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

DataRobot Blog

AUGUST 16, 2022

The survey asked companies how they used two overlapping types of tools to deploy analytical models: Data operations (DataOps) tools, which focus on creating a manageable, maintainable, automated flow of quality-assured data. If deployment goes wrong, DataOps/MLOps can even help solve the problem. Survey Questions.

DataOps 52

DataOps AI AI ML 52

IBM Journey to AI blog

OCTOBER 22, 2024

The data universe is expected to grow exponentially with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase pressure to manage cloud costs efficiently and complicate governance of AI and data workloads.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

IBM Journey to AI blog

SEPTEMBER 5, 2024

Master data management (MDM) MDM tools keep an organization’s master data—such as customer, product or supplier information—consistent and up-to-date across systems and departments, preventing data silos and providing a unified view of critical data entities.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

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

Precisely

JUNE 26, 2023

Business needs and challenges 77% of respondents say data-driven decision-making is the top goal of their data programs – and they’re also looking to accelerate those processes. Those who have already made progress toward that end have used advanced analytics tools that work outside of their application-based data silos.

Data Quality 52

Data Quality Data Silos Data Governance Analytics 52

Pickl AI

DECEMBER 11, 2024

Efficiency emphasises streamlined processes to reduce redundancies and waste, maximising value from every data point. Common Challenges with Traditional Data Management Traditional data management systems often grapple with data silos, which isolate critical information across departments, hindering collaboration and transparency.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52