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Course Description

Certified Big Data & Data Analytics Practitioner is a hands-on and practical training program designed to equip participants with the knowledge and skills to collect, process, analyze, and visualize large-scale data for actionable business insights. The program emphasizes real-world applications of big data technologies, data analytics frameworks, and visualization tools to support data-driven decision-making. Participants completing this program will receive a certificate recognizing their capability as a Big Data & Analytics practitioner.

Course Objectives

Upon the successful completion of this course, each participant will be able to:

  • Understand the fundamentals of big data, data types, and analytics.
  • Work with data storage, processing, and retrieval systems for large datasets.
  • Apply data cleaning, transformation, and preprocessing techniques.
  • Use statistical and machine learning methods to analyze structured and unstructured data.
  • Create data visualizations and dashboards to communicate insights effectively.
  • Understand big data technologies such as Hadoop, Spark, and cloud-based analytics tools.
  • Implement data-driven solutions for business problems.
  • Interpret analytics results to support strategic and operational decision-making.

Who Should Attend?

This course is designed for data analysts, business analysts, IT professionals, managers, and professionals seeking practical skills in big data and data analytics.

Course Agenda

Registration

Welcome & Introduction

Pre-Test

Day 1: Introduction to Big Data & Data Analytics

  • Overview of Big Data: 5 V’s (Volume, Velocity, Variety, Veracity, Value)
  • Types of data: structured, semi-structured, unstructured
  • Data sources and collection methods
  • Big Data ecosystem overview (Hadoop, Spark, NoSQL databases)
  • Introduction to analytics: descriptive, diagnostic, predictive, prescriptive
  • Tools and platforms for data analytics
  • Workshop Activity: Explore sample datasets and classify data types

Day 2: Data Storage, Cleaning & Preprocessing

  • Data storage technologies: relational databases, NoSQL, cloud storage
  • Data cleaning techniques: handling missing values, duplicates, outliers
  • Data transformation and normalization
  • Data integration and preprocessing for analytics
  • Introduction to ETL (Extract, Transform, Load) process

Day 3: Data Analytics Techniques & Statistical Methods

  • Introduction to descriptive statistics and data summarization
  • Correlation, regression, and hypothesis testing
  • Exploratory data analysis (EDA)
  • Basic machine learning concepts: classification, clustering, and regression
  • Applying analytics methods to solve business problems

Day 4: Big Data Technologies & Tools

  • Overview of Hadoop ecosystem: HDFS, MapReduce
  • Apache Spark for big data processing
  • NoSQL databases overview (MongoDB, Cassandra)
  • Introduction to cloud-based data analytics platforms (AWS, Azure, Google Cloud)
  • Working with large datasets efficiently

Day 5: Data Visualization & Business Insights

  • Principles of data visualization and storytelling
  • Dashboard creation with Tableau / Power BI / Python libraries
  • Communicating insights effectively to stakeholders
  • Key metrics and KPIs for decision-making
  • Case study: end-to-end data analytics project

Post Test

End of the Course

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.