Turning Big Data into Big outcomes
Knowing more about your business and knowing it faster than others is the best way to power innovation & stay ahead of competition. We are living in an era of unmatched digital innovation with rapidly expanding horizons. Big Data Analytics is shaping up as the critical frontier for organizations who want to use [Big] Data to excel on their performance and not use the data to just control the performance. Often more than 70% of the data is referred as Dark Data, though it exists with a purpose in the enterprise, is not used. Big Data Analytics with Data Science is becoming the cornerstone to make sense of all the relevant data within the data landscape and expand the power of information and real time and predictive actionable insights.
Big Data, OT-IT convergence, Internet of Things, Cloud, Mobility, social networks at an enterprise and a consumer level – all are forming a nexus that is creating new opportunities for organizations. However, in order to leverage them, these organizations need to transform their BI & Analytics landscape. Merely adding “Big Data” as one more component to the existing landscape without focusing on the overall vision, strategy and technology roadmap is likely to yield myopic consequences. On the other hand, sound principles have to be applied to ensure minimal incremental investments and maximize re-use of existing resources. To achieve competitive advantage, organizational leaders and CXOs need to be able to rely on Single Source of Truth through Logical Data Warehouse (LDW) across the vale continuum irrespective of the type and underlying source of data. Business use cases should drive the technology adoption creating value through rapid ROI and lower TCO.
Adopting Big Data Analytics is seen as a tall order in many organizations and it is not just because of the Big Data itself, but the information maturity and ability to strategize and implement the same. The key enablers of a successful Big Data analytics strategy for an enterprise include – Business context and value scenarios - Balanced Score cards and KPIs, Data and Meta data Quality, Integration, Data and BI Architecture, Data Governance, Collaboration and information delivery.
Mature pre-built Big Data Analytics platforms go a long way in partnering with businesses, helping them realize their desired business benefits. Such powerful solutions ideally include the following features - IP-based advisory, niche domain skills, cutting-edge technologies, appropriate strategies for consolidating and standardizing the information landscape, flexibly bringing in relevant Big Data capabilities & associated data types, and providing a unified analytics platform with rich visualizations. These advanced capabilities would yield unprecedented real-time and performance analytics – Descriptive, Diagnostic, Predictive and Prescriptive Analytics.