IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution.

Data Platform 130

Data Platform ETL Metadata Data Discovery 130

Marktechpost

JULY 18, 2023

Extract, Transform, and Load are referred to as ETL. ETL is the process of gathering data from numerous sources, standardizing it, and then transferring it to a central database, data lake, data warehouse, or data store for additional analysis. Involved in each step of the end-to-end ETL process are: 1.

ETL 52

ETL Data Integration Business Intelligence Automation 52

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 130

Data Quality Metadata Big Data ETL 130

IBM Journey to AI blog

JULY 3, 2024

Your data strategy should incorporate databases designed with open and integrated components, allowing for seamless unification and access to data for advanced analytics and AI applications within a data platform. With an open data lakehouse, you can access a single copy of data wherever your data resides.

Data Quality 112

Data Quality Metadata Business Intelligence AI 112

Flipboard

NOVEMBER 27, 2024

The table only exists in the Data Catalog. This powerful solution opens up exciting possibilities for enterprise data discovery and insights. We encourage you to deploy it in your own environment and experiment with different types of queries across your data assets.

Metadata 146

Metadata Auto-complete Data Discovery ML Engineer 146