erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Is it sensitive data or are there any risks associated with it?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

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. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Alation

SEPTEMBER 7, 2021

This is the last of the 4-part blog series. In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

Data Governance 96

Data Governance Enterprise Data Quality Metadata 96

erwin

OCTOBER 31, 2019

The Regulatory Rationale for Integrating Data Management & Data Governance. Now, as Cybersecurity Awareness Month comes to a close – and ghosts and goblins roam the streets – we thought it a good time to resurrect some guidance on how data governance can make data security less scary.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

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). Strengthen data security. Five Steps to GDPR/CCPA Compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. Data Governance 2.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

erwin

APRIL 15, 2020

In our businesses, it is vital that we work to develop a deeper understanding of the sources, methods and quality of incoming third-party data. This deeper understanding will help us make better decisions about the risks and rewards of using that external data. Data Governance Methods for Data Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

erwin

JANUARY 24, 2019

With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. In data governance terms, an automation framework refers to a metadata-driven universal code generator that works hand in hand with enterprise data mapping for: Pre-ETL enterprise data mapping.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

erwin

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

erwin

FEBRUARY 12, 2021

Managing an organization’s governance, risk and compliance (GRC) via its enterprise and business architectures means managing them against business processes (BP). Governance, risk and compliance are treated as isolated bubbles. Data-related risks are not connected with the data architects/data scientists.

Risk 98

Risk Slice and Dice Management Enterprise 98

erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. To manage not only risk but also to grow and compete effectively requires the ability to deal with both planned and unplanned change.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

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 Digital Transformation Metadata 131

erwin

MARCH 30, 2020

To do this, the consortium will need the ability to automatically scan and catalog the data sources and apply strict data governance and quality practices. Unraveling Data Complexities with Metadata Management. Metadata management will be critical to the process for cataloging data via automated scans.

Metadata 122

Metadata IT Data Governance Data Quality 122

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The foundations of successful data governance The state of data governance was also top of mind.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

CDW Research Hub

MAY 29, 2019

Data governance helps organizations manage their information and answer questions about business performance, allowing them to better understand data, and govern it to mitigate compliance risks and empower information stakeholders. Checklist: Building an Enterprise Data Governance Program.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

IBM Big Data Hub

APRIL 20, 2023

When consumers lose trust in a bank’s ability to manage risk, the system stops working. Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. We’ve seen what follows—financial crises, bailouts, destruction of capital, and losses of jobs.

Risk 73

Risk Risk Management Reporting Metadata 73

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). This also diminishes the value of data as an asset. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

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 94

Strategy Data Architecture Cost-Benefit Reporting 94

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. .

Analytics 108

Analytics Digital Transformation Risk Forecasting 108

DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. Tools affect their risk tolerance.

Testing 147

Testing Data Governance Metadata Visualization 147

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

OCTOBER 16, 2020

IDC defines data intelligence as business, technical, relational, and operational metadata that provides transparency of data profiles, classification, quality, location, context, and lineage, providing people, processes, and technology with trustworthy, reliable data. Subscribe to the erwin Expert Blog.

Internet of Things 145

Internet of Things Data-driven Uncertainty Data Governance 145

IBM Big Data Hub

JUNE 8, 2022

By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage. Ensuring data quality and access within an organization, while establishing and maintaining proper governance processes, is a major struggle for many organizations.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

Cloudera

JUNE 7, 2023

Agencies should inventory, categorize, and label data; protect data at rest and in transit; and deploy mechanisms to detect and stop data exfiltration. Agencies should carefully craft and review data governance policies to ensure all data lifecycle security aspects are appropriately enforced across the enterprise.”

Metadata 79

Metadata Data Lake Optimization Modeling 79

Alation

JULY 15, 2021

Eckerson recommends Alation for companies focused on supporting a wide range of users with a collaborative, social platform: Alation takes a people-oriented approach to the data catalog, seeking to foster collaboration and conversation about data. Data Governance: Access with Compliance Guidance. The Forrester Wave.

Reporting 98

Reporting Data Governance Recreation/Entertainment Metadata 98

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Alation

JUNE 14, 2021

And third is what factors CIOs and CISOs should consider when evaluating a catalog – especially one used for data governance. The Role of the CISO in Data Governance and Security. They want CISOs putting in place the data governance needed to actively protect data. So CISOs must protect data.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Cloudera

MARCH 22, 2023

Luke Roquet recently drilled into the topic of data observability with Mark Ramsey of Ramsey International (RI) to also cover the five pillars (freshness, distribution, volume, schema, and lineage) that describe the quality and reliability of data. And, crucial for a hybrid data platform, it does so across hybrid cloud.

Metrics 85

Metrics Data Governance Cost-Benefit Dashboards 85

erwin

APRIL 9, 2020

As someone who works in data governance and intelligence , I’d like to look at three aspects of disaster planning and business continuity in particular. Understanding the semantic meaning of our data and identifying critical data elements will help us complete our resources-on-hand survey.

Metadata 132

Metadata Risk Data Governance IT 132