Hiren Dutta

Work place: Associate Consultant, Tata Consultancy Services Limited

E-mail: hiren.dutta@gmail.com

Website:

Research Interests: Swarm Intelligence, Data Structures and Algorithms

Biography

Hiren Dutta received the B.E. degree in Computer Technology from the Nagpur University, Maharashtra, India, in 2004 and received  M.E. degrees in Software Engineering (Information Technology) from the Jadavpur University, Kolkata, WB, India, in 2013. He completed PGD in supply chain management from St. Xavier’s college, Kolkata in 2009 and awarded certificate on analytics from Indian Statistical Institute in 2014.He is currently designated as an Associate Consultant in Tata Consultancy Services Ltd. He is an expert in providing solution architecture of business applications based on IIoT, brokered SOA, JEE architecture and middleware Integration. He worked in a number of open source technologies, design methodologies, patterns and developing algorithms in system integration and communication. His research interests are IIoT, molecular communication, swarm intelligence, real time data processing and analytics.

Author Articles
Graph Based Data Governance Model for Real Time Data Ingestion

By Hiren Dutta

DOI: https://doi.org/10.5815/ijitcs.2016.10.07, Pub. Date: 8 Oct. 2016

Data governance is one of the strongest pillars in Data management program which goes hand in hand with data quality. In industrial Data Lake huge amount of unstructured data is getting ingested at high velocity from different source systems. Similarly, through multiple channels of data are getting queried and transformed from Data Lake. Based on 3Vs of big data it's a real challenge to set up a rule based on traditional data governance system for an Enterprise. In today's world governance on semi structured or unstructured data on Industrial Data lake is a real issue to the Enterprise in terms of query, create, maintain and storage effectively and secured way. On the other hand different stakeholders i.e. Business, IT and Policy team want to visualize the same data in different view to analyze, imposes constraints, and to place effective workflow mechanism for approval to the policy makers. In this paper author proposed property graph based governance architecture and process model so that real time unstructured data can effectively govern, visualize, manage and queried from Industrial Data Lake.

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