Ramke Ramakrishnan is a results-driven technology leader with broad-based experience in driving data management strategies and delivering excellence through research, innovation, advisory and agility for Technology Professionals. Mr. Ramakrishnan helps IT organization in modernizing their data platform and advice on the optimization, best practices and continuous improvements on the architecture, design and deployments of data lakes, data warehouse applications in relational, OLAP databases, data processing frameworks such as Hadoop, Kafka, Spark and specialized databases such as NoSQL and Graph database. He provides technical expertise in variety of data management principles such as data integration, orchestration, database management, data virtualization, metadata management, data security, data governance and advanced analytics using machine learning and artificial intelligence thereby enabling technology professionals in building "best in class" analytical applications and data-driven decisions, strategies for management and deployment.
Prior to this, Mr. Ramakrishnan helped companies deliver analytics to business stakeholders and leads strategic initiatives on data management technologies to execute smart, fact-based decisions with business intelligence and predictive analysis. Through his professional services background, he led, advised, managed and delivered several scalable, flexible, adaptive and complex data management, end-to-end integrations and processes for data delivery to support analytical solutions and applications.
Grant Thornton LLP
Analytics and Artificial Intelligence for Technical Professionals
Cloud Computing for Technical Professionals
Application Architecture and Integration for Technical Professionals
Integration Architecture and Platforms for Technical Professionals
Data Management Solutions for Technical Professionals
Masters in Computer Applications, Bharathidasan University
Certificate in Applied Data Science and Applied Artificial Intelligence, Columbia Engineering Executive Education
1Provide thought leadership on Data Warehouse architecture, design and orchestration
2Deliver value proposition on Cloud (SaaS/PaaS/IaaS) Data Management and Integration deployments
3Enable Advanced Analytics and Big Data Life Cycle Management
4Advice on modern data technologies and deployment road maps
5Define Strategies for Data Integration and Data Governance frameworks