Dataversity

DECEMBER 14, 2020

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

DataOps 59

DataOps Data Pipeline Data Warehouse Big Data 59

IBM Journey to AI blog

SEPTEMBER 5, 2024

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

Precisely

FEBRUARY 9, 2024

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Alation

DECEMBER 13, 2022

So feckless buyers may resort to buying separate data catalogs for use cases like…. Data governance. For example, the researching buyer may seek a catalog that scores 6 for governance, 10 for self-service, 4 for cloud data migration, and 2 for DataOps (let’s call this a {6, 10, 4, 2} profile). Self-service.

DataOps 52

DataOps Data Governance Data Silos Data Scientist 52

Pickl AI

DECEMBER 11, 2024

Understanding Lean Data Management Lean data management revolves around four core principles: accuracy , relevance , accessibility , and efficiency. Accurate data ensures decisions are grounded in reliable information. Relevance prioritises the most critical data for organisational goals, eliminating unnecessary noise.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

Alation

OCTOBER 12, 2021

Enterprise data analytics integrates data, business, and analytics disciplines, including: Data management. Data engineering. DataOps. … In the past, businesses would collect data, run analytics, and extract insights, which would inform strategy and decision-making. Business strategy.

Analytics 52

Analytics Analytics Data Governance DataOps 52