erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Manage policies and rules. Five Steps to GDPR/CCPA Compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

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 93

Strategy Data Architecture Cost-Benefit Reporting 93

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Ontotext

DECEMBER 1, 2023

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.

Metadata 78

Metadata Sales Consulting Enterprise 78

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. Automating data capture frees up resources to focus on more strategic and useful tasks.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

IBM Big Data Hub

JUNE 30, 2022

The amazing evolution of technology, cloud and analytics—and what it means for data use — changes quickly, which makes it easy to fall behind if your data strategy and related processes aren’t frequently revisited. Luckily, today’s data management approaches aren’t limited by traditional constraints like location or data patterns.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. The goal of a data product is to solve the long-standing issue of data silos and data quality.

Technology 78

Technology Data-driven Machine Learning Sales 78

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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 67

Data Quality Data Integration Metadata Cost-Benefit 67

Cloudera

AUGUST 30, 2022

That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. As such, managers at different agencies need to sort through multiple systems to make sure these documents are delivered correctly—even though they all apply to the same individuals.”. Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

TDAN

MARCH 17, 2020

Business has a fundamental problem with data quality. In some places it’s merely painful, in others it’s nearly catastrophic. Why is the problem so pervasive? Why does it never seem to get fixed? I believe we’ve been thinking about the problem wrong. It’s time for a fresh look.

Data Quality 59

Data Quality Data Architecture IT Metadata 59

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 87

Management Metadata Data Architecture Data Lake 87

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

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? Ensure data security and compliance.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Ontotext

JANUARY 10, 2024

Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. Finally, I will elaborate on the major design patterns and the requirements for an enterprise-wide knowledge graph management platform. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Ontotext

FEBRUARY 7, 2024

This also results in the information loss I’ve already mentioned and severely impacts our insight creation and monetizing the data. The first element we need for such an architecture is to set our terminology management. Besides a vague understanding, there is little support from management for a real breakthrough.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

TDAN

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Publishing 78

Publishing Data Quality Data Architecture IT 78

TDAN

MAY 14, 2019

Welcome to DAMA Corner, a source of information for data management professionals here in TDAN.com, an industry-leading publication for people interested in learning about data administration, data management disciplines, and best practices.

Management 40

Management Data Quality Data Architecture Metadata 40

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. A DataOps implementation project consists of three steps.

Testing 157

Testing Metadata Dashboards Statistics 157

TDAN

MAY 14, 2019

The President’s Management Agenda (PMA) lays out a long-term vision for modernizing the Federal Government. Cross-Agency Priority (CAP) Goal #2 is “leverage data as a strategic asset to grow the economy, increase the effectiveness of the Federal Government, facilitate oversight, and promote transparency.”

Management 40

Management Data Quality Data Architecture Metadata 40

CIO Business Intelligence

JANUARY 30, 2024

“CIOs are in a unique position to drive data availability at scale for ESG reporting as they understand what is needed and why, and how it can be done.” “The As regulation emerges, the needs for auditable, data-backed reporting is raising the stakes and elevating the role of data in ESG — and hence the [role of the] CIO.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

erwin

DECEMBER 6, 2019

While many organizations are aware of the need to implement a formal data governance initiative, many have faced obstacles getting started. Creating a Culture of Data Governance. Team Resources : Most successful organizations have established a formal data management group at the enterprise level. Data Security.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. times better performance than the self-managed version.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

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. Data Catalog: To access and represent all metadata types. The Power of Social Metadata.

Metadata 52

Metadata IT Metrics Data-driven 52

CIO Business Intelligence

MARCH 9, 2022

Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. They’re comparatively expensive and can’t handle big data analytics. However, they do contain effective data management, organization, and integrity capabilities. Pulling it all together.

Data Lake 118

Data Lake Unstructured Data Data Warehouse Data Quality 118

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 83

Data Lake Analytics Snapshot Optimization 83

TDAN

JULY 2, 2019

The third and final part of the Non-Invasive Data Governance Framework details the breakdown of components by level, providing considerations for what must be included at the intersections. The squares are completed with nouns and verbs that provide direction for meaningful discussions about how the program will be set up and operate.

Data Governance 74

Data Governance Data Quality Data Architecture Metadata 74

Ontotext

FEBRUARY 26, 2024

RDF tends to be more data and metadata -centric. There’s an additional effort around controlled vocabularies, using IRIs to resolve entities, leveraging Linked Open Data to enrich metadata, and managing complex ontologies and taxonomies. You can enrich the data and metadata with Linked Open Data.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Ontotext

MAY 30, 2019

Which are not so different from the concerns of any other enterprise having to deal with data management. And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

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. For this reason, CIOs recommend only migrating data with downstream business value. Lower control.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Ontotext

MAY 30, 2019

In this article, we are bringing science fiction to the semantic technology (and data management) talk to shed some light on three common data challenges: the storage, retrieval and security of information. We will talk through these from the perspective of Linked Data (and cyberpunk). Give us a call !

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75