Dataconomy

APRIL 27, 2023

Additionally, adding more single-purpose or fit-for-purpose databases to expand functionality can create data silos and amplify data management problems. Building in these characteristics at a later stage can be costly and resource-intensive.

Database 159

Database Data Scientist Data Mining Data Mining 159

Tableau

JULY 25, 2024

This data model enables you to explore correlations and answer more sophisticated analytical questions, such as how Marketing spend affects Sales, or how Spend actuals are tracking against Budget forecasts. Play around with the hypothetical retail store data model and explore analytics scenarios: Download the sample Tableau workbook.

Tableau 76

Tableau Data Modeling Data Models Data Silos 76

Alation

DECEMBER 13, 2022

One data catalog supports a broader organizational ability to collaborate (and innovate) across user types, use cases, and business units. Not only do such products create data silos – they perpetuate a broken social system that excludes key stakeholders. Curious to learn more about data catalogs?

DataOps 52

DataOps Data Governance Data Silos Data Scientist 52

The MLOps Blog

MAY 17, 2023

This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines. Before delving into the technical details, let’s review some fundamental concepts.

ETL 59

ETL Data Pipeline ML ML 59

Flipboard

DECEMBER 4, 2024

However, building data-driven applications can be challenging. It often requires multiple teams working together and integrating various data sources, tools, and services. For example, creating a targeted marketing app involves data engineers, data scientists, and business analysts using different systems and tools.

Data Lakes 132

Data Lakes Data Warehouse AWS Database 132