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.

Duration: 3 hours
Fee: USD15
Start Date: Flexible

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

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;

Understand the emergence and importance of Big Data Analytics
Understand the tools, technologies, architectures and framework that are used in Big Data Analytics
Apply new understanding in the planning stage of Big Data projects
Ability to determine the viability of any Big Data projects
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.

Hear from Our Alumni

The training has benefited me a lot with the skills required to be a data analyst and has upskilled me in data analysis. What I like about the program is where real life problems in the office is used as the materials during the trainings which provides more understanding of the topics. Eventually, it has broaden up my market in the career development.

The program started by setting an expectation on Day 1, that it is not a Read-And-Pass syllabus. The beauty of this program is that it requires the trainees to get their hands dirty and do the actual work throughout the course. It is indeed very different from a lot of programs in the market which just produces a certificate in the end without the trainee actually able to do some real stuff. The course is definitely benefiting anyone who really want to do Machine Learning and Data Science, by creating talents who are able to connect human thought with the machine algorithm, being the bridge within the corporate, into the digital worlds.

The training was beneficial as it trains myself to think from another perspective - one that may not be new, but wasn't practiced as often as I'd like. It was fun and interactive thanks to the facilitator, Jay, too. He was very helpful to answer any questions the attendees have. Believe that this training gives the attendees an extra edge by giving them the knowledge and perspective on how to better utilize data to what they want/need to do - for the organization, the business, and even for personal use, of which I believe will bring myself further in my career.

The training has been an eye opener for me. As someone who is not of programming background, it introduces me to the possibilities of what data can do. It has also helped me bridge the difference in thinking between the Business Team and the Data Science Team. Had a great time learning!

This training enhance on my skill of analyzing of using another tools of programming instead of excel and how to model and visualized our data in a better way instead of our traditional way. Especially when involve with a large scale of data. If using excel, there will a lot of time consuming there instead of R. For me, in market nowadays of big data, this course will brings more value and create another point of view on how to visualize our data especially in making any decision. And of course will enhance our career development.

Register Interest for Group or Organisation Enrolment

Big Data Analytics 101

Big Data Analytics 101

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

Learning outcome: