Soumendra Mohanty works as an information management capability lead for Accenture, India. In this role, he is responsible for all BI activities in India and for the strategic direction and growth in this geography.
His work spans across areas focusing on BI architectures, data warehouse, customer relationship management (CRM) or customer insight, and supply chain analytics solutions. He also leads innovation and industrialization for the Information Management (IM) offerings. Mohanty works with clients across industries to assist them with achieving profitable growth and business transformation.
His experience spans developing and executing strategies for BI practices and customer insights. In an extensive chat, Mohanty reveals his thoughts on big data. Excerpts
How is big data going to change enterprise IT?
The explosion of data has made it necessary for organizations to adopt specialized databases and data warehouse appliances along with information management tools and techniques for storing, extracting, transforming, integrating, sorting, and manipulating data. Enterprise IT should be geared towards coping with data volume, velocity, and variety to not only prevent storage costs from getting out of control but, more importantly, get better insights faster.
What kind of benefits are companies getting out of it, and what kind of questions should they be asking?
The convergence of big data and cloud provides benefits to businesses in the form of cost savings, ease of management, and unrivaled flexibility. While harnessing big data can provide organizations with valuable insights, they are often faced by the challenge of limited storage and computing power available on premise. Cloud addresses this challenge by providing unlimited storage and access to virtually any place with internet.
Isn't big data all about analytics at scale? Shouldn't we be calling this 'big analytics'?
Not necessarily. While big data is a term used to describe the voluminous amount of unstructured and semi-structured data a company creates, big data analytics is the application of advanced analytic techniques to such big data sets. According to a recent IDC research, big data will earn its place as the next 'must have' competency in 2012 as the volume of digital content grows to 2.7 zettabytes (ZB), up 48% from 2011.
While this data is full of rich information, it is challenging to understand and analyze. In order to gain high-value insights from this big data, businesses are increasingly leveraging analytics technologies, such as in-memory databases and BI tools.
Who are the top players in this space? Please discuss the core areas where big data and cloud can play a game changer role.
The global cloud market is set to explode in the next 10 years. According to a recent Forrester research, the global cloud market will grow from $40.7 bn in 2011 to more than $241 bn in 2020. Simultaneously, the big data market is expanding as large IT companies and start-ups vie for customers and market share. According to a recent IDC study, the market for big data technology and services will grow from $3.2 bn in 2010 to $16.9 bn in 2015.
While harnessing big data generates value across industries & sectors, it has great potential in healthcare, public services, retail, and manufacturing.
For example, if the US healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 bn in value every year. Two-thirds of that would be in the form of reducing US healthcare expenditure by about 8%. In the developed economies of Europe, government administrators could save more than 100 bn ($149 bn) in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues.
Do companies need to hire data scientist or create a specialized team for analyzing data trends?
It is not necessary to hire a data scientist for analyzing data trends. Companies can leverage the existing team(s) of data researchers, statisticians, mathematicians, analysts, and visual creators to identify and analyze data trends. More than a data scientist, there is a need of people who understand the business, customers, and data which as of today don't exist.
If such people with such skillsets are available, for companies across industries, they can generate a lot of value from the data that is available, understand customer behavior, and leverage the data optimally and apply it to the business.
How are big data and cloud changing traditional outsourcing industry? How do you see convergence of cloud with big data?
The convergence of cloud computing with big data and analytics presents a major opportunity for outsourcing companies. Traditionally, data collected by organizations was stored in massive relational databases accessible to only few within the organization and required elaborate infrastructure both in terms of hardware and software for storage, retrieval, and reporting/analytics.
However big data stored on cloud can be accessed from anywhere. Outsourcing companies can offer their clients value added services in the area of big data analytics without heavy investments on the part of clients in specialized hardware and software as was the case with traditional data analytics.
This is resonated by a recent research report from Accenture entitled 'Achieving high performance in BPO', which reveals that cloud computing and data analytics are two technology areas currently offering businesses the opportunity to get more out of BPO.
The research further states that while in the past, a business would have to buy licenses and install heavy-duty business applications as part of a BPO deal, today they can sign up to cloud based services and easily scale up and down the number of users.