Remove Data Lake Remove Data Strategy Remove Strategy Remove Technology
article thumbnail

The data flywheel: A better way to think about your data strategy

CIO Business Intelligence

This article was co-authored by Duke Dyksterhouse , an Associate at Metis Strategy. Data & Analytics is delivering on its promise. Some are our clients—and more of them are asking our help with their data strategy. Often their ask is a thinly veiled admission of overwhelm. We discourage that thinking.

article thumbnail

Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 100
Insiders

Sign Up for our Newsletter

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

article thumbnail

Creating Data Value With a Decentralized Data Strategy

CIO Business Intelligence

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. Thinking about that intelligence as having millions of loosely connected decision points at the edge requires a different strategy, and you can’t micromanage it.

article thumbnail

Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

article thumbnail

Data architecture strategy for data quality

IBM Big Data Hub

Next generation of big data platforms and long running batch jobs operated by a central team of data engineers have often led to data lake swamps. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

article thumbnail

Deriving Value from Data Lakes with AI

Sisense

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. In Growing Up with AI , we help you keep up with all the ways this pioneering technology is changing the world. Once your data is prepared for analysis, the next question is: how else can AI help you?

article thumbnail

Empowering data-driven excellence: How the Bluestone Data Platform embraced data mesh for success

AWS Big Data

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.