Name: Enterprise Big Data Analyst E-learning
SKU: 29069
Availability: InStock

Course Overview

The Enterprise Big Data Analyst (EBDA®) e-learning course equips professionals with the skills to analyze Big Data and generate actionable insights. The program covers statistical and machine learning methods, guiding participants to present results in a structured, reproducible way.

Through interactive modules, participants explore key techniques for exploratory data analysis, predictive modeling, and machine learning, including classification and clustering, with practical application using Python. The course emphasizes correct model application and interpretation, enabling informed decision-making without requiring extensive programming expertise.

As part of DASCIN‘s globally accredited Big Data Framework curriculum by APMG-International, the course provides a vendor-neutral perspective on Big Data architectures, technologies, and processes. Learners gain a strong theoretical foundation while connecting concepts to practical scenarios.

By completing this e-learning program, participants enhance their ability to design reproducible analyses, evaluate model performance, and communicate insights clearly. The course prepares professionals for the Enterprise Big Data Analyst certification exam, empowering them to support data-driven decisions and deliver value across organizational contexts.

Learning Objectives

The Enterprise Big Data Analyst (EBDA®) qualification demonstrates that candidates can analyze Big Data and understand key data analysis concepts and techniques. A certified Enterprise Big Data Analyst has proficiency in essential models and concepts for day-to-day data analysis. They understand theoretical differences between statistical and machine learning approaches, can explain model distinctions, and select the appropriate model for specific business problems.

Certified candidates can extract value from Big Data sets, though their autonomy may depend on experience, problem complexity, and available support.

By the end of this course, participants will be able to:

Understand and explain the enterprise data analysis process and its key steps.
Recognize different data sources (local, online, databases) and import them for analysis.
Apply fundamental data cleaning and wrangling operations, understanding differences between techniques.
Utilize exploratory data analysis for model building, validation, and initial visualization.
Apply core statistical inference concepts, including hypothesis testing.
Formulate and interpret predictive models, including simple linear regression.
Apply machine learning models for classification (K-Nearest Neighbour, Naïve Bayes, Logistic Regression, Classification Trees).
Apply machine learning models for clustering (Hierarchical and K-means).
Formulate and interpret outlier detection models (Grubbs and K-NN).
Use core data presentation techniques, including codebooks and visualizations, to communicate findings.

Target Audience

This qualification targets professionals involved in enterprise Big Data analysis who need practical knowledge of Big Data principles, statistical methods, and machine learning techniques to make informed decisions, including the following roles: