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

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

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 Artificial Intelligence 52

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

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

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 forecasting.

Analytics 52

Analytics Analytics Data Governance DataOps 52