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As enterprises go about their Big Data adoption journey, there are many pressing questions at hand. What are the Big Data capabilities they desire? How will they leverage Big Data for greater business value? How can they find a solution that

delivers both speed and outcomes? Let’s find out with our Big Data experts.

Vishnu BhatVice President and Global Head – Cloud, Infosys @BhatVishnu

Joseph A. di Paolantonio Vice President and Principal Analyst, Constellation Research @JAdP

Rajeev NayarAssociate Vice President and Head – Big Data, Infosys @nayar_rajeev

R ‘Ray’ WangPrincipal Analyst and CEO, Constellation Research @rwang0

Is the traditional approach to data warehousing relevant in the Big Data environment?

A significant shift in mindset is required.

Enterprise data warehousing (EDW) has to account for unstructured and semi-structured data.

EDW will transform to augmented data warehousing or logical data warehousing very soon, and in a hurry.

Some approaches from data warehousing are key, like a focus on data quality and information governance.

The end in mind takes advantage of some data warehousing techniques. The goal is moving from data to decisions.

Vishnu Bhat

R ‘Ray’ Wang

Are enterprises considering the complete spectrum of opportunities that Big Data presents?

Not really. So far we have seen the mindshare predominantly revolving around externally available social media data.

The opportunity lies in harnessing unstructured data within enterprise as well as structured operational data in backup tapes.

Large, traditional enterprises are just beginning to see beyond the hype of Big Data by investigating newer approaches to data management and analytics for sales, customer service and retention, operations.

The full spectrum of opportunities have not yet been defined. The use cases are a huge data set themselves.

Vishnu Bhat

Joseph A. di Paolantonio

What’s the criterion to choose the right solution for Big Data to address the varied needs of both IT and business?

The questions to be asked of the data sets set the criteria. As do the available talent and architectural fit.

The criteria should include speed, agility, self-service concepts, and connection to variety of data sources.

Other important criteria: does the solution enable fast discovery of insights from massive volumes of data? Does the solution minimize data extraction and movement?

Joseph A. di Paolantonio

Vishnu Bhat

What data governance aspects should enterprises consider while implementing Big Data solutions?

Big data and data science are about exploring data. Outliers can be important.

Agile, iterative approaches to data cleansing, integrity, and master data management are vital.

Content governance on the other hand is different. Quality concerns remain but the solutions can be made tolerant to bad quality data by using statistical methods to normalize.

Joseph A. di Paolantonio

Rajeev Nayar

Solutions available in the market today talk about faster insights and decisions. But how do you ensure implementation of those decisions?

Solutions in the market today focus on analysis, but these are of no use unless enterprises are able to institutionalize them.

Enterprises should look for Big Data solutions that enable rapid institutionalization. They should also put in place a process that ensures business leaders take accountability of insights and follow through to institutionalization.

Implementation can be ensured with the right processes, training, and automation with regard to Big Data.

When you focus on business outcomes and not the technology, you improve alignment for success.

Success also requires alignment with business processes, as well as providing the right rewards and incentives.

Vishnu Bhat

R ‘Ray’ Wang

Joseph A. di Paolantonio

There will be two camps that clearly form in this space.

One that will try to build the capabilities of existing data processing solutions into Big Data technologies.

And the other that will subsume the Big Data processing model into the traditional databases.

Enterprises need an even stronger emphasis on probability and statistics as even more complex data sources spring from the Internet of Things.

All roadmaps must interweave — including machine-to-machine (M2M), machine-to-human (M2H), human-to-machine (H2M), and human-to-human (H2H). Decisions must be made at the right time, at the right place, meaning Big Data includes mobility and cloud.

Rajeev NayarJoseph A. di Paolantonio

What is the future of Big Data and how should enterprises plan their adoption roadmap?

Big Data, data science, as well as data management and analysis (DMA) skills are in short supply at enterprises.

Also, traditional skills in enterprise data warehousing and business intelligence don’t translate to Big Data expertise.

Service providers address both these needs.

There will be a shift from product vendors and engineered system providers to system integrators who will engineer solutions.

The service providers who do not evolve along this shift will be pushed down to the infrastructure space.

Service providers can play a role in Big Data business models.

Or they can help guide enterprises as to which Big Data tools are worth the investment.

What role can service providers play to realize business value through Big Data?

Joseph A. di Paolantonio

Rajeev Nayar

R ‘Ray’ Wang

While it is evident that business and IT teams across enterprises want to leverage Big Data insights, they are unable to find a solution that meets both their priorities. If turning data into revenue is the

clarion call, what enterprises need is:

Real-time data discovery and aggregation Easy-to-use data visualization options

Automated connector functions for new information sources

A way to operationalize insights across the enterprise

Reusable algorithms to build insights in a few minutes Prebuilt industry-specific scenarios

Vishnu Bhat, Vice President and Global Head – Cloud, Infosys

Vishnu has been with Infosys for 20 years. He leads the Cloud and Big Data practices at Infosys, and is driving the vision of delivering a trusted cloud ecosystem for its clients. Previously, Vishnu led the System Integration unit at Infosys. Prior to that, he was the Chief Operating Officer (COO) for Infosys Australia. As COO, he integrated an acquired subsidiary, building a strong footprint in the market. He has also headed the Global Development Centre in Toronto and delivery operations for Canada.

Rajeev Nayar, Associate Vice President and Head – Big Data, Infosys

Rajeev Nayar leads the Big Data practice as part of the Cloud unit at Infosys. He has more than 18 years of experience in information management. His key areas of focus now are big data analytics and extreme data processing, which deals with very large-scale data solutions. His works spans multiple vertical areas and has helped guide the development of a patent pending solution for big data at Infosys. He has presented at a number of conferences and co-authored a book on big data titled ‘Big Data Spectrum.’

Joseph A. di Paolantonio, Vice President and Principal Analyst, Constellation Research

Joseph A. di Paolantonio focuses on the Internet of Things, applying data management and analytics to energy management, sustainability, sensors, green business practices, and more. Since 1978, Joseph has been involved with renewable energy research, creating analytical techniques for solving business, engineering and scientific problems. Starting 2004, he has been blogging at The TeleInterActive Press.

R ‘Ray’ Wang, Principal Analyst and CEO, Constellation Research

R “Ray” Wang is the author of the popular enterprise software blog ‘A software insider’s point of view’, as well as a much sought-after thought leader and speaker. A background in emerging business and technology trends, enterprise apps strategy, technology selection, and contract negotiations enables Ray to provide his clients and readers with the bridge between business leadership and technology adoption.

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The 7 key considerations are derived from a Big Data Tweetchat, featuring Big Data experts from Constellation Research and Infosys. The Tweetchat brought together business and IT

communities to discuss Big Data opportunities.

For more information and insights, please visit us at www.infosys.com/bigdataedge

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