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

ODSC - Open Data Science

SEPTEMBER 27, 2023

Data Warehouses Some key characteristics of data warehouses are as follows: Data Type: Data warehouses primarily store structured data that has undergone ETL (Extract, Transform, Load) processing to conform to a specific schema. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

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 208

ETL AI AI Metadata 208

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 Ingestion 162

Pickl AI

NOVEMBER 15, 2023

It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes. Transactional databases, containing operational data generated by day-to-day business activities, feed into the Data Warehouse for analytical processing.

ETL 52

ETL Metadata Business Intelligence Data Analysis 52

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 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks. Later this year, it will leverage watsonx.ai

Machine Learning 168

Machine Learning AI AI Automation 168