Big Data and its Management Process Training Course


Objective : This training course aims at helping attendees understand why Big Data is changing our lives and how it is altering the way businesses see us as consumers. Indeed, users of big data in businesses find that big data unleashes a wealth of information and insights which translate to higher profits, reduced costs, and less risk. However, the downside was frustration sometimes when putting too much emphasis on individual technologies and not enough focus on the pillars of big data management.

Attendees will learn during this course how to manage the big data using its three pillars of data integration, data governance and data security in order to turn big data into real business value. Different exercices conducted on a case study of customer management will help attendees to better understand the underlying processes.

Course Outline


  • Introducing Big Data : Evolutions over the years
  • The Characteristics of Big Data
  • Identifying Different Sources of Big Data
  • How Big Data Is Used in Business ?


The challenges of Big Data

  • Identifying the Challenges of Big Data : Current and Emerging Challenges
  • Why Businesses are Struggling with Big Data ?
  • State of Big Data Projects
  • Understanding the layers of big data architecture
  • The Big Data Management – Introduction
  • Defining capabilities of big data management
  • Overcoming obstacles with big data management


Building Blocks of an Efficient Big Data Management

  • The Big Data Laboratory versus Big Data Factory
  • Understanding the Three Pillars of Data Management
  • Data Integration
  • Data Governance
  • Data Security
  • Understanding functions of Big Data Management Processes
  • Competencies of the Big Data Team


Implementing Big Data Management

  • Implementing the Big Data Management
  • Identifying Big Data Tools
  • Leveraging the Right Tools
  • What are Commercial Tools built atop Open Source Projects ?
  • How to combine Integration, Governance and Security ?


Conclusion – Tips for Succeeding with Big Data Management

  • Use Cases to provide Business Value
  • Identifying Data Quality Issues Early
  • Aligning Your Vocabulary
  • Centralizing and Automating your Data Management
  • Leveraging Data Lakes
  • Collaborative Methods for Data Governance
  • Using a 360-Degree View on your Data and Relationships
  • How to work with Vendors to Accelerate Your Deployments ?

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