Putting the Voluminous Data to Best Use By Srikanth Karnakota, Country Head for Server and Cloud Business, Microsoft

Putting the Voluminous Data to Best Use

Srikanth Karnakota, Country Head for Server and Cloud Business, Microsoft | Thursday, 08 December 2016, 08:26 IST

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Q. As companies begin to deeply explore what big data can do for them, it’s important that the chosen solution is able to address both business intelligence and big data. What according to you can be a probable answer to it?

It is imperative for businesses today to evaluate and explore new revenue streams through various approaches that deliver value and competitive advantage to the organization. As such, digital transformation becomes a persistent and relevant theme across industries. Through the right use of data, intelligence and tools, businesses are able to engage customers, empower employees, optimize operations, transform offerings – ultimately leading to improved business outcomes for organizations.

Today, the ability to dissect data is held by a select few. For a new data culture to happen, talents across the board need to be data-savvy in other to optimize the data collection, analysis and usage.

Q. The world is awash in data- according to one estimate, almost 3 zettabytes (3 billion terabytes) of information had been created by 2012, a digital deluge that is growing at around 50 percent a year. How do the computing technologies need to evolve with this pace of growth of Big Data?

The growing volume, velocity, diversity, and locations of enterprise data make it increasingly challenging to discover, connect to, move, transform, integrate, and analyze it all. In fact, with the compound annual growth rate of data from 2013 to 2020 estimated at 41 percent, this can be termed a data explosion. This is the result of more and more devices combined with a new hunger from businesses for more data to better understand and predict customer needs to make smarter decisions with data.

Yet, without the ability to analyze it, data loses its value. Microsoft SQL Server and the related Microsoft data platform are delivering the tools that businesses need to gain deeper insights from all of their data. SQL Server 2016 offers new and enhanced features to support these ever-growing data storage needs. Users can now query relational and non-relational data together with PolyBase, and also take advantage of cloud-based big data capabilities with HD Insight for Azure. In addition, SQL Server 2016 includes advanced solutions for both on-premises and cloud-based data warehousing.

Q. Limits to storage capacity, hardware acquisition, scalability, performance and cost are all potential reasons why customers haven’t been able to implement a data lake. How does Microsoft intend to counter those drawbacks through Azure Data Lake?

Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists and analysts to store data of any size, shape and speed and do all types of processing and analytics across platforms and languages in the cloud. It removes the complexities of ingesting and storing all of your data while making it faster to get up and running with batch, streaming and interactive analytics.

Azure Data Lake solves many of the productivity and scalability challenges that prevent you from maximizing the value of your data assets with a service that is ready to meet your current and future business needs.

Q. Businesses will be able to access future predictive trends, and machine learning will be a property of every predictive application, enabling these smart insights. How far has the innovation proceeded to in Machine Learning? How is Microsoft headed?

The idea of machine learning has been around for quite a while. Because we now have so much more data, machine learning has become useful in more areas. Yet, unless the technology of machine learning gets more accessible, we won’t be able to use our big data to derive better solutions to problems, and thus build better applications.

A primary goal of Microsoft Azure ML is to address this challenge by making machine learning easier to use. Azure ML is a fully managed service that you can use to create, test, operate, and manage predictive analytic solutions in the cloud. Going forward, expect data-derived models to become more common components in new applications.

Recently, ICRISAT has adopted Microsoft Cortana Intelligence Suite including Machine Learning and Power BI or Business Intelligence, to empower farmers and government officials with technology, and promote digital farming practices in the state. Also, Microsoft is working with the Government of Andhra Pradesh to build machine learning models on data being collected on student enrollment to predict dropouts. Andhra Pradesh Government is now using this intelligence to plan strategic interventions under its 'Badi Pilusthundi' campaign.

Q. Data provides you with the insight to analyze your past, optimize your present, and make strategic decisions for the future. The key question is: In a world of big data and information on demand, how do you accelerate time to insight and action?

Increasing consumer demands and changing economics have created an imperative for change in the world of business today. Data is the new currency driving agile innovation across industries for those with the tools, attitude, and commitment to change.

Each day vast quantities of valuable data are generated, that could be combined and analyzed to improve outcomes and effectiveness. But most often, the problem is that the needed data is stuck in multiple silos. Without the right tools, it’s hard to get to.

At Microsoft, we’re committed to working with organizations around the world to reduce boundaries to data and empower them through the availability of information at the moment of need. Among our latest offerings that are being used to bridge the data silos are SQL 2016, Cortana Intelligence Suite, Power BI and Azure Machine Learning.

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