Limitless DATA — From Accumulation to Actionable Insights

It’s all about data — available in every possible format and kind! There is virtually no limit to the amount of data that is available to an enterprise or to the user, but there is a limit to the actually usable amount of data. Organizations have begun to harness data being generated from sources like social media streams, machine and sensor data, besides storing their traditional enterprise data. And these forms of data are often accessed and analyzed to generate insights into customer information, user behavior, market trends, product feedback, etc.

In a joint survey carried out by Accenture and General Electric, out of the total companies surveyed, 80–90% revealed that Big Data is either a top priority for their organization or one in their list of Top 3. Further statistics suggests that 73% of the surveyed organizations already invest 20% of their overall IT budget on Big Data and analytics solutions. They are increasingly becoming an integral part of an organization’s strategy, be it in marketing, development or formulating critical business decisions.

Big data is indeed a vast amount of data and it is growing at an exponential rate. Reports from McKinsey Global Institute point towards data growing at the rate of 40% per year, which is further expected to encounter a 44-times increase by the year 2020. Big Data basically has three main characteristics, although a fourth can also be added to it:

  1. Volume:
    The data available to organizations is usually in the range of petabytes and zettabytes.
  2. Velocity:
    Data influx into the system and its subsequent storage into the storage servers occur at a remarkable rate. As an example, Twitter registers over 8 Terabytes of data every day and manages to process over 5000 tweets every second.
  3. Variety:
    Big data analytics utilizes both structured as well as unstructured data that can be harnessed from any source, starting from marketing campaigns and consumer behaviors to new sensor generated data.
  4. Value:
    One of the highly important elements of analytics, the value of derived data depends on the type of organization, besides having a significant dependence on the type of economy it operates in.

In order to achieve targeted and well-defined analyzes into their vast reserves of data, organizations need to set up the requisite IT infrastructure to collect, store and analyze data. These data streams or sources are accessed by organizations to generate actionable insights on their customers through ERPs, Customer (or Content) Management Systems, weblogs or equipment logs. The results obtained from Big Data and Analytics solutions can be used to formulate new business or marketing strategies.

Speaking of Content Management Systems, Kentico offers a highly dynamic and feature-rich content management system to their users as well as developers. The Kentico CMS is based on the 3-tier .NET architecture and the features include customizable and more than 400 built-in web parts and 40 modules. With Kentico Development, developers can utilize the CMS for managing content; create e-commerce or social networking websites with multi-lingual support and Intranets.