostic, predictive, and prescriptive analytics techniques to financial problems.
• Visualize and communicate insights using dashboards and reports tailored to finance and accounting functions.

Target Audience

• Finance Managers and Financial Analysts
• Chartered Accountants and Auditors
• FP&A Professionals
• Accounting & Reporting Specialists
• Data Analysts in the finance sector
• Professionals transitioning into data-driven finance roles

Training Methodology

• Instructor-led sessions with real-world finance datasets
• Hands-on exercises, coding labs, and interactive case studies
• Group discussions, quizzes, and daily recap sessions
• Capstone project and final presentations
• Post-training resources and self-study material

5-Day Program Content

Day 1: Introduction to Big Data in Finance

• What is Big Data? Volume, Velocity, Variety, Veracity, Value
• Big Data in the financial ecosystem: Use cases and impact
• Overview of structured vs unstructured financial data
• Data lakes vs data warehouses in finance
• Introduction to data architecture: ETL and pipelines
• Tools overview: Excel, SQL, Python, Power BI, Hadoop basics

Day 2: Data Management & Preparation for Finance

• Data cleaning and wrangling: Missing data, outliers, formatting issues
• Using SQL for querying and managing financial databases
• Data preparation in Excel and Power Query
• Introduction to Python for data cleaning (Pandas basics)
• Merging and joining financial data across sources (ERP, CRM, etc.)

Day 3: Exploratory Data Analysis (EDA) & Descriptive Analytics

• Understanding financial metrics and KPIs
• Descriptive statistics in financial datasets
• Trend analysis, variance analysis, and anomaly detection
• Data visualization techniques for finance (charts, pivots, heatmaps)
• Tools: Excel dashboards, Python visualizations (Matplotlib/Seaborn), Power BI

Day 4: Advanced Analytics in Finance (Predictive & Prescriptive)

• Introduction to predictive modeling: Forecasting revenue, cash flow, and expenses
• Regression analysis and time series basics
• Scenario and sensitivity analysis
• Prescriptive analytics using decision trees and optimization models
• Introduction to machine learning in finance (conceptual)

Day 5: Building Dashboards & Capstone Project

• Principles of financial data storytelling
• Dashboard tools comparison: Excel vs Power BI vs Tableau
• Creating KPI dashboards for CFO and audit reporting
• Sharing insights: Reports, dashboards, and automation
• Ethics and compliance in financial data analytics