Remove introducing-entity-centric-data-modeling-for-analytics
article thumbnail

Reduce Friction In Your Business Analytics Through Entity Centric Data Modeling

Data Engineering Podcast

Summary For business analytics the way that you model the data in your warehouse has a lasting impact on what types of questions can be answered quickly and easily. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles.

article thumbnail

Data Engineering Weekly #127

Data Engineering Weekly

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make collecting data from every application, website, and SaaS platform easy, then activating it in your warehouse and business tools. 🍒 We'll send exclusive The Data Stack Show swag just for participating!

Insiders

Sign Up for our Newsletter

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

article thumbnail

Object-centric Process Mining on Data Mesh Architectures

Data Science Blog: Data Engineering

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

article thumbnail

Data Entropy?—?More Data, More Problems?

Towards Data Science

Data Entropy — More Data, More Problems? How to navigate and embrace complexity in a modern data organisation. Business users are unable to find and access data assets critical to their workflows. Data engineers spend countless hours troubleshooting broken pipelines. Every “minor” change upstream results in mayhem.

article thumbnail

Data Contracts and 4 Other Ways to Overcome Schema Changes

Monte Carlo

There are virtually an unlimited number of ways data can break. But perhaps one of the most common reasons for data quality challenges are software feature updates and other changes made upstream by software engineers. These are particularly frustrating, because while they are breaking data pipelines constantly, it’s not their fault.

article thumbnail

Apache Ozone and Dense Data Nodes

Cloudera

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Separates control and data plane enabling high performance.

article thumbnail

Introducing CDP Data Engineering: Purpose Built Tooling For Accelerating Data Pipelines

Cloudera

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.