Big Data Analytics 101

Track: Enterprise Data Practitioner (EDP)
This course provides a comprehensive introductory overview of the concept of Big Data and its technologies, architectures and management. Participants can reap the benefits of this course when planning Big Data projects and understanding the technology involved using different types of analytics such as Descriptive Analytics, Predictive Analytics and Machine Learning.

Navigate the Big Data landscape by mastering the fundamentals of Big Data Analytics and its various business applications

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This course provides a comprehensive introductory overview of the concept of Big Data and its technologies, architectures and management. Participants can reap the benefits of this course when planning Big Data projects and understanding the technology involved using different types of analytics such as descriptive analytics, predictive analytics and machine learning.

In-depth review will be given to actual use cases of five large international organizations in how analytics were used to provide insights from various data sources. These insights can solve business problems, reduce costs, enhance customer loyalty and experience and gaining competitive advantage against their competitors.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;
  1. Understand the emergence and importance of Big Data Analytics
  2. Understand the tools, technologies, architectures and framework that are used in Big Data Analytics
  3. Apply new understanding in the planning stage of Big Data projects
  4. Ability to determine the viability of any Big Data projects
  5. Gain insight into how large organizations have solved business problems, reduce costs, enhance customer loyalty & experience, effectively gaining competitive advantage against their competitors, using Big Data Analytics

Who should attend:

Managers and Decision makers looking to understand how Data will affect their roles, companies, and strategies

3 hours of in depth learning

Structured online learning.

Pre-requisite:
N/A

CADS Certification​

Earn certification upon completion.

Minimum Qualification:
N/A

Training Track

Enterprise Data Practitioner (EDP)

Big Data Analytics 101 is one of the modules under our Enterprise Data Practitioner (EDP) programme. EDP is an eight-day training program that super- charges Business Intelligence analysts with new skills to analyse and communicate insights effectively.

Details of Subject

Module Description
  • This training course starts with a very brief introductory chapter which will help us to set the scene for our discussion throughout the course. So, we will learn about the emergence and importance of big data and big data analytics, the datafication of the world, the importance of public cloud and how data silos can hinder our big data projects.
  • The second chapter presents big data technologies. To help you understand better, we will discuss and present a few big data architecture frameworks.  These are extremely helpful during the planning stage of big data projects because they identify all business and technical requirements that determine the viability of any big data project. In addition, we will discuss the various big data technologies that have been developed to materialize the big data project including the importance of public cloud.
  • Big data management deals with tools and technologies employed by organizations to handle, organize or utilize large volumes of structured and unstructured data efficiently. At the top of big data management is Hadoop with each ecosystem of applications which help organizations to deal with any big data problem. In this chapter will also cover Hadoop technologies for storing, processing and querying efficiently data.
  • The goal of a data journey is to produce insights from data, and for this purpose we need suitable big data analytics. So in the fourth chapter we will cover everything you should know about big data analytics, we will discuss about the different types of analytics such as descriptive and predictive, we will talk about simple and advanced analytics, like for instance text analytics that can be applied on unstructured data. the chapter will conclude with a brief presentation of machine learning frameworks.
  • The last chapter presents the use cases of five large organisations namely AMEX, UPS, Delta airlines, Walmart and Alibaba; and how they managed by producing insights from internal and external data to solve business problems, reduce costs, enhance customer loyalty & experience, effectively gaining competitive advantage against their competitors.

Lead Instructor

Jan Sauer
Jan Sauer was a biostatistician in the field of deep learning and image/pattern recognition. He has a master’s degree in physics and have extensive experience as a software developer. Throughout his career, he has been involved in different areas of data science, ranging from automated data collection and data analysis, data pipeline and database design, and advanced machine learning where he uses Tensorflow extensively in image processing.

CADS Certification

EDP CADS Certified Enterprise Data Practitioner

Each exam in this program certifies job-ready knowledge and skill. Those that pass all are recognized as being able to distill an insight from data and communicate its value to a decision maker. Enter the world of Data Professionals.

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Big Data Analytics 101