Act on Your Data Now

The big data buzz has invaded the industry and each vendor, be it storage, hardware, security, applications, or some other, is getting his solutions in place to capitalise on the trend. In such a situation, it is imperative for IT managers to ensure that they are not laggards in the big data game. It is time for them to grab the opportunity and make certain internal changes to mine the big data trend to drive growth.

Grace Kumar R, Associate Director-IT Infrastructure Services, Cognizant Business Consulting, says, It is a terrible thing to waste data as information is valuable. To run a business successfully and have a competitive edge, it is necessary to ensure that we are not leaving such value on the table behind which can create better customer experiences and growth for the organisation, says Kumar.

Dr MVK Sarma, VP-RDW Product Development, Ramco Systems, observes, It is critical for IT managers to build data visualisation map and put all the infrastructure pieces together to understand the data types; take up business activity monitoring to assess the information usage and thereby reduce dependency on various units for sourcing data flow.

Vivekanand Venugopal, VP&GM India, Hitachi Data Systems, agrees that IT managers need to assess multiple layers in order to capture the trend. He says, Identify an individual (or individuals) who is knowledgeable and has good insights into social business, social media and cloud models. Build the information evolution, which can interlock IT and business, independent of applications, storage and infrastructure that are available to understand the types of data. The idea, according to Venugopal, is to identify the data being used as information lifecycle management, which can be preserved, used and reused to help the organisation leverage data strength.

Mitesh Agarwal, CTO and Director, Systems Solution Consulting, Oracle India, points that the IT heads need to recognise that they cant drive big data with the same cost economics as they do the regular business data.

For example, in ERP they have to store all the data for a certain number of years, while in the case of big data, not all the data will need to be permanently stored. Most of the data may not have relevance, but CIOs cannot know in advance what to keep and what to discard. In addition, in some cases, only summary data may need to be stored permanently. At the same time, the need for analytical tools has increased because of the deeper analytical processing required.

IT heads need to decide the balance of investments in storage, processing power and software after careful analysis of data needs, its potential value, data processing methods and streams, storage location, assessing analytical tools and so on, says Agarwal.

Berjes Eric Shroff, Senior Manager, Information Technology, Tata Services Ltd, raises an intriguing question: Where and when should the organisations IT head start extracting value from the unstructured and structured data? My suggestion is to start with getting clarity into the business problems and extract value from the data sources which are likely to have an impact on the business, says Shroff.

Educating hardcore supporters of conventional analytics and harmonising them with supporters of big data in the team would be beneficial, points out Shroff.

Soumendra Mohanty, Global Lead, Information Management, Accenture, explains what IT managers should keep in mind about the data and its nature. Data can be both big and polystructured. For example, consider the classic Hadoop log-collection use case, or MarkLogics databases, or even the dynamic-schema parts of relational data warehouses built by Zynga and eBay, he says. According to him data can be big and yet simply structured. I think most of Teradatas and Verticas petabyte-scale installations would fit that description, the countless examples of legacy data warehouses would suffice as well.

Data can be not-so-big but polystructured. Consider, for example, the traditional business applications and associated structured and unstructured data they handle and most of the traditional RDBMS world. This is what I have advised clients who are puzzled and worried (thanks to the non-stop chatter around big data and constant flow of marketing collaterals from product vendors) about big data implications, says Mohanty. Mohanty says it is high time we got out of defining big data and got down to the implications it has and the implementations around it. For him, the big problem is not just data volume and data management, it is actually an information optimisation problem.

John Haddard, Director of Enterprise Data Integration, Informatica, opines that some IT heads are not adequately prepared to access, process, integrate and deliver this data. However, according to him, combining big interaction data with big transaction data will unleash great new opportunities for data-centric enterprises.

Mujer