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The Enterprise Big Data Analyst (EBDA) course discusses advanced techniques for the analysis of Big Data. In this course, you will learn how you can obtain value from data through statistical and machine learning techniques and how this analysis should be presented in a reproductible manner.

The Enterprise Big Data Analyst course discusses advanced data analysis techniques in the context of Big Data. Working is a structure and reproductible manner, this course provides an overview of the most common algorithms for exploratory data analysis, statistical inference, predictive modelling and machine learning techniques (classification and clustering). Course participants will learn the underlying theory of the different algorithms, and how each algorithm can be applied in practice in the R programming language.

The Enterprise Big Data Analyst course is the second level of the Big Data Framework course curriculum and certification program, that is globally 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 data 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.
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What You'll Learn

  • 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.

Who Should Attend

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
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Prerequisites

The pre-requisites for taking the Enterprise Big Data Analyst examination is passing the Enterprise Big Data Professional certificate.

Learning Journey

Coming Soon...

Introduction to Big Data Analysis
  • 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 Data Analysis Process
  • The Business objective
  • Introduction
  • Types of Business Objectives

Data Ingestion – Importing and Reading Data
  • Introduction
  • Raw versus Processed Data
  • Reading Local Data Sets
  • Reading Online Data Set
  • Reading Data Sets from Databases

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

Data Analysis – Model Building
  • Introduction to Data Analysis
  • Exploratory Data Analysis
  • Statistical Inference
  • Correlation
  • Regression

Module 6: Classification Techniques
  • 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

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

Outlier Detection
  • Grubbs Outlier detection
  • K-NN Outlier Detection

Data Presentation
  • Introduction to Reproducible Research
  • Codebooks
  • Data Visualisation

Frequently Asked Questions (FAQs)

  • Why get APMG International certified?

    APMG International certifications validate your expertise in a wide range of best practice methodologies, including project management, cybersecurity, IT service management, and more.

    These globally recognized credentials demonstrate your commitment to professional development and can open doors to new career opportunities.

  • What to expect for the examination?

    The format and content of APMG International exams vary depending on the specific certification.

    Exams may include multiple-choice questions, scenario-based questions, or practical exercises.

    Note: Certification requirements and policies may be updated by APMG International from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is APMG International certification valid for?

    The validity period for APMG International certifications varies depending on the specific certification.

    Some certifications, like the Foundation level, do not expire, while others, like the Practitioner and Master levels, may require re-registration or recertification after a certain period.

    Note: Certification requirements and policies may be updated by APMG International from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 16 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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