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. The communication between business units and data professionals is usually incomplete and inconsistent. Introduction to Data Mesh. Source: Thoughtworks.

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 91

Strategy Data Architecture Cost-Benefit Reporting 91

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

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. Five Steps to GDPR/CCPA Compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

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 80

Data Lake Data Governance Data Architecture Machine Learning 80

IBM Big Data Hub

JUNE 30, 2022

The diversity of data types, data processing, integration and consumption patterns used by organizations has grown exponentially. Extend data governance to foster trust in your data by creating transparency, eliminating bias and ensuring explainability for data and insights fueled by machine learning and AI.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

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 66

Data Quality Data Integration Metadata Cost-Benefit 66

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 83

Data Architecture Risk Management Risk Management 83

AWS Big Data

APRIL 19, 2023

The goal of a data product is to solve the long-standing issue of data silos and data quality. Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights.

Technology 80

Technology Data-driven Machine Learning Sales 80

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ).

Data Architecture 77

Data Architecture Data Lake Metadata Data Warehouse 77

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

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

Alation

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Peter James Thomas

AUGUST 18, 2018

Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. This required additional investments in metadata.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

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

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 85

Management Metadata Data Architecture Data Lake 85

Ontotext

FEBRUARY 7, 2024

They have to misallocate resources because 80% of the time the data scientists are busy doing data finding, accessing, cleansing, etc. This also results in the information loss I’ve already mentioned and severely impacts our insight creation and monetizing the data. Last but not least, we need to converge.

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

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. Monitoring Job Metadata. Adding Tests to Reduce Stress.

Testing 157

Testing Metadata Dashboards Statistics 157

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

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. Then, you transform this data into a concise format.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

erwin

DECEMBER 6, 2019

As a foundational component of enterprise data management, DG would reside in such a group. Enterprise Data Management Methodology : DG is foundational to enterprise data management. metadata management, enterprise data architecture, data quality management), DG will be a struggle.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 100

Reporting Data Quality Strategy Data-driven 100

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

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 86

Data Lake Analytics Snapshot Optimization 86

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 102

Data Lake Unstructured Data Data Warehouse Data Quality 102

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 also have controlled vocabularies and better data hygiene with data validation.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

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

TDAN

MAY 14, 2019

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.” The President’s Management Agenda (PMA) lays out a long-term vision for modernizing the Federal Government.

Management 40

Management Data Quality Data Architecture Metadata 40

Ontotext

MAY 30, 2019

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. 6 Linked Data, Structured Data on the Web. Linked Data and Information Retrieval.

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. Cloud data should remove the infrastructure discussions and return attention to business, data, and outcomes.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69