TDAN

JUNE 18, 2019

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Strategy 90

CIO Business Intelligence

APRIL 29, 2022

The strategy should put formalized processes in place to quantify the value of different types of information, leveraging the skills of a chief data officer (CDO), who should form and chair a data governance committee. Data has rights and sovereignty. That’s no longer viable, and that fact needs to be faced.

Digital Transformation 122

Digital Transformation Strategy Data-driven Data Strategy 122

Alation

MAY 31, 2023

The state of data governance is evolving as organizations recognize the significance of managing and protecting their data. With stricter regulations and greater demand for data-driven insights, effective data governance frameworks are critical. What is a data architect?

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

JULY 28, 2022

What Are the Biggest Drivers of Cloud Data Warehousing? It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. What Are the Biggest Business Risks to Cloud Data Migration? Data quality /wrangling.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

erwin

OCTOBER 24, 2019

. • Harvesting data – Automate the collection of metadata from various data management silos and consolidate it into a single source. Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.

Metadata 104

Metadata Management Data-driven Data Architecture 104

CIO Business Intelligence

FEBRUARY 28, 2024

And not only do companies have to get all the basics in place to build for analytics and MLOps, but they also need to build new data structures and pipelines specifically for gen AI. What you have to do as a CIO is take an architectural approach and invest in a common platform.” This is imperative for us to do.”

IT 121

IT Consulting Modeling Enterprise 121

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. This is a key component of active data governance.

Metadata 52

Metadata IT Metrics Data-driven 52

Andrew White

JANUARY 9, 2022

Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases. Much of the analytics architecture takes place at the solution architecture level since we should be looking at business process and decision design. – Data (and analytics) governance remains a challenge.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Peter James Thomas

AUGUST 2, 2019

It includes 30 new definitions, some of which have been contributed by people like Tenny Thomas Soman, George Firican, Scott Taylor and and Taru Väre. Data Architecture – Definition (2). Data Catalogue. Data Sourcing. Geospatial Data. Reference Data (contributor: George Firican ).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

Alation

OCTOBER 12, 2021

Like many, the team at Cbus wanted to use data to more effectively drive the business. “Finding the right data was a real challenge,” recalls John Gilbert, Data Governance Manager. The third challenge was around trusting the data. The fourth challenge was around using the data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

BI-Survey

FEBRUARY 6, 2020

Although a common data model consisting of aligned structures and measures is needed for consistency and governance , it will not grant business departments the freedom required to efficiently analyze and interpret data. Data management has always been a challenge for companies.

Reporting 59

Reporting Optimization Enterprise Data Quality 59