How Open Lakehouses for Query Execution and Performance Simplify Cloud Analytics
TDWI Speaker: David Loshin, President of Knowledge Integrity
Date: Wednesday, April 27, 2022
Time: 12:00 p.m. PT, 3:00 p.m. ET
Cloud migration affords your organization the opportunity to rethink the fundamental architecture of corporate reporting and analytics system design. This webinar explores how cloud resources and services eliminate the need for costly data warehouse solutions that require significant data integration and preparation efforts.
By examining how an optimized SQL engine can support data access, querying, and generation of result sets materialized from across cloud storage paradigms, attendees will learn about:
- Leveraging cloud caching to reduce data latency
- How a columnar orientation of data stored in memory can speed response times
- Using intelligent precomputed aggregations to accelerate performance
- How query optimization can streamline computation of complex queries across distributed data artifacts
Director of Product Marketing
Preeti Kodikal is the Director of Product Marketing at Dremio. She has worked in Analytics and other industries for the past 17+ years at SAP as well as mid-sized companies and startups - in product management and product marketing roles.
Webinar Series: Strategies for Democratized Cloud-based Analytics Using Open Lakehouse
The design of the traditional on-premises data warehouse is predicated on the presumption that data must be extracted from source systems, transformed into a format suited to an architecture specifically for analytical queries, and loaded into a segregated data system isolated from the original sources. Over the past decades, data warehouse design has abjectly followed this conventional wisdom, resulting in a piling on of technical debt that sometimes overwhelms the ecosystem for reporting and analytics.
As a platform, the cloud is positioned to change this. Fundamental aspects of cloud computing reduce or even eliminate technical dependencies that constrained the traditional data warehouse design, including, but not limited to:
- Decoupling of data from computing resources
- Effectively unlimited resource scalability
- Seamless data distribution
- Massively parallel computing
- Integrated data pipelines
No wonder that organizations are actualizing their analytics workloads to the cloud. A naive approach such as replicating an on-premises data warehouse in the cloud may seem like an easy approach for moving to the cloud. However, newer approaches such as data lakehouses that use an open foundation can provide a strategic architecture that best takes advantage of cloud services and technologies.
This series of three webinars examines the different aspects of the open data lakehouse and how it can support analytics performance and democratization while eliminating dependencies on proprietary data file structures, table formats, or system components.
Don’t miss any of the webinars in this special series!
April 27 - How Open Lakehouses for Query Execution and Performance Simplify Cloud Analytics
May 24 - Automating the Open Data Lakehouse Using an Open Intelligent Metastore
June 15 - Putting it all Together: Panel Discussion on Building Cloud Analytics Using an Open Lakehouse