SYNOPSIS

For most organizations, big data is the reality of doing business. Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. Big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses. More accurate analyses may lead to more confident decision making. Better decisions can mean greater operational efficiencies, cost reductions and reduced risk. Imagine being able to analyze data to determine the root cause of failures or detect fraudulent behavior before it affects revenue. Implementing the right solutions to make the most of your big data – from data management to analytics – can be key to your business success.

As data floods your organization on a daily basis, the question is no longer "What is big data?". It’s "What can we do with the big data we have?". The answer, of course, is integral to the future of your business. With analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore options and make the best possible business decisions.

Analytics is the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions. With analytics, data scientists and others can analyze huge volumes of data that conventional analytics and business intelligence solutions can't touch. Consider this, it's possible that your organization could accumulate (if it hasn't already) billions of rows of data with hundreds of millions of data combinations in multiple data stores and abundant formats. High-performance analytics is necessary to process that much data in order to figure out what's important and what isn't. Enter big data analytics.

As engineers we play a key role in bridging the gap between theory and application. We apply mathematics and science with a dash of ingenuity in order to come up with practical solutions to business problems. With the advent of big data, having analytical knowledge will provide us an advantage in coming up with business solutions. The age of the analytical engineer is upon us.
Some questions on everyone’s mind are:

•    What is big data?
•    How do companies manage data?
•    How can analytics help?
•    Who is the analytical engineer?
•    How do we share analytical insights in order to accelerate business  
•    decisions?
•    How ready are companies to utilize analytics?
•    Where does Malaysia stand in terms of analytic readiness compared to  
•    the region?

Come join me for a personal view on the analytical engineer and their role.

BIODATA OFSPEAKER

Mark is the Head of Analytics within SAS’s Technology Centre of Excellence in Malaysia. Mark works with clients across industries to design, develop and implement analytics solutions within their organizations successfully. He has been with SAS since 2011.

Before joining SAS, Mark worked in IT for over ten years with various UK companies. He has worked for software development companies and an internet dating company. He has done a variety of roles from software engineering, systems administration, consulting, systems analysis, project management, product management and company management.

Mark holds two bachelor degrees from the University of Adelaide, Australia. The first with honours is in Electrical and Electronic Engineering and the second is in Applied Mathematics and Computer Science.

He did his PhD in Electrical Engineering at the University of Edinburgh, United Kingdom. He is also registered as a Chartered Engineer with the Engineering Council (UK) through the Institution of Engineering and Technology.