IBM Journey to AI blog

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. .

ETL 243

ETL AI AI Metadata 243

Unite.AI

DECEMBER 5, 2023

Data warehousing is a data management system to support Business Intelligence (BI) operations. These can include structured databases, log files, CSV files, transaction tables, third-party business tools, sensor data, etc. Metadata: Metadata is data about the data. Metadata: Metadata is data about the data.

Metadata 162

Metadata Big Data ETL Data Mining 162

IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. A shared metadata layer, governance to catalog your data and data lineage enable trusted AI outputs.

Metadata 113

Metadata Data Quality AI AI 113

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Efficiently adopt data platforms and new technologies for effective data management.

Data Quality 130

Data Quality Metadata ETL Big Data 130

IBM Journey to AI blog

JANUARY 18, 2023

Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This adds an additional ETL step, making the data even more stale. Metadata plays a key role here in discovering the data assets.

Data Platform 130

Data Platform ETL Metadata Data Discovery 130

IBM Journey to AI blog

JULY 1, 2024

Irina Steenbeek introduces the concept of descriptive lineage as “a method to record metadata-based data lineage manually in a repository.” Extraction, transformation and loading (ETL) tools dominated the data integration scene at the time, used primarily for data warehousing and business intelligence.

ETL 100

ETL Automation Metadata Business Intelligence 100

Marktechpost

JUNE 5, 2024

Analytics, management, and business intelligence (BI) procedures, such as data cleansing, transformation, and decision-making, rely on data profiling. Analysts and developers can enhance business operations by analyzing the dataset and drawing significant insights from it.

Data Quality 113

Data Quality Metadata Data Integration ETL 113