Precisely

DECEMBER 12, 2023

It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation. But with all that data, there are new challenges that may prompt you to rethink your data observability strategy. Learn more here.

Data Observability 52

Data Observability Data Quality Data Pipeline Machine Learning 52

IBM Journey to AI blog

DECEMBER 16, 2022

It seamlessly integrates with IBM’s data integration, data observability, and data virtualization products as well as with other IBM technologies that analysts and data scientists use to create business intelligence reports, conduct analyses and build AI models.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

IBM Journey to AI blog

FEBRUARY 26, 2024

That’s why data pipeline observability is so important. Data lineage expands the scope of your data observability to include data processing infrastructure or data pipelines, in addition to the data itself.

Data Pipeline 101

Data Pipeline Data Governance Data Engineering Data Engineer 101

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

ODSC - Open Data Science

MAY 16, 2023

The mesh approach allows for more streamlined data-driven decisions and processes within specific departments and puts responsibility in the hands of the people who actually use the information. AI in Data Observability Automation has steadily become more common in data management software, but it’ll reach new heights in 2023.

Database 98

Database Data Lakes Data Science Data Observability 98

Alation

DECEMBER 7, 2021

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it.

Data Quality 52

Data Quality Data Observability Data Pipeline Data Profiling 52

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.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

ODSC - Open Data Science

JANUARY 9, 2024

Now that we’re in 2024, it’s important to remember that data engineering is a critical discipline for any organization that wants to make the most of its data. These data professionals are responsible for building and maintaining the infrastructure that allows organizations to collect, store, process, and analyze data.

Data Engineering 97

Data Engineering Data Engineer Data Engineering Data Engineering 97

Alation

FEBRUARY 8, 2022

While data fabric takes a product-and-tech-centric approach, data mesh takes a completely different perspective. Data mesh inverts the common model of having a centralized team (such as a data engineering team), who manage and transform data for wider consumption. But why is such an inversion needed?

Data Governance 52

Data Governance Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. This provides end-to-end support for data engineering and MLOps workflows.

Machine Learning 134

Machine Learning Machine Learning ML ML 134