erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Ontotext

FEBRUARY 12, 2024

In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

DECEMBER 21, 2023

This is a guest post co-written by Alex Naumov, Principal Data Architect at smava. smava believes in and takes advantage of data-driven decisions in order to become the market leader. smava believes in and takes advantage of data-driven decisions in order to become the market leader.

Data Lake 85

Data Lake Data Warehouse Data-driven B2B 85

IBM Big Data Hub

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Enter the open data lakehouse.

Data Warehouse 94

Data Warehouse Data Lake Optimization Data-driven 94

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52