Big data, undoubtedly, one of the most trending buzzwords in the tech word in the 21^st century. For, it is not just the large volumes of data nor the pace in which it is growing made it trending, but the strategic value that can be derived out of it for the growth of organizations made it so.

While the definition of Big Data has become clearer in terms of what it is, the adoption and implementation of Big Data is still in earlier stage. According to a recent study conducted by Gartner, only 13% of the respondents have deployed Big Data solutions in their organizations. So why is this slow adoption rate? What are the major concerns?

Here are our views on challenges/apprehensions enterprises have in implementing Big Data solutions.

Deriving value: How to decide the value for Big Data? How to estimate ROI? There are the burning questions in the minds of CIOs, IT heads. It is clear from the same study by Gartner, where 31% of respondents have mentioned that “Determining value of Big Data adoption” is their major challenge.

Where and how to start?Given that most of the organizations mayhave some IT infrastructure already existing and significant investments might have been made, defining the road-map for enterprise wide Big Data implementation and the priority of implementation with proof of concept is a key.

Risk and governance:This is another area of concern enterprises see, failing to keep track of endless amounts of data may pose potential legal and compliance risks.

Integration with existing infrastructure:Compatibility of the new big data technologies with the existing IT eco system, total cost involved in integration are other concerns enterprises have; over 14% of the respondents have mentioned it in the same Gartner report.

Implementation:It is known fact that Big Data technologies are complex in nature and often implementing the same requires new skills. Also, Big Data projects are iterative and exploratory, hence often requires different project management and life-cycle approach.

Big Leap solution, aimed at helping organizations to take competitive edge over their competitors using Big Data, addresses these challenges by enabling customers with:

• Quicker value realizationwith up to 30% increase in revenue and/or savings
• Greater control on Data with up to 5x improvement in agility of the data management platform
• Easy integration with up to 40% reduction in Total Cost of Ownership

Now let us look at the different solutions which customers consider as a best bet for Big Data when driven from IT.

Hybrid EDW:As the data volume almost doubling every year, cost of infrastructure keeps growing at the exponential pace, also analytic and reporting queries often scan large volume of data. So, need of the hour is to have a system that shares the burden of data for easy data management and quicker analytics.

A Hybrid EDW pattern enables data storage, data processing and analytical workloads to be shared between the traditional data warehouse and the Big Data technologies thereby helping organizations in Reduced TCO, improved operational efficiency and enhanced effectiveness of Analytics

Data Hub:Fragmentation of enterprise data across transactional systems and inconsistency in data definition effectively leads to lack of agility in Analytics.

Data Hub offers enterprises an agile data management platform with robust data governance, easy integration options and a meta-data driven data processing framework thereby enabling organizations with agility in decision making, scalability to accommodate ever-growing data and availability of enterprise data for decision making across the organization

Accessible Archive:As modern businesses compete with each other on analytics, data has come to be treated as acorporate asset. Consequently, there is now an unprecedented drive to collect and preserve hugevolumes of data. The constantly evolving regulatory landscape also necessitates retention of granular historical data so that the enterprise can respond with agility to compliance and audit requirements.

Accessible Archive solution offers enterprises a highly scalable, cost-effective, reliable,secure, seamless and easy-to-access data storage solution

Modern data platform: When data is getting generated across different transactional systems, the ever-growing data compounds the woes in data management and the turnaround time for data delivery to analytics is high.

Big Data solution helps enterprises to bring data to a consolidated, robust platform which not only improves performance but also delivers higher information insights at a lower cost.

Contact us to know more about our Big Data Analytics offerings