erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 118

Metadata Snapshot Data Lake Metrics 118

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. Ironically, relational databases only imply relationships between data points by whatever row or column they exist in.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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

Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. So it’s safe to say that organizations can’t reap the rewards of their data without automation.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

erwin

MAY 31, 2019

It’s time to consider data-driven enterprise architecture. The traditional approach to enterprise architecture – the analysis, design, planning and implementation of IT capabilities for the successful execution of enterprise strategy – seems to be missing something … data. That’s right. This is what we call the Mezzo.

Data-driven 104

Data-driven Enterprise Metadata Strategy 104

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

Data Lake 81

Data Lake Data Warehouse Data-driven Optimization 81

erwin

NOVEMBER 6, 2019

erwin released its State of Data Governance Report in February 2018, just a few months before the General Data Protection Regulation (GDPR) took effect. Download Free GDPR Guide | Step By Step Guide to Data Governance for GDPR?. IDC Technology Spotlight, Data Intelligence in Context: Get the report (… it’s free).

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. These changes may include requirements drift, data drift, model drift, or concept drift. I suggest that the simplest business strategy starts with answering three basic questions: What?

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

AWS Big Data

OCTOBER 21, 2024

Data is the most significant asset of any organization. However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture.

Sales 104

Sales Data-driven Data Processing Key Performance Indicator 104

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. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

DECEMBER 4, 2024

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

erwin

NOVEMBER 19, 2020

erwin has once again been positioned as a Leader in the Gartner “2020 Magic Quadrant for Metadata Management Solutions.”. The post erwin Positioned as a Leader in Gartner’s 2020 Magic Quadrant for Metadata Management Solutions for Second Year in a Row appeared first on erwin, Inc.

Metadata 98

Metadata Management Digital Transformation Data Governance 98

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Remember that dark data is the data you have but don’t understand. So how do you find your dark data? Analyze your metadata.

IT 135

IT Metadata Data-driven Data Governance 135

AWS Big Data

DECEMBER 4, 2024

With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. In addition, organizations rely on an increasingly diverse array of digital systems, data fragmentation has become a significant challenge.

Data Integration 97

Data Integration Data Lake Statistics Data-driven 97

erwin

OCTOBER 8, 2020

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way. Then you must bulk load the legacy data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

NOVEMBER 28, 2019

In the era of data-driven business, such perspective is critical. EA also enables a better understanding of change, or impact analysis – which is essential considering the agile, data-driven landscape and its state of flux. Related content: 2019 Gartner Magic Quadrant for Metadata Management Solutions.

Enterprise 145

Enterprise Data-driven Data Governance Metadata 145

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. It helps blur data silos, and empowers data and analytics teams to better understand the context and quality of data. This, in turn, builds trust in data and the decision-making to follow. Improve data discovery.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Constructing A Digital Transformation Strategy: Data Enablement. Probably not.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

Visualization 115

Visualization Data Lake Testing Data Governance 115

erwin

DECEMBER 9, 2024

When it comes to using AI and machine learning across your organization, there are many good reasons to provide your data and analytics community with an intelligent data foundation. For instance, Large Language Models (LLMs) are known to ultimately perform better when data is structured. Lets give a for instance.

Metadata 52

Metadata Data Quality Sales Modeling 52

AWS Big Data

DECEMBER 19, 2024

Organizational data is often fragmented across multiple lines of business, leading to inconsistent and sometimes duplicate datasets. This fragmentation can delay decision-making and erode trust in available data. This solution enhances governance and simplifies access to unstructured data assets across the organization.

Publishing 77

Publishing Unstructured Data Metadata Data-driven 77

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Constructing a Digital Transformation Strategy: How Data Drives Digital.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

datapine

MAY 29, 2019

That’s a fact in today’s competitive business environment that requires agile access to a data storage warehouse , organized in a manner that will improve business performance, deliver fast, accurate, and relevant data insights. One of the BI architecture components is data warehousing. Data integration. Storage of data.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

erwin

JANUARY 14, 2021

When the pandemic first hit, there was some negative impact on big data and analytics spending. Digital transformation was accelerated, and budgets for spending on big data and analytics increased. But data without intelligence is just data, and this is WHY data intelligence is required. Now is the time.

Digital Transformation 143

Digital Transformation Metadata Big Data Data-driven 143

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Data Lineage Tells an Important Origin Story. Who are the data owners?

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

erwin

MARCH 12, 2020

With metadata-driven automation, many DevOps processes can be automated, adding more “horsepower” to increase their speed and accuracy. Data lineage and impact analysis views for ‘data in motion’ also stay up to date with no additional effort. Data Intelligence: Speed and Quality Without Compromise.

Metadata 140

Metadata Digital Transformation Data-driven Enterprise 140

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. However, throughout history, data services have held dominion over their customers’ data.

Data Lake 121

Data Lake Metadata Snapshot Analytics 121

Cloudera

APRIL 18, 2024

All of that technology, though, depends on data to be successful. In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular.

Analytics 110

Analytics Metadata Data Strategy Optimization 110

erwin

DECEMBER 6, 2019

In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture. Creating a Culture of Data Governance.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145