Remove Cost-Benefit Remove Data Architecture Remove Data Science Remove Data Transformation
article thumbnail

How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

article thumbnail

Best BI Tools For 2024 You Need to Know

FineReport

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Cost-effective pricing and comprehensive supporting services, maximizing value.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Lay the groundwork now for advanced analytics and AI

CIO Business Intelligence

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. After moving its expensive, on-premise data lake to the cloud, Comcast created a three-tiered architecture.

article thumbnail

How to modernize data lakes with a data lakehouse architecture

IBM Big Data Hub

In the case of Hadoop, one of the more popular data lakes, the promise of implementing such a repository using open-source software and having it all run on commodity hardware meant you could store a lot of data on these systems at a very low cost. But it never co-existed amicably within existing data lake environments.