Certified Big Data Science Professional
 /  Certified Big Data Science Professional

The Big Data Science Professional track is comprised of BDSCP Modules 1, 2, and 3, the outlines for which are provided in the upcoming pages. Depending on the exam format chosen, attaining the Big Data Science Professional certification can require passing a single exam or multiple exams. Upon achieving the accreditation, certification holders receive a formal digital certificate and an Acclaim/Credly digital badge with an account that supports the online verification of certification status.

Module 1: Fundamental Big Data
This module provides a high-level overview of essential Big Data topic areas. A basic understanding of Big Data from business and technology perspectives is provided, along with an overview of common benefits, challenges, and adoption issues. The course content is divided into a series of modular sections, each of which is accompanied by one or more hands-on exercises.

The following primary topics are covered:
– Understanding Big Data
– Fundamental Terminology & Concepts
– Big Data Business & Technology Drivers
– Traditional Enterprise & Technologies Related to Big Data
– Characteristics of Data in Big Data Environments
– Dataset Types in Big Data Environments
– Fundamental Analysis and Analytics
– Machine Learning Types
– Business Intelligence & Big Data
– Data Visualization & Big Data
– Big Data Adoption & Planning Considerations

Module 2: Big Data Analysis & Technology Concepts
This module explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments. The course content does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions, as well as a high-level understanding of the back-end components that enable these functions.

The following primary topics are covered:
– Big Data Analysis Lifecycle (from business case evaluation to data analysis and visualization)
– A/B Testing, Correlation
– Regression, Heat Maps
– Time Series Analysis
– Traditional Enterprise
– Network Analysis
– Spatial Data Analysis
– Classification, Clustering
– Filtering (including collaborative filtering & content-based filtering)
– Sentiment Analysis, Text Analytics
– Processing Workloads, Clusters
– Cloud Computing & Big Data
– Foundational Big Data Technology Mechanisms

Module 3: Big Data Analysis & Technology Lab
As a hands-on lab, this module provides a set of detailed exercises that require participants to solve a number of inter-related problems, with the goal of fostering a comprehensive understanding of how Big Data environments work from both front and back-ends, and how they are used to solve real-world analysis and analytics problems

This course is targeted for the following audience:

• Performance improvement and strategy specialists

• BI and data warehouse architects

• Designers and developers

• BI project managers

• Business and data analysts

• Data quality & data governance professionals

To achieve this certification, Exam B90.BSP must be completed with a passing grade.
For more information on exam format / preparation / policies, visit

  • 24 – 26 Feb 2020
  • 6 – 8 Apr 2020
  • 1 – 3 Jun 2020
  • 12 – 14 Aug 2020
  • 12 – 14 Oct 2020
  • 30 Sep – 2 Dec 2020

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Course Fee $3,500.00
Course Fee after GST $3,745.00
Certification Body
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