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Scientific Session
International Conference on Data Modernization: Transforming Enterprises for the Digital Age 2025 in Plano, Texas


Mr.Sai Nikhil Paluru, Speaker at Data Modernization

Mr.Sai Nikhil Paluru

Data Engineer
Title :  Data Modernization: Transforming Enterprises for the Digital Age



Abstract:

The growing complexity of modern enterprises has made effective data integration and interoperability critical to operational success. As organizations increasingly rely on data-driven decision-making, the challenge of overcoming data silos becomes paramount. This session will explore cutting-edge strategies for seamless data integration, focusing on the removal of barriers between isolated data sources. Key themes will include the adoption of interoperability standards that enable diverse systems, applications, and technologies to work in unison, as well as the role of platforms and tools designed to manage and unify data across heterogeneous environments. Attendees will gain insights into best practices for ensuring data consistency, security, and accessibility, while also learning how to leverage modern technologies such as cloud-based solutions, APIs, and microservices to achieve a truly interconnected enterprise ecosystem. The session will conclude with a look into future trends in data integration, preparing organizations for the next generation of data management and interoperability challenges.

Biography:

• Over 8 years of extensive IT experience with multinational clients this includes 6+ years of recent experience in Big Data/Hadoop Ecosystem.
• Proficient in programming Spark with Scala/Python
• Experience in Spark Streaming to ingest data from multiple data sources into HDFS and other Databases.
• Experienced on SAS/SQL/Data Analysis using latest Statistical software and business intelligence tools.
• Solid Experience and understanding of Implementing large scale Data warehousing Programs and E2E Data Integration Solutions on Snowflake Cloud, AWS Redshift
• Experienced on Cloud Services like AWS and other big data Distributions like Cloudera.

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