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Enterprise Big Data Analyst

Learn the in-depth analysis skills to become a Big Data analyst

Enterprise Big Data Analyst

RM4,000.00RM5,680.00

The Enterprise Big Data Analyst qualification is a practitioner course for all professionals that aim to an in-depth understanding of Big Data analysis techniques and models, core data analysis processes steps, and best practices to retrieve value from data.

Delivery format: Classroom, Virtual-Led & Self-Paced Online
Certification: Enterprise Big Data Analyst (APMG International)

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Description

What benefits can your organization achieve with Big Data? How to spot patterns in large quantities of enterprise data to improve performance and find underlying pattern that can benefit the organization? How can enterprises obtain a competitive advantage with Big Data? The Enterprise Big Data Analyst (EBDA) course discusses the theoretical concepts of Big Data and subsequently applies this knowledge to a real-world case study.

The Big Data Framework provides a holistic and compressive approach for enterprises that aim to leverage the value of data in their organizations. The framework covers all the essential aspects of Big Data that are necessary to understand and analyse massive quantities of data. The Enterprise Big Data Analyst course is the second level of the Big Data Framework course curriculum and certification program, that is globally recognized and accredited by APMG-International. The curriculum provides a vendor-neutral and objective understanding of Big Data architectures, technologies and processes.

The Enterprise Big Data Analyst qualification is a practitioner course for all professionals that aim to an in-depth understanding of Big Data analysis techniques and models, core data analysis processes steps, and best practices to retrieve value from data.

The course will provide an overview of statistical and machine learning models, which are illustrated in the R programming language. This certification will not test programming skills. The emphasis is on the correct application of the theoretical models, however participants are required to understand the output of programming languages in order to draw conclusions from the results of analysis.

Learning Objectives

The Enterprise Big Data Analyst (EBDA®) qualification shows that candidates possess the skill to analyze Big Data and are able to understand key data analysis concepts and techniques. Moreover, an Enterprise Big Data Analyst is able to correctly interpret data and draw conclusions. The Enterprise Big Data Analyst qualification builds upon the first level of the Big Data Framework qualification scheme (EBDP) in which fundamental knowledge and elementary concepts related to Big Data were covered. The Enterprise Big Data Professional certificate is therefore a pre-requisite to this certification.

A certified Enterprise Big Data Analyst has proficiency in key models and concepts that are required to analyze data on a day-to-day basis. (S)he understands the theoretical difference between different statistical and machine learning approaches and is able to explain the difference between models and select and apply the appropriate model when confronted with a particular business problem.

Certified candidates should be able to deduce value out of Big Data sets but may not be sufficiently skilled to do this autonomously for all types of problems. Their Big Data experience, complexity of the problem, and the support provided in their work environment would all be factors that impact what the certified candidate can achieve.

Specifically, (s)he should be able to demonstrate this understanding by being able to:

  • Understand and explain the data analysis process, including all relevant steps included in enterprise big data analysis.
  • Understand the difference and structure of common data sources (local, online and database connections) and the way these sources should be imported in order to perform data analysis.
  • Apply and utilize fundamental data cleaning operations and the differences between different data cleaning techniques.
  • Apply and utilize fundamental data wrangling operations and the differences between different data wrangling techniques.
  • Understand and apply exploratory data analysis techniques that are required for model building, model validation and initial visualizations.
  • Understand and apply the core concepts of statistical inference, including techniques required for hypothesis testing.
  • Formulate and interpret predictive models based on statistical correlation and regression functions, including simple linear regression.
  • Formulate and interpret machine learning models for classification, including K-Nearest Neighbour, Naïve Bayes, Logistic Regression and Classification Trees.
  • Formulate and interpret machine learning models for clustering, including the Hierarchical clustering and K-means clustering techniques.
  • Formulate and interpret outlier detection models, including Grubbs Outlier detection and K-NN Outlier Detection.

Understand and apply the core data presentation, techniques including codebooks and visualizations to present the findings of their analysis.

Target Audience

This qualification is aimed at individuals who are involved in enterprise Big Data analysis, who require a working knowledge of the principles behind Big Data analysis techniques, and who need to know the different statistical and machine learning techniques to make the right decisions. The target audience of the Enterprise Big Data Analyst qualification therefore includes the following roles:

  • Data Analysts
  • Business Analysts
  • Business Data Analysts
  • Systems Analysts
  • Data Management Analysts
  • Business Analytics Consultants
  • Data Scientists
  • Data Modellers

Exam Structure

The Enterprise Big Data Analyst certification has the following structure:

  • Objective testing based on a case study scenario
  • 4 questions of 20 marks each
  • 53 marks required to pass (out of 80 available) – 65%
  • 2.5 hours duration
  • Restricted open book – The EBDA Guide may be used in the exam

Downloads

Download the official syllabus:

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Event Details

Cybiant offer the following learning options for this course:

Self-Paced-Online Learning - 3 months access
If your a choosing the Self-Paced-Online (SPO) learning option, you will complete the course on your own time, in your own pace. Cybiant will provide you with access to an online learning environment where you can watch videos, and practice with sample questions. The SPO option provides access for 3 months, and includes the official exam.

Virtual Training - 2x2hours per day
If you are choosing the virtual training learning option, you will participate in a live course by a Cybiant instructor, which is delivered 100% online. You will receive meeting invitations to participate in the live lectures through the Zoom platform. There will be 2 x 2-hour sessions per day, so this option does provide you with flexibility to plan some other work. All sessions are recorded, in case you miss any of the session. All virtual training courses include the official examination, which will be taken online on the last day of class.

Classroom Training - full day
If you are choosing the classroom training option, you will participate in this training in a live class in a 5-star hotel. This training option provides you with the opportunity to discuss topics in detail with other course participants, and learn from their experience. You will be trained by one of our Cybiant experts, and will complete the exam on the last day of class. Training is conducted daily, based on the following time schedule:

Start time: 09:00 UTC+08

End time: 17:00 UTC+08

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