Overview of Course

The Enterprise Big Data Analyst (EBDA) course provides an in-depth understanding of big data technologies and their applications. This course covers a wide range of topics, including data management, data analytics, and data visualization. The course helps learners become proficient in working with big data tools and techniques.

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Course Highlights

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Comprehensive coverage of big data analytics

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Hands-on experience in working with big data tools

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Industry-relevant case studies and projects

Key Differentiators

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    Personalized Learning with Custom Curriculum

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    Flexible Schedule & Delivery

    Choose between virtual/offline with Weekend options

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


Understanding of big data concepts and technologies


Proficiency in data management and analytics


Hands-on experience in working with big data tools and techniques


Ability to analyze large datasets


Knowledge of data visualization techniques


Understanding of machine learning concepts

Training Options

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1-on-1 Training

USD 2500/ INR 200000
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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  • Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
  • Keep employees up-to-date with changing industry trends and advancements.
  • Adapt to new technologies & processes and increase efficiency and profitability.
  • Improve employee morale, job satisfaction, and retention rates.
  • Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
  • Obtain long-term organizational growth and success.

Course Reviews


  • What is Enterprise Big Data Analysis?
  • The Objective of Enterprise Big Data Analysis
  • The Data Analyst versus the Data Scientist
  • The Big Data Analysis Toolbox
  • Models, Algorithms and Intellectual Property

  • The Business objective
  • Introduction
  • Types of Business Objectives

  • Introduction
  • Raw versus Processed Data
  • Reading Local Data Sets
  • Reading Online Data Set
  • Reading Data Sets from Databases

  • Tidy Data
  • Data Inspection – Review your Data
  • Data Cleaning
  • Data Wrangling
  • Data and R Files for this Chapter

  • Introduction to Data Analysis
  • Exploratory Data Analysis
  • Statistical Inference
  • Correlation
  • Regression

  • K-Nearest Neighbour (K-NN algorithm)
  • Dimensions in the k-NN classifiers
  • Naïve Bayes
  • Naïve Bayes Classifier with multiple variables
  • Laplace Smoothing
  • Logistic Regression
  • Classification Trees
  • Building a Classification tree
  • Model Overfitting and Accuracy

  • Hierarchical Clustering
  • Variations in hierarchical clustering
  • Jaccard index
  • K-Means Clustering

  • Grubbs Outlier detection
  • K-NN Outlier Detection

  • Introduction to Reproducible Research
  • Codebooks
  • Data Visualisation
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