EDITOR ’ S QUESTION
ABED HAMANDI , SENIOR DIRECTOR – PROFESSIONAL SERVICES , SOUTH & EAST EUROPE , CENTRAL ASIA & MEA
At a high level , a Big Data strategy is a plan designed to help organisations oversee and improve the way they acquire , store , manage , share and use data within and outside in decision support . In practice , it can help companies do all sorts of things – determining root causes of failures , issues and defects in near-real time and in real time where necessary . For example , in Retail business , generating coupons at the point of sale based on the customer ’ s buying habits and , in banking and financial sector , recalculating entire risk portfolios in minutes and detecting fraudulent activities before such activities affect the organisation . A Big Data strategy sets the stage for business success amid an abundance of data .
There ’ s no single blueprint for beginning a data analytics project – never mind ensuring a successful one . There are , however a number of questions that help individuals and organisations frame their data analytics projects in instructive ways . Start by asking what business problem you are trying to solve . Then , look at what types and sources of data are available to you , including both internal and existing resources . Assess the quality of data available . Before data can be used , it must be accessed , categorised and cleansed .
Once that ’ s done , Big Data can be analysed for insights that lead to better decisions and strategic business moves . One of the most significant benefits of Big Data tools and solution including SAS is that these offer cost advantages to businesses when it comes to storing , processing , and analysing large amounts of data . Not just that , Big Data tools can also identify efficient and cost-savvy ways of doing business .
Given the explosion of data CIOs and IT leaders are struggling to store and process Big Data and a lot has been spoken about this explosion of data in the world .
As we generate the zettabytes of data , Big Data and analytics have cemented their place in the enterprise .
The CIO has to make the right technology choices that enable business users to become more data driven . Today , CIO ’ s and IT head ’ s role has evolved much more and become more centred around business transformation . The CIO is almost like the change agent who ensures that all IT functions that support the business work smoothly to effect transformational change .
To implement transformational change , you need information and intelligence – something that you can get only with data and analytics .
The objective of Big Data and analytics is also to enable collaboration to drive transformation and lead to successful business outcomes . When designing Big Data and analytics strategies , a CIO ’ s main mission is to promote collaboration between technology teams and the business while remaining compliant with all regulatory requirements .
The CIO ’ s role has crossed a long journey from being the ones who deployed technology into businesses to becoming technology integrators and then moving on to becoming the ones who design the architectures of the business , CIO ’ s are now the main players of value creation .
Since the CIO ’ s role has become that of the transformation enabler , he or she has to ensure that the technology implementations close the gap between business priorities and outcomes . For this , they almost have to constantly evaluate and answer which comes first – the business opportunity ( chicken ), or the technology opportunity ( egg ) and then decide on a platform that acts as a universal translator that supports both .
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