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Practical Data Analytics and Business Intelligence Master Program

Transform your career with the Practical Data Analytics and Business Intelligence Master Program. Gain hands-on expertise in data collection, analysis, and visualization to drive strategic decision-making. Ideal for professionals looking to excel in data-driven environments and deliver impactful business insights.

Virtual classes | 11 Week(s) | FEE: Ksh 140000 / USD 1200

Apply Now

Application Deadline: 5th April 2026

Image thumbnail depicting Practical Data Analytics and Business Intelligence Master Program on indepth research institute website

Want to upskill?

Enroll today in our Practical Data Analytics and Business Intelligence Master Program to elevate and expand your expertise.

Program Fee

140000 / USD 1200

Duration

0 Week(s)

Study Mode

Virtual classes

Introduction

The Practical Data Analytics and Business Intelligence Master Program is designed to equip professionals with essential skills in data analytics and business intelligence. Through hands-on training, you'll learn to effectively collect, analyze, and visualize data, enabling you to make informed decisions and drive business success. This program provides practical, real-world applications to help you master data-driven strategies and enhance your career in today’s data-centric landscape

Application Process

1

Register

Submit your registration by filling in the form online.

2

Make Payments

Receive Invoice upon registration and make payments.

3

Join program

Choose a mode of study and attend course.

Program Prerequisites

Participants are expected to have:

  • Basic computer skills and comfort working online.
  • Interest in data analysis (prior experience optional).
  • Familiarity with spreadsheets (e.g., Microsoft Excel).
  • Foundational statistics knowledge.
  • Basic understanding of programming concepts.

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Program Modules

  • Fundamentals of data analytics and business intelligence (BI)
  • Importance of data-driven decision-making
  • Data analytics lifecycle
  • Role of BI in organizations
  • Introduction to key concepts:
    • Data warehousing
    • Data mining
    • Data visualization
  • Provides a solid foundation for the rest of the course
  • Case Study: Enhancing Operational Efficiency with Data Analytics
  • Focus on data preparation and cleaning using Microsoft Excel
  • Handle common data issues: missing values, duplicates, incorrect data types
  • Techniques covered: data transformation, normalization, standardization
  • Use advanced Excel functions and formulas for automating the data cleaning process
  • Case Study: Optimizing Financial Data Accuracy and Efficiency with Advanced Excel Techniques
  • Builds on basic Excel skills
  • Focuses on advanced Excel functionalities for data analysis
  • Exploration of:
    • Pivot tables
    • Advanced charting techniques
    • Excel's Data Analysis Toolpak
  • Emphasis on:
    • Creating dynamic dashboards
    • Generating reports to visualize and interpret data effectively
  • Case Study: Leveraging Advanced Excel Techniques for Efficient Financial Reporting and Data Visualization
  • Introduction to SQL (Structured Query Language) as a tool for managing and querying databases
  • Creating, modifying, and querying databases using SQL
  • Basic SQL syntax
  • Joining tables
  • Filtering data
  • Aggregating results
  • Extracting meaningful insights from large datasets
  • Case Study: Leveraging SQL for Enhanced Customer Segmentation and Targeted Marketing
  • Expand on basic SQL knowledge with advanced techniques.
  • Learn about subqueries, window functions, and common table expressions (CTEs).
  • Explore stored procedures for complex data analysis.
  • Practice solving real-world data analysis problems with advanced SQL queries.
  • Case Study: Optimizing Fraud Detection and Risk Assessment in Financial Services with Advanced SQL Techniques
  • Introduction to Python as a versatile programming language for data analysis
  • Basics of Python programming:
    • Data types
    • Control structures
    • Functions
  • Introduction to key libraries for data analysis:
    • pandas
    • numpy
  • Enabling efficient data manipulation and analysis
  • Case Study: Streamlining Financial Data Analysis with Python
  • Builds on Python fundamentals.
  • Focuses on data visualization using popular libraries (e.g., matplotlib, seaborn).
  • Teaches how to create various charts and plots for visual data representation.
  • Covers best practices for data visualization.
  • Explores techniques for creating interactive visualizations.
  • Case Study: Interactive Data Visualization for Investment Analysis with Python
  • Perform exploratory data analysis (EDA) using Python
  • Summarize the main characteristics of a dataset using visual methods
  • Learn to identify patterns, detect anomalies, and generate hypotheses
  • Explore techniques for data profiling, correlation analysis, and feature selection
  • Case Study: Enhancing Fraud Detection in Financial Services Through Exploratory Data Analysis with Python
  • Introduction to Power BI as a tool for data visualization and reporting
  • Connecting to various data sources
  • Transforming data for analysis
  • Creating interactive dashboards and reports
  • Exploring key features:
    • Power Query
    • Data modeling
    • DAX (Data Analysis Expressions)
  • Case Study: Streamlining Financial Reporting and Decision-Making with Power BI
  • Builds on basic Power BI knowledge.
  • Covers advanced Power BI techniques.
  • Teaches advanced data modeling.
  • Explores custom visuals.
  • Focuses on optimizing performance in Power BI.
  • Introduces techniques for creating advanced DAX measures.
  • Explores leveraging Power BI's AI capabilities.
  • Case Study: Optimizing Financial Reporting and Forecasting with Advanced Power BI Techniques and AI Integration
  • Focus on integrating Power BI with Excel, SQL, and Python for comprehensive data analytics solutions.
  • Learn to use Power BI's data connectors to integrate data from multiple sources.
  • Cover techniques for automating data workflows.
  • Explore the creation of end-to-end BI solutions.
  • Case Study: Optimizing Financial Reporting with Power BI, Excel, SQL, and Python
  • Opportunity to apply skills and knowledge gained throughout the program
  • Work on a comprehensive real-world data analytics problem
  • Involves data collection, cleaning, analysis, visualization, and reporting
  • Culminates in a presentation of findings and recommendations

Certifications

Upon successful course completion, participants will be awarded a certificate of program completion from Indepth Research Institute.

Certification image

The Program also Includes

Program Delivery

Delivered via video lectures in form of zoom and google meet.

Real World Examples

Delivered through a combination of video and live online lectures.

Hands on Experience

Learn through individual assignments and feedback.

Debrief of Learning

A combination of recorded and live video lectures.

Tech Stack

No Technology needed

Upcoming Application Deadline

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Deadline: 5 Apr 2026

Apply Now

Program Fees

Fees: 140000 / USD 1200

We accept

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Interested in this Program?

Curious about how the program can help you reach your goals? To get started, just click the button below to make an inquiry, or reach out to us at outreach@indepthresearch.org or call us at +254 715 077 817

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