Big Data Business Consultancy

A Data Driven Organization, Digital Transformation

Implementation challenges remain the biggest hurdles towards the effective use of customer data analytics by organizations. While pilots deliver quick and measurable results, companies need to concurrently lay the foundations to effectively scale-up big data initiatives. The key lies in adopting a comprehensive approach, where pilots are backed by a well-defined data strategy and data governance model. The first step towards such an approach lies in altering traditional mindsets. Big data initiatives must be perceived differently from traditional IT programs. They must extend beyond the boundaries of the IT department and be embraced across functions as the core foundation for decision-making. Only then will banks be able to make the best use of their vast and growing repositories of customer data.

Lack of Strategic Focus: Big Data Viewed as Just Another ‘IT Project’ Big data requires new technologies and processes to store, organize, and retrieve large volumes of structured and unstructured data. Traditional data management approaches followed by banks do not meet big data requirements. For instance, traditional approaches hinge on a relational data model where relationships are created
inside the system and then analysed. However, with big data, it is difficult to establish formal relationships with the variety of unstructured data that comes through. Similarly, most traditional data management projects view data from a static and/or historic perspective. However, big data analytics is largely aimed to be used in a near real-time basis. While most IT projects are driven by the twin facets of stability and scale, big data demands discovery, ability to mine existing and new data, and agility. Consequently, by taking a traditional ITbased approach, organizations limit the potential of big data. In fact, an average company sees a return of just 55 cents on every dollar that it spends on big data.

We can help you with setting up Big Data Business Strategy, Data Assessment, Innovation program, Data Projects Management, Big Data Team establishment.