IBM Journey to AI blog

OCTOBER 22, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. This process is known as data integration , one of the key components to improving the usability of data for AI and other use cases, such as business intelligence (BI) and analytics.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

AI 103

AI AI Data Governance Data Pipeline 103

Alation

MAY 24, 2022

This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. The stewardship workbench within the data governance app empowers data stewards to bulk curate data using search and filters.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

phData

AUGUST 10, 2023

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Having model-level data validations along with implementing a data observability framework helps to address the data vault’s data quality challenges.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Read our eBook 4 Ways to Measure Data Quality and learn more about the variety of data and metrics that organizations can use to measure data quality.

Data Quality 52

Data Quality Cloud Data Data Pipeline Data Observability 52

IBM Journey to AI blog

JULY 3, 2024

This approach ensures that data quality initiatives deliver on accuracy, accessibility, timeliness and relevance. Moreover, a data fabric enables continuous monitoring of data quality levels through data observability capabilities, allowing organizations to identify data issues before they escalate into larger problems.

AI 45

AI AI Data Quality Database 45

Precisely

OCTOBER 10, 2024

Data democratization has become a hot topic lately with advances in technology such as AI and machine learning, cloud storage and scalable server capacity, and improved integration. Then add self-service business intelligence tools that are accessible to virtually anyone.

Data Quality 52

Data Quality Data Governance Analytics Analytics 52