AWS re:Invent 2018: Effective Data Lakes: Challenges and Design Patterns (ANT316)
Data lakes are emerging as the most common architecture built in data-driven organizations today. A data lake enables you to store unstructured, semi-structured, or fully-structured raw data as well as processed data for different types of analytics-from dashboards and visualizations to big data processing, real-time analytics, and machine learning. Well-designed data lakes ensure that organizations get the most business value from their data assets. In this session, you learn about the common challenges and patterns for designing an effective data lake on the AWS Cloud, with wisdom distilled from various customer implementations. We walk through patterns to solve data lake challenges, like real-time ingestion, choosing a partitioning strategy, file compaction techniques, database replication to your data lake, handling mutable data, machine learning integration, security patterns, and more.
Пікірлер: 13
I recommend this to my clients as one of the best collections of datalake best practices in one place.
Great presentation. No fluff. Went straight to the problems and recommended the solutions. Very compact and dense though. Thanks for an outstanding job.
thank you....well articulated ...! please keep them rolling ...-:)
appreciate so many blueprints they shared for different scenarios
Very effective Radhika's speech
Very good summation of AWS components from Data Lake Standpoint
Great preso .. Direct to the point! Good job Radhika
Best all in one place
Radhika's speech is impressive.
@tiagotele1
3 жыл бұрын
Indeed! The level of knowledge and clear presents is astonishing!
Most crazy and dense lecture I ever heard.. congrats.. that too Indian +female
Why the other friend there's hanged like jesus christ :)