Digitalization of the economy has resulted in data being the world’s newest resource for competitive advantage. Every digital process, or social media ex­change gives rise to data. Big Data is arriving from multiple sources at an alarming volume at a very high velocity and in a variety of forms. Making value out of these enormous data is the biggest challenge that organizations face today. Big Data has frequently been defined by the four Vs: Volume, Velocity, Variety and Value.

Big data is changing the way we do business, it is shifting deci­sion making from a select few to a large mass of individuals who are all equipped with information to make better decisions at all levels.

Organizations need to develop a clear strategy around Analyt­ics and how it can align with their overall business strategy, instead of piecemeal big data projects arising out of individual group impera­tives. Below are a few things to remember before embarking on a Big Data journey:

• Never start with the technology but with the business need

• Start by identifying some sim­ple use cases which can be eas­ily understood from a business relevance perspective

• While the overall strategy should be guiding the initiative, it’s better to start small with the end goal in mind, with open source products, and a small set of people. A pilot or POC with concept and underlying technology would be a good idea.

• Change management and gen­eral stakeholder buy-in is key in any newer initiative and Big Data is no exception. Sincere attempt should be made to get stakeholder buy-in. Hence, the need for simple and rel­evant use cases to start with. Analyt­ics is a team sport.

• Identify the right set of people to be part of the initiative. These should be run by people who under­stand the business and knows the business outcome expected from the Big Data initiative in general and the use case in particular and sup­plemented by Business Analysts, Data Scientists, Graphic Designers, Analytics Architect, Data Engineer, Graphic Designer. Often these skillsets are hard to get and hiring from the market might become chal­lenging. Attempts should be made to reuse, cross train and retrain existing skillsets.

Incubating big data projects with true values is a challenge in itself for the industry. Deep understand­ing of structured data, augmented with relevant unstructured data, is not an easy task. From ingestion of various data sources to meaningful business intelligence dashboard is a long journey which will require a good strategy and careful planning.

In agile way, the Big Data Analytics team and the business users work in a series of iterations right from scope definition, requirements gathering, data extrac­tion, data exploration, data analytics phases, to delivery. Working in iterations and in close collaboration with the user ensures the delivery of a meaningful business out­come, which the business users can relate to, because they have been involved in the full lifecycle.

Another challenge is with respect to technology & people. The landscape is changing with a rapid pace and newer technologies are being added before the previous one has proven it’s worth. Finding the right mix of tech­nology and a matching skillset is a real challenge.

Explosion of unstructured data from social media, messaging, connected devices (IoT) etc. will always have trouble fitting in the traditional data management scheme. It’s not just augmenting the database with a field or two every time there is a need. The data strategy of tomorrow has to be scalable, performance centric, se­cure, highly available, fast, and logically useable. Cloud is a promising answer to all these challenges. With prom­ise of ‘anything as service’ cloud has potential to solve many Infrastructure issues arising from digital and big data transformation. "Analytics is addictive, this posi­tive addiction quickly turns sour if your infrastructure can't keep up”- Matt Wood, AWS Data Science Chief.

Benefits Brought About by Big Data in Customer Centricity

The rise of social media has already proven that custom­er is at the centre and every strategy revolves (or will revolve) around her. With better persona of customer the companies are in a better position to reachout and interact with the customers. Structured data within an organization and unstructured data together can release immense business intelligence which is/will transform how companies do business today. Many start-ups, in­sure-tecs and fin-techs are a result of this evolution. Tra­ditional way of doing business is no more viable. And meaningful outcome based options are emerging more and more – re pay-as-you-use, pay-how-use etc.

The most heartening evolution will be that find­ing the right skill will become easier as more and more young professionals are focusing on these skillsets and these areas are making entry into the educational cur­riculum as well.