Big Data Analytics Enterprise Trends & Approach

BIG DATA ANALYTICS ENTERPRISE TRENDS & APPROACH

Business and technology are experiencing a convergence. Data and analytics leaders are central to any high-performance digital organization. So how do companies achieve competitive advantage in today’s business environments? Basically, they must use data, information and analytics more simply and more effectively. Technological, financial and commercial together with social elements have pushed Big Data into an orbit of phenomenal growth, giving organizations greater access to insights that are deeper and broader – with greater levels of knowledge about user behavior across channels such as search and social, and into key performance indicators, both globally and locally. This calls for enterprises to be more responsive to changes in user behavior and needs, and to industry developments.

Data and analytics analysts agree that we are at the front end of a generational shift. This transformation has come about with the ability to handle large volumes of data and Big Data assumes importance because it has transformed the way enterprises manage data and at a larger level how the enterprises are managed. While earlier it may have taken much iteration, mid-course corrections and alternatives, the use of an alternative approach called Bayesian inference has made the whole exercise more robust, reliable and more intuitive so that it is now possible to simply make a guess and then revise the judgment as new information came in. This approach has no specific controls, no rules about significance, but just a revision of probabilities in the wake of new data, inferences and developments.

The cheaper cost of storage has also made it possible to hold data while the processing power is also fast increasing. The combination of greater returns in storage and processing power, along with huge volumes of data from the Internet of Things (IoT) and better algorithms, has helped make Bayesian methods not only practical, but faster, cheaper and more accurate than conventional methods. This outlines the importance of Big Data Analytics as a technology that provides the means to fruitfully analyze data and derive insights that are timely, actionable and relevant.

Trends affecting data and analytics:

  1. Roles are changing: Data, analytics, algorithms and information governance are becoming ever more separate from IT.
  2. Data itself is changing: This is the oft-discussed phenomenon of “big data” (a term that is already passé) and how to manage it with governance, analytics and algorithms.
  3. Organizations are changing: We see the organizational convergence of three disciplines —information management, analytics (BI) and algorithms, and change leadership and management.
  4. Businesses are changing: Digital business is encouraging the monetization of data and algorithms, and along with the phenomenon of open data is creating business ecosystems that transcend the boundaries of the traditional enterprise or government entity.

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