erwin

JUNE 27, 2019

Data modeling, quite simply, describes the process of discovering, analyzing, representing and communicating data requirements in a precise form called the data model. There’s an expression: measure twice, cut once. Empowering of end-user BI/analytics by data source discovery, analysis and integration. .

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

MAY 12, 2023

At Alation, one of our core values is to measure success through customer impact. Alation had such good connectivity to third-party platforms that we wanted to go with them,” wrote Joe Harrington, Director of Business Intelligence at East Idaho Federal Credit Union. “In I am using Alation to aid in our data governance efforts.

Metadata 52

Metadata Data Governance Data-driven Sales 52

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 87

Strategy Data Architecture Cost-Benefit Reporting 87

Alation

MAY 12, 2023

At Alation, one of our core values is to measure success through customer impact. Alation had such good connectivity to third-party platforms that we wanted to go with them,” wrote Joe Harrington, Director of Business Intelligence at East Idaho Federal Credit Union. “In I am using Alation to aid in our data governance efforts.

Metadata 40

Metadata Data Governance Data-driven Sales 40

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 64

Data Quality Data Integration Metadata Cost-Benefit 64

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. And that makes sense.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Creating a data architecture roadmap.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

BI-Survey

FEBRUARY 6, 2020

Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data. These problems become even more obvious when contrasted with modern infrastructures built in the cloud and micro services as well as the challenges caused by exploding data volume and variety. This will and must change.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

CIO Business Intelligence

JULY 5, 2022

Data sovereignty is the ability to maintain legal control and authority of the data within the defined nation’s jurisdictional boundaries. This includes data flows and subsequent processing of that data located within the jurisdictional boundary in question. Data Governance, IT Leadership

Uncertainty 87

Uncertainty Metadata Machine Learning Data Governance 87

CIO Business Intelligence

JUNE 30, 2022

Data sovereignty is the ability to maintain legal control and authority of the data within the defined nation’s jurisdictional boundaries. This includes data flows and subsequent processing of that data located within the jurisdictional boundary in question. Data Governance, IT Leadership

Uncertainty 87

Uncertainty Metadata Machine Learning Data Governance 87

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS.

Data-driven 87

Data-driven Advertising Metadata Data Architecture 87

BI-Survey

MARCH 4, 2022

Due to steadily growing interest in the topic, we conducted this survey to better understand the flavors of data culture within organizations, the hurdles they are facing, the initiatives that are underway and of course the wins that have already been achieved with these measures. DATA LEADERSHIP. DATA GOVERNANCE.

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Don’t You Need to Understand Your Business Information Architecture?

Analytics 68

Analytics Metadata Data Governance Management 68

AWS Big Data

AUGUST 14, 2023

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.

Management 81

Management Risk Measurement Optimization 81

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Grooper

OCTOBER 23, 2019

By measuring performance, they drive improvements through necessary process and workflow changes. It simply takes the right resources and a measured approach to get there. Most companies today are more reactive to information governance. As Peter Drucker so famously said, “If you can’t measure it, you can’t improve it.”

Metrics 59

Metrics Measurement Strategy Optimization 59