The first phase is just managing data, which sounds simple but can involve a series of stages of identification, storage, dissemination and use in the most comprehensive and optimal manner. Data sources now proliferate, both within the enterprise and externally, with the promise of 50 billion data generating objects connected to the Internet by 2020 and ETL (extract, transform, and load) and IoT (Internet of Things) tools available in abundance. There is adequate research and focus by vendors as well as user enterprises and increasing maturity in data organisation, storage, migration, consolidation, federation and virtualisation. With intelligent metadata management, organisations are able to fathom the use of the terabytes of data that are internally and externally buffeting them and plan the organisation of data warehouses and data lakes that make master data management a reality. Considerations of data quality and governance in the process of enterprise data integration and due attention to data privacy and security with the conscious application of statistical and modelling techniques available in data science have played a big role in this evolution.
The second phase is one which curiously enough is the most evolved in most organisations, that of business intelligence. Each of the top hundred organisations in the IT and business process management industry in India have built a substantial business intelligence practice either in consulting or in the implementation of multiple vendor tools. Many of the full service focused data and analytics firms like Systech, Bridgei2i and Tiger Analytics started their journey in this area and their clients have evolved with them through this phase to an expansion of their data sources and progress into the realm of analytics. A typical comprehensive business analytics execution would see the identification and implementation of technologies and tools that are powerful and agile and serve the purpose of consolidating processes and work streams and providing an integrated environment that caters to evolving organisational demands. These provide standardised analytics and dashboards to support business key performance indicators which lead to better coordination and collaboration between teams in the organisation and enable the proactive driving of functional and organisation-wide goal achievement.
The third milestone is the move towards maturity in handling data and building a true environment of advanced analytics in a firm. If oil was the key resource of nations in a previous era, data is surely the most precious resource this millennium, and drilling for data through new technology innovations like artificial intelligence, machine learning and cognitive computing will pave the road to success for organisations which are ready and willing to make the investments necessary to create a climate and culture of managing data and managing with data. Advanced analytics will see managers moving from descriptive and post-mortem analysis of what happened to predictive analytics that will model customer behaviour and anticipate demand and buying behaviour. Finally, prescriptive analytics which will recommend actions to managers and take the guesswork out of decision-making will greatly improve the quality of business outcomes and provide the true competitive edge to data-driven organisations.
The entire buzz in the country across most industry sectors today is the worry about job losses and the creation of future jobs. Big data and analytics is one area which has the potential to create multiple employment and entrepreneurship opportunities for intelligent youth and reskilled career seekers. From Mckinsey to Deloitte to WNS to specialist firms like Systech, we are seeing real focus on enabling industry and individuals to master data and analytics. The future is going to be an interesting place! The author is chairman of 5F World, Pune City Connect, and Social Venture Partners, India
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