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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

MARCH 22, 2022

So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY? This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house. They can better understand data transformations, checks, and normalization.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

IBM Big Data Hub

MARCH 14, 2024

By using decades of database expertise in performance by IBM and combining it with AWS’s scalability, security and governance features, customers can achieve enhanced flexibility, agility and cost efficiency in the cloud. This integration simplifies data management and accelerates the preparation process, directly benefiting clients.

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 94

Data Lake Data Warehouse Data-driven B2B 94

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52