About this Training Course

The goal of data analytics is to gain understanding and intelligence from data which can be used to make improvements or changes in business. Analytics often involves studying past historical data for hidden valuable trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario.

The aim of this 2 full-day course is to enable participants to understand the process behind Data Analytics or Data Science, equip them to find opportunities from their data to make better business decisions as well as apply the insights obtained from the data to identify potential gaps and develop improvements needed in the business. The applications are to help participants understand better where the possible use of data analytics can be applied in their respective field of work or discipline.

This course can also be offered through Virtual Instructor Led Training (VILT) format.

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TRAINING OBJECTIVES

By the end of this course, participants will be able to:

Describe the definition of Data Analytics, Data Science, Machine Learning & Artificial intelligence and the main difference between them
Describe the use and purpose of data analytics and data science
Describe the strengths and weakness of data analytics and visualization in a business setting
Explain the importance of visualization, the first step to gain value from Data Analytics and what benefits visualization provides
Propose how data visualization and its tools can be used to identify potential gaps and develop improvements in the business
Describe how data analytics and visualisation can enhance decision making
Walkthrough the steps on how to start building data analytics capabilities, namely data governance and visualization.
Explain the technology buzzwords around Data Science, Artificial Intelligence and Big Data technology for better communication/discussion with technology vendors

TARGET AUDIENCE

This course will benefit:

Managers
Analysts
Technologists
Technology leaders
Oil & Gas professionals who would like to find out more on what data analytics has to offer and how they can gain further insights from their existing data.

COURSE LEVEL

Basic
Foundation

TRAINING METHODS

System requirements for this course:

The system requirements are as follows:

Excel 2013
Windows 7 Enterprise Above
8GB Memory RAM, preferably 16 RAM

TRAINER

Your expert course leader is an experienced data scientist, consultant and seasoned trainer with over 1,600 man-hours of training completed to date. He currently conducts training at the SAS Institute, and is also the adjunct senior faculty with SUSS and SCALE, NUS. He was a guest lecturer at NUS-ISS before and previously held an adjunct position in School of Information Systems, SMU. He is currently the mentor to the trainees accepted into the IMDA-SAS BIA Programme.

Prior to this, he was the Analytics Practicum Manager of the Master of IT in Business (Analytics) Singapore Management University, School of Information Systems. He managed the industrial relationships through projects and attachments. He often advised companies on the type of Analytics projects they can do with their data and is a co-supervisor for many MITB students on their Analytics Capstone Projects.

Through his career, he has gathered much experience on statistical modeling, from working in the industry, supervising MITB (Analytics) students and doing education research. His Analytics experience range from a wide variety of business functions and industries, gathered from consulting with companies from a wide variety of industries.

His strong passion in Analytics/Data Science can be seen through his involvement in Analytics interest groups, being a Co-founder of DataScience.Sg, former Working Committee Chairman of SAS User Group Singapore and Data Ambassador for one of DataKind SG project. He also reads widely on the different topics related to Data Science and Artificial Intelligence, keeping himself up-to-date with their developments.

His research interest lies in how Data Science can help organisations and businesses be more efficient and effective, and how organisations can build in-house data science capabilities successfully. He holds an MBA from the University of Adelaide. He obtained his Bachelor Degree in Economics from the National University of Singapore, with a minor in Computational Finance.

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POST TRAINING COACHING SUPPORT (OPTIONAL)

To further optimise your learning experience from our courses, we also offer individualized “One to One” coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.
Request for further information post training support and fees applicable

Introduction to Data Analytics & Visualization