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The data lakehouse is the new popular data architecture. In a nutshell, the data lakehouse is a combination of a data warehouse and a data lake. It makes a lot of sense to combine them, because they are sharing the same data and similar logic.
This session discusses all aspects of data warehouses and data lakes, including data quality, data governance, auditability, performance, historic data, and data integration, to determine if the data lakehouse is a marketing hype or whether this is really a valuable and realistic new data architecture.
Your role can range from Chief Data Officers (CDO) and technology planner to ICT and enterprise architect, and from data analyst, data warehouse designer, data architect, solution architect, to data engineer, data scientist and data consultant.
Presented by Rick van der Lans
This eSeminar is a LiveOnline event. This means that there will be an expert speaker in a virtual meeting room along with you and other highly interested participants. We will make your learning experience as immersive and interactive as we have done in the past 25+ years, but now in a live, online environment. Besides answering your appetite for knowledge and your questions, we will stimulate the interactivity between the speaker and the participats, and between participants.
The data lakehouse is the new kid on the block in the world of data architectures. In a nutshell, the data lakehouse is a combination of a data warehouse and a data lake. In other words, this architecture is developed to support a typical data warehouse workload plus a data lake workload. It holds structured, semi-structured and unstructured data.
Technically, in a data lake house the data is stored in files that can be accessed by any type of tool and database server. The data is not kept hostage by a specific database server. SQL engines are also able to access that data efficiently for more traditional business intelligence workloads. And data scientists can create their descriptive and prescriptive models directly on the data.
It makes a lot of sense to combine these two worlds, because they are sharing the same data and they are sharing logic. But is this really possible? Or is this all too good to be true? This session discusses all aspects of data warehouses and data lakes, including data quality, data governance, auditability, performance, immutability, historic data, and data integration, to determine if the data lakehouse is a marketing hype or whether this is really a valuable and realistic new data architecture.
These are a few good articles about the data lakehousing concept and solutions:
Rick van der Lans is a highly-respected independent analyst, consultant, author, and internationally acclaimed lecturer specializing in data architectures, data warehousing, business intelligence, big data, and database technology. In 2018 he was selected the sixth most influential BI analyst worldwide by onalytica.com.
He has presented countless seminars, webinars, and keynotes at industry-leading conferences. For many years, he has served as the chairman of annual Data Warehousing and Business Intelligence Summit in The Netherlands.
Rick helps clients worldwide to design their data warehouse, big data, and business intelligence architectures and solutions and assists them with selecting the right products. He has been influential in introducing the new logical data warehouse architecture worldwide which helps organisations to develop more agile business intelligence systems.
Over the years, Rick has written hundreds of articles and blogs for newspapers and websites and has authored many educational and popular white papers for a long list of vendors. He was the author of the first available book on SQL, entitled including Introduction to SQL, which has been translated into several languages with more than 100,000 copies sold. Recently published books are Data Virtualization for Business Intelligence Systems and Data Virtualization: Selected Writings.
He presents seminars, keynotes, and in-house sessions on data architectures, big data and analytics, data virtualization, the logical data warehouse, data warehousing and business intelligence.
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