Cloud object storage has become the de facto choice for data lakes. Even though data lakes offer the ability to store large amounts of structured and unstructured data, gaining all the insights from all that data can be challenging.
- How to accelerate data lake analytics and what are the advantages of running analytics on your Data Lake?
- How avoid the complex architectural changes of configuring, refreshing, and analysing data within your data lake?
- What does it take to combine the performance and scalability of the cloud with your data lake to discover all insights?
- How can you support all your users?
Experienced Engineer & Architect in Big Data and Analytics. Enjoys the challenge of establishing disruptive products on new markets by combining deep technical knowledge of Software Engineering and Enterprise Architecture with modern business values.
Stage 2 | Master Data Management & Data Quality
Mats Johansson – Solution Architect | Snowflake