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Today’s businesses demand more insight, faster, from higher volumes and variety of data. The modern data warehouse is designed to handle these new challenges, using new architectures based on new technologies. In this session we will explore:
Challenges facing legacy data warehouse architectures in addressing modern business demands
Aspects of a modern data warehouse
Use cases for modern data warehousing, including data science, data engineering, and machine learning
The cloud offers a great advantage in time to delivery for new analytics projects, flexibility in scaling up and down based on need, and more. However, moving to the cloud, in whole or in part, has challenges, especially around maintaining a consistent data context for security, governance, and metadata. In this session we will explore:
Opportunities offered by data warehousing in the cloud
Use cases for data warehousing in the cloud
Technologies, architectures, and tools to help maintain a shared data experience when using pure or hybrid cloud deployment models
The modern data warehouse is a myriad of new technologies working together to provide better insight on more data. This new architecture comes complete with new challenges for keeping things running smoothly. This session will explore:
New challenges in data warehouse optimization
New challenges in data warehouse troubleshooting
Tools and techniques to manage, optimize, and troubleshoot all manner of workloads
Greg is responsible for driving SQL product strategy as director of product management on Cloudera’s Data Warehouse product team, including working directly with Impala. Greg has spent more than 20 years working with relational database systems across a variety of roles—including software engineering, database administration, database performance engineering, and most recently product management—providing a holistic view and expertise on the database market. Previously, Greg was part of the esteemed Real-World Performance Group at Oracle and was the first member of the product management team at Snowflake Computing.
Raman is a product manager on Cloudera’s Data Warehouse product team, specializing in building machine learning, predictive analytics, and data management products. He has a passion for creating and implementing high-performance algorithms for massively parallel processing and big data platforms. Raman has more than 15 years of international experience in R&D, product development, data science and machine learning, and engineering, with a deep understanding of healthcare, financial, and high-tech manufacturing domains.
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