article thumbnail

Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

article thumbnail

Eight Top DataOps Trends for 2022

DataKitchen

For example, a Hub-Spoke architecture could integrate data from a multitude of sources into a data lake. The Hub-Spoke architecture is part of a data enablement trend in IT. Data that flows through the Hub-Spoke data architecture will be controlled and managed by workflows located in a centralized process hub.

Testing 245
Insiders

Sign Up for our Newsletter

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

article thumbnail

Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126
article thumbnail

DataOps For Business Analytics Teams

DataKitchen

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics.

article thumbnail

The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

article thumbnail

The Future of the Data Lakehouse – Open

CIO Business Intelligence

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

article thumbnail

How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps automation replaces the non-value-add work performed by the data team and the outside dollars spent on consultants with an automated framework that executes efficiently and at a high level of quality. Focusing on the processes that operate on data enables the team to automate workflows and build a factory that produces insights.

Analytics 246