Does Big Data and Social Media Analytics go hand in hand?

Social Media Analytics is a discipline that helps organizations measure, assess and explain the performance of their social media initiatives. Analzing social media data involves data collection, measurement, analysis and innovation, the latter being the final step, where insights from the data are transformed into ideas and new products.

Typically, the data sources  include internal data, such as the purchase history of customers, their transactions, and profiles in the enterprise database, website traffic data covering internal CSR logs, customer queries, automated agent discussions, complaints and resolutions, and employee insights, social activities and profile updates of customers on public social media platforms such as Twitter, Facebook, Myspace, LinkedIn, as well  as industry sources of information and market research reports.

Social  Media Analytics is an outcome-based approach which creates visible Return on Investment (RoI) for companies.  It not only helps organizations retain customers by addressing their concerns upfront, but also enables them to improve customer service, bring down the cost of operations, add new customers by capturing their requirements, predict client behavior, and monitor competition.
Considering these factors, and the fact that it enables enterprises to leverage the colossal data that is continuously being generated through social media interactions Social Media Analytics should be made an integral part of the marketing and research strategies of enterprises.

At the same time, and despite its obvious benefits, it is clear that Social Media Analytics faces a huge challenge—dealing with humungous data. Existing Enterprise Datawarehousing (EDW) environments lack the ability to capture, and process social media data within a reasonable time or analyze the behavior of  users.

In this scenario, using Big Data technologies is the best bet for large organizations. Big Data technologies can help organizations handle large volumes of complex, unstructured data from social sources, of the order of terabytes and petabytes, gain insights into customers and trends, store images and videos, and save hundreds of thousands of dollars per terabyte per year.

Impetus, an established thought leader in  the Big Data space, has conceptualized and architected  a Big Data platform for Social Media Analytics. 

The Impetus Large Data Analytics Platform (iLaDaP) developed by Impetus, is built using the Service Oriented Architecture (SOA), and designed to derive intelligence and operate on huge datasets collected from numerous data sources in multiple data formats.

Powered by Hadoop, it can linearly scale up to thousands of nodes using commodity hardware, bringing significant cost advantages to organizations in the long run.  iLaDaP also comes with a set of pre-canned and customized reports.

Businesses that need to track down and take advantage of opportunities as they happen, can use the Impetus platform to react to events. The iLaDaP is also capable of collecting data from a range of disparate sources. This unstructured data can be transformed and utilized for strategic business decisions. Furthermore, organizations can deploy the solution on-premise, as well as in a Cloud supported setup. iLaDaP can be seamlessly integrated with the current platforms of companies thus preserving existing investments, without making any major changes.