[Webinar] Data Warehousing Trends, Best Practices, and Future Outlook

Описание: About the Session:

Over the last decade, the 3Vs of data - Volume, Velocity & Variety has grown massively. The Big Data revolution has completely changed the way companies collect, analyze & store data. Advancements in cloud-based data warehousing technologies have empowered companies to fully leverage big data without heavy investments both in terms of time and resources. But, that doesn’t mean building and managing a cloud data warehouse isn’t accompanied by any challenges. From deciding on a service provider to the design architecture, deploying a data warehouse tailored to your business needs is a strenuous undertaking.

Looking to deploy a data warehouse to scale your company’s data infrastructure or still on the fence? Then join us for this session with James Serra - Data Platform Architecture Lead at EY to gain insights into the current Data Warehousing trends, best practices, and future outlook. Learn how to build your data warehouse with the help of real-life use-cases and discussion on commonly faced challenges.

In this session you will learn:
1) Choosing the best solution - Data Lake vs. Data Warehouse vs. Data Mart
2) Choosing the best Data Warehouse design methodologies: Data Vault vs. Kimball vs. Inmon
3) Step by step approach to building an effective data warehouse architecture
4) Common reasons for the failure of data warehouse implementations and how to avoid them
5) Trends and benefits of implementing Data Warehouse Automation

About the Speaker:

James is an expert in data warehousing and data management space. He has over 35 years of experience in data modeling, data governance, and development methodologies and holds the Microsoft SQL Server MVP title. James is currently working as a Data Platform Architecture Lead, Director in the Client Technology Group at EY. Prior to EY, he was working at Microsoft as a big data and data warehousing solution architect for 7 years.

#DataWarehousing #CloudDataWarehouse #DataEngineering