Precisely

AUGUST 3, 2023

They reported facing challenges to the success of their data programs — including cost (50%), lack of effective data management tools (45%), poor data literacy/program adoption (41%), and skills shortages (36%) as well as poor data quality (36%).

DataOps 98

DataOps Data Quality Analytics Analytics 98

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

Data Profiling 52

Data Profiling Data Quality Data Governance Data Pipeline 52

Precisely

JUNE 26, 2023

Successful organizations also developed intentional strategies for improving and maintaining data quality at scale using automated tools. Only 46% of respondents rate their data quality as “high” or “very high.” Only 46% of respondents rate their data quality as “high” or “very high.” The biggest surprise?

Data Quality 52

Data Quality Data Silos Data Governance Artificial Intelligence 52

Alation

JANUARY 25, 2022

This is a key component of active data governance. These capabilities are also key for a robust data fabric. Another key nuance of a data fabric is that it captures social metadata. Social metadata captures the associations that people create with the data they produce and consume. The Power of Social Metadata.

DataOps 52

DataOps SQL ML ML 52

Alation

AUGUST 11, 2022

DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. So we have to be very careful about giving the domains the right and authority to fix data quality. Tools became stacks.

Data Warehouse 52

Data Warehouse Data Engineering Data Engineer Data Engineering 52

Dataversity

JUNE 29, 2022

The quality of the data you use in daily operations plays a significant role in how well you will generate valuable insights for your enterprise. You want to rely on data integrity to ensure you avoid simple mistakes because of poor sourcing or data that may not be correctly organized and verified.

Data Observability 98

Data Observability DataOps Data Quality Data Governance 98

Dataversity

JULY 1, 2022

Businesses rely on data to drive revenue and create better customer experiences – […]. A 20-year-old article from MIT Technology Review tells us that good software “is usable, reliable, defect-free, cost-effective, and maintainable. And software now is none of those things.” Today, most businesses would beg to differ.

Analytics 52

Analytics Analytics DataOps Data Pipeline 52

Dataversity

NOVEMBER 15, 2021

DataOps is something that has been building up at the edges of enterprise data strategies for a couple of years now, steadily gaining followers and creeping up the agenda of data professionals. The number of data requests from the business keeps growing […].

DataOps 110

DataOps Analytics Analytics Data Quality 110

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models. Our researchers did it in two days.

AI 111

AI AI DataOps Data Governance 111

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models. Our researchers did it in two days.

AI 103

AI AI DataOps Data Governance 103

Snorkel AI

OCTOBER 31, 2023

However, one of the fundamental ways to improve quality and thereby trust and safety for models with billions of parameters is to improve the training data quality. Higher quality curated data is very important to fine-tune these large multi-task models. Our researchers did it in two days.

AI 52

AI AI DataOps Data Governance 52

Precisely

FEBRUARY 9, 2024

For example: data integration captures the necessary data from diverse sources and makes it available in real time data governance provides positive control over data storage, access, use, etc., That approach assumes that good data quality will be self-sustaining.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Precisely

JULY 15, 2024

Multiple domains often need to share data assets. Quality and formatting may differ with more autonomous domain teams producing data assets, making interoperability difficult and data quality guarantees elusive. Data discoverability and reusability.

Data Governance 72

Data Governance DataOps Data Silos Data Observability 72

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. Evaluate and monitor data quality.

Analytics 52

Analytics Analytics Data Governance DataOps 52

Dataversity

JUNE 23, 2021

The role of the chief data officer (CDO) has evolved more over the last decade than any of the C-suite. The post Speed Up AI Development by Hiring a Chief Data Officer appeared first on DATAVERSITY. Click to learn more about author Jitesh Ghai. As companies plan for a rebound from the pandemic, the CDO […].

AI 59

AI AI DataOps Data Quality 59