Arvind Shetty brings with him over three decades of IT industry experience, and has held diverse set of roles at IBM. Arvind joined IBM in 2003, and his assignments have included leadership of the IBM Java Technology Center, the ISL Talent Development program, the Infosphere development and Cloud hosted offerings mission.
Arvind has also led the worldwide development responsibilities for a range of offerings and development missions, including the Information Server On-prem Customer Commits, IS on Hadoop, Optim, MDM, Data Replication, and Information Lifecycle and Governance. Across all his roles, Arvind has brought a rare empathy and exceptional focus to ensure customer success and employee empowerment.
In 2015, Arvind was also selected as an IBM Manager Champion, to be an advocate, role model, and mentor to managers and thought leaders, one among 50 such appointments worldwide. Analytics India Magazine got in touch with Arvind Shetty, the Director of Analytics for IBM India Software Labs to find out how the organization is making use of analytics to address unique business and industry challenges.
Analytics India Magazine: What is IBM strategy towards encouraging innovation at the firm? Present us with a picture of the innovation lab at IBM.
Arvind Shetty: Innovations is one of the key focus areas, and is an integral part of our core values ‘innovations that matters — for our company and for the world.’ With 24 Years of IBM Patent Leadership as backing, we have IP Development and Harvesting programs which provide the basis for this level of leadership. IBM also conducts Innovation Jams to encourage Ideas and Innovative approaches for existing solutions.
Besides this, IBM has a dedicated Research Unit called the IBM Research Labs with centres across the world. They primarily focus on solving unique technology impediments.
AIM: IBM Analytics offers a complete portfolio of big data and analytics solutions to fuel your cognitive business. Please walk us through your solution portfolio.
AS: The IBM Analytics Portfolio covers Data Management, Unified Governance, Content Management, Data Science, Business Analytics, Big Data, Watson Data Platform and Watson Services.
In the Data Management space, IBM provides Hybrid Databases, Data Warehousing Solutions and different types of NoSQL Databases. IBM’s Unified Governance space, provides all the capabilities needed for Information Integration, Governance, and Data Lifecycle Management. In the Content Management space, there are various solutions for dealing with documents, imaging, and other needs surrounding unstructured and semi-structured Data.
IBM’s Data Science division provides most of the capabilities needed by a Data Scientist Persona, primarily oriented towards Data Wrangling needs. The Business Analytics space comprises of solutions needed for BI, Performance Management, and Discovery of Insights. In the Big Data space, IBM furnishes solutions for building and managing Data Lakes.
This is not all. The Watson Data Platform brings together many services like Apache Hadoop, Spark, Machine Learning, Streams, Asset Catalogs, and Big Data Governance components as a set of Fabric Services. Additionally, the Watson Services provides for all the Cognitive aspects of analytics to be blended for conversation, discovery, language, speech, vision, and empathy gauges.
AIM: IBM furnishes Predictive analytics and data visualization services through its Watson platform. Can you shed some light on this statement, explaining how this solution is benefitting your clients in India?
AS: The Predictive Analytics capabilities on Cloud are offered under the name IBM Watson Machine Learning Service on Bluemix. For regular visualization, IBM offers Watson Analytics. On the other hand, IBM Cognos Software on Cloud facilitates advanced visualization and reporting.
AIM: Present a case study where you used your analytics based solution to address business challenge for one of your clients. How did they see value out of your solution?
We have a lot of industry-specific case studies catering to our analytics value proposition. Eliminating welfare fraud and delivering the right benefits to the citizens who need them the most is important. Moreover, Economic assistance provides a safety net for vulnerable citizens. The Government of Odisha found it a challenging job to allocate benefits to the people who needed them the most.
The organization used IBM Analytics solutions to match claimant records to corresponding tax, income, and property records. This helped towards identifying around 500,000 individuals, who were wrongfully claiming benefits. With newfound visibility into which citizens truly qualify for social assistance; the organization can ensure that vital resources are distributed fairly and taxpayers’ money is better utilized.
Benefits of implementing the solution:
- Ensures that vital benefits go to citizens who are truly in need.
- 500,000 wrongful claimants identified and removed from the system.
- Saves costs and effort, helping the government make the best use of its resources.
AIM: What does the IBM future look like in a data-driven industry?
AS: Enterprise requirements will continue to evolve with the shifting business dynamics. The data driven industry will look for solutions to simplify data, leverage, and maximize insights from their own data. Besides, platform for unified governance and a data fabric will provide access to all enterprise data through a common interphase. Our mission is to make data simpler and help enterprises be ready for the data-driven era.
IBM recently announced ‘Download and Go’ for DB2 which allows you to download and see value in fifteen minutes. We also believe that it’s best to bring Machine Learning to the data source, and hence we brought Watson Machine Learning on IBM Cloud, followed by mainframe. Furthermore, we recently introduced Machine Learning and Data Science to Hadoop where the data resides. We don’t dictate framework or language as the open platforms helps bring more people to the table.
We have built Watson Data Platform which allows enterprises to access all data from a single inter-phase, collaborate, share new insights, and build smarter, scalable applications in less time.
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