erwin

JUNE 19, 2020

Despite the similarities in name, there are a number of key differences between an enterprise architecture and solutions architecture. Much like the differences between enterprise architecture (EA) and data architecture, EA’s holistic view of the enterprise will often see enterprise and solution architects collaborate.

Enterprise 94

Enterprise Data Architecture Strategy Data Governance 94

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

Anmut

APRIL 6, 2023

How do you do a Data Maturity Assessment? What does a Data Maturity Assessment Measure? What makes a Good Data Maturity Assessment? What is a Data Maturity Assessment? The definition of a data maturity assessment is a measurement of the reliability, effectiveness, and efficiency of an organisation’s data management.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 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?

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

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 113

Digital Transformation Strategy Data-driven Data Strategy 113

Anmut

MARCH 24, 2022

In this post, we’ll explore what a data landscape is, why it’s so important, and how you can design and build a data landscape that supports your business goals. What is a data landscape? The definition of data landscape differs depending on the context and who you ask. Focus on value.

ROI 52

ROI Measurement Data-driven Data Transformation 52

TDAN

JUNE 18, 2019

Most organizations agree that they have data issues, categorized as data quality. Organizations typically define the scope of their data problems by their current (known) data quality issues (symptoms). However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Strategy 90

AWS Big Data

JUNE 29, 2023

With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers. In many organizations, one or multiple Amazon Redshift data warehouses run daily for data and analytics purposes.

Data Warehouse 59

Data Warehouse Dashboards Testing Visualization 59

AWS Big Data

APRIL 24, 2023

It allows you to access diverse data sources, build business intelligence dashboards, build AI and machine learning (ML) models to provide customized customer experiences, and accelerate the curation of new datasets for consumption by adopting a modern data architecture or data mesh architecture.

Data Lake 77

Data Lake Data Governance Cost-Benefit Machine Learning 77

TDAN

JUNE 30, 2020

About a week ago, I was teaching a data modeling class, and an attendee asked me to explain the concept of a data catalog. Like a lot of hype-related terms in IT, there is more than one definition. However, I had recently read the book, The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics by […].

Modeling 52

Modeling Analytics Data Architecture IT 52

Jim Harris

JANUARY 1, 2016

No matter how uncomfortable these discussions may be at times, they are essential to evaluating the potential ROI of data quality improvements, defining data quality standards, and most importantly, providing a working definition of success. Six blog posts related to Inebriate : Why isn’t our data quality worse?

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. The Data Catalog organizes this information in the form of metadata tables and databases.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

Sisense

JULY 6, 2020

EDM covers the entire organization’s data lifecycle: It designs and describes data pipelines for each enterprise data type: metadata, reference data, master data, transactional data, and reporting data. Data governance is the foundation of EDM and is directly related to all other subsystems.

Enterprise 98

Enterprise Management Data Architecture Strategy 98

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

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? Clearly, moving data isn’t free.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

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. All of that is fascinating to us and my team is definitely working on this,” she adds. This is imperative for us to do.”

IT 112

IT Consulting Modeling Enterprise 112

Cloudera

NOVEMBER 18, 2020

The technological linchpin of its digital transformation has been its Enterprise Data Architecture & Governance platform. It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery.

Internet Publishing and Broadcasting 119

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 119

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

Jen Stirrup

MARCH 29, 2023

SAP helps to solve this search problem by offering ways to simplify business data with a solid data foundation that powers SAP Datasphere. It fits neatly with the renewed interest in data architecture, particularly data fabric architecture. They fail to get a grip on their data.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

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

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

Alation

DECEMBER 22, 2022

The team’s adoption of a data catalog made it possible for the North Pole to deliver a great holiday season despite all the obstacles. see across the workshop’s many many different data sources. And they finally had common definitions for key terms like “naughty” and “nice.” Data Demand Surges at the North Pole.

Dashboards 52

Dashboards Manufacturing Data Architecture Reporting 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

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 88

Data Lake Data Warehouse Data-driven B2B 88

IBM Big Data Hub

JULY 5, 2023

Their fast adoption meant that customers soon lost track of what ended up in the data lake. And, just as challenging, they could not tell where the data came from, how it had been ingested nor how it had been transformed in the process. Data governance remains an unexplored frontier for this technology.

Data Lake 66

Data Lake Metadata Cost-Benefit Data Warehouse 66

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. Fact-Based Decision-Making Requires Trusted And Managed Data.

Reporting 59

Reporting Optimization Enterprise Data Quality 59