Infosys is all set to tap the big data space by mass scale enablement of their talent pool in big data and related technologies and churning out more IP, said Rajeev Nayar, associate VP & head, Big data Practice – Cloud, Infosys.
What are your tips and solutions to enterprise CIOs to improve RoI from Big data deployments?
A number of organizations make the mistake of investing in big data infrastructure and then trying to figure out what insights to gain. It is therefore important that enterprise CIOs, looking to improve ROI from big data deployments, justify the outcome of their big data analysis before making investments.
What are the demands of your enterprise customers?
For CIOs, enabling business to make better decisions, faster, is top priority. However, most CIOs and business leaders are realizing that the traditional approach to data warehousing is inadequate to address today’s big data demands. Enterprises are now looking for solutions that provide the ability to quickly discover, analyze and act on information to drive business decisions. Technology teams need flexibility to rapidly develop industry-specific big data applications while business requires agility for insights and actions.
What are your new strategies in the big data segment?
At Infosys we started the Big data journey back in early 2010 when the term Big data was not even coined. We worked with some global companies in the industry to create their strategy around Big data technologies to transform their IT and business at much lower cost at that point of time. At the same time we also spotted the need (and opportunity) to create our own IP around the gaps in Big data technology space which eventually we launched as our solution ‘BigDataEdge’ in February 2013. To keep up the momentum, our strategy going forward is to tap the Big data Space in two ways – mass scale enablement of our talent pool in Big data (and related technologies) and churning out more IP.
What are your new big data offerings?
Our core offering in this space is the Infosys BigDataEdge platform, which enables real-time discovery of data across both internal systems and external sources; it also helps empower technology and business teams to develop industry-specific insights and act on them very quickly. Infosys BigDataEdge includes:
A rich visual interface with more than 50 customizable dashboards and 250 built-in algorithms. These algorithms, a set of reusable business rules both function and industry-specific, enable business teams to self-serve the process of building insights while minimizing the need for technical intervention
Over 50 data source connectors, which allow easy access to structured and unstructured data residing across enterprise and external sources. This would enable acceleration of discovery of relevant information from existing, underutilized data
A powerful collaboration wall and pre-built workflows that allow teams across functions to interact on insights and collectively implement decisions
A Logical Data Warehouse providing a virtual data management architecture, eliminates the need for physical availability of data to build and test insights
‘Out-of-the-box’ applications for specific industry needs such as fraud detection and prevention, predictive analytics and monitoring, and customer micro-segmentation that deliver faster returns on investment
BigDataEdge provides highly configurable reusable components to handle commonly observed challenges associated with any Big data solution such as structured, unstructured and semi-structured data (Variety), real-time, near-real-time and batch data (Velocity), and large volumes (Volume).
The platform can also serve as a market place where the reusable components can be seamlessly and effortlessly discoverable and marketed to all the interested parties.
What are the latest trends in Big data?
Devices, Processes and Customers
Today, these are sources of elephantine amounts of data that is hard to store, and harder to process. While enterprises were still trying to wrap their heads around the big data phenomenon in 2012, many of them will finally start taming it with strategies and technology solutions. But what are the capabilities they desire? How will they leverage big data for greater business value? Below are 10 big data trends that will answer these questions:
The information strategy – still in formation
While enterprises will be “inundata’d” with a hybrid big data dump, the need of the hour is to turn this into a flexible, manageable information ecosystem.
Easy to configure, easy to use
No longer will big data be the bastion of scientists — enterprises will look for technology solutions that can be easily configured based on user preferences, provide rich visualization dashboards for executives, and accessed on smartphones and tablets.
Big data – of the people, by the people, for the people
Cloud-based and open source tools will help democratize big data to take it out of the realm of expensive resources and high-computing infrastructure — giving even smaller companies the ability to leverage big data for business insights.
All roads lead to instant insight
Enterprises cannot afford to wait around for big data to be processed at its own time — they will need near-real-time results that match the speed of traditional business intelligence.
Internet of things, meet big data
We are fast approaching an era where every device from a car to a fridge to a Kindle is connected to the Internet — and with the rollout of IPv6, big data is only going to get bigger.
Big data and social computing – a match made in ether
Trawling and processing the social web for social network analysis and content analytics will require a new kind of processing power, one that capitalizes on newer social avatars of data.
Retail soothsaying and market crystal ball gazing
Retailers will use big data to analyze social media and match this data against customers lists, transactions, and loyalty club memberships, in addition to predicting consumer patterns, market trends, and competitor initiatives.
A smarter healthcare economy
From process healthcare data available in the public domain to genetic data processing, big data will help analyze vast amounts of information that have been overlooked because of disparate systems and inadequate analytics tools.
Cracking down on fraud in financial services and insurance
Information is at large, and so is fraud — but financial services enterprises will use big data to monitor large volumes of transactions and activity logs to zero in on credit card fraud and account takeovers, while insurers will leverage it to check for fraudulent claims by tracking social data and behavior.
Fault tolerance and detection in manufacturing
Binding operational data with IT data will help create a unified system that can track machine performance, which will be especially useful for high-tech and automotive enterprises.