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 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.

Data Quality 130

Data Quality Metadata ETL Big Data 130

IBM Journey to AI blog

AUGUST 4, 2023

It’s often described as a way to simply increase data access, but the transition is about far more than that. When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard.

Machine Learning 149

Machine Learning AI AI Automation 149

IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. ” Romain Gaborit, CTO, Eviden, an ATOS business “We’re looking at the potential usage of Large Language Models.

Machine Learning 157

Machine Learning AI AI Metadata 157

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time.

Machine Learning 82

Machine Learning Data Mining Data Scientist Artificial Intelligence 82

Artificial Corner

JUNE 6, 2023

This period also saw the development of the first data warehouses, large storage repositories that held data from different sources in a consistent format. The concept of data warehousing was introduced by Bill Inmon, often referred to as the “father of data warehousing.” This avoids data lock-in from proprietary formats.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52