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?

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Data Governance Strategy Data Quality Metrics 96

Alation

FEBRUARY 3, 2022

DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms. So how does data governance relate to DataOps? Data governance is a key data management process. Continuous Improvement Applied to Data Governance.

Data Governance 98

Data Governance Measurement Metadata Testing 98

erwin

FEBRUARY 13, 2020

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. Data Governance Attitudes Are Shifting. Finding metadata, “the data about the data,” isn’t easy. Why such a heavy lift?

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Alation

FEBRUARY 14, 2023

And a data breach poses more than just a PR risk — by violating regulations like GDPR , a data leak can impact your bottom line, too. This is where successful data governance programs can act as a savior to many organizations. This begs the question: What makes data governance successful? Where do you start?

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

erwin

MARCH 25, 2021

erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, the second webinar focused on “ The Value of Data Governance & How to Quantify It.”.

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

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.

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Data Governance Metadata Testing Reporting 134

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). How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

SEPTEMBER 19, 2019

Data governance isn’t a one-off project with a defined endpoint. Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security. Slow Down, Ask Questions.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

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

Alation

SEPTEMBER 7, 2021

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. So why are organizations not able to scale governance? Meet Governance Requirements.

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Data Governance Risk Data Quality Dashboards 59

CDW Research Hub

AUGUST 12, 2020

What is your organization doing to protect the value of your data? A strong data governance strategy helps ensure that your data is usable, accessible and protected, guaranteeing trust in the quality and consistency of the data. But creating a data governance program is not something you can do overnight.

Data Governance 52

Data Governance Data-driven Dashboards Strategy 52

CIO Business Intelligence

APRIL 1, 2024

Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key.

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

erwin

APRIL 29, 2020

In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates. Business terms and data policies should be implemented through standardized and documented business rules.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Octopai

JUNE 24, 2019

There are a number of scenarios that necessitate data governance tools. Businesses operating within strict industry regulations, utilizing analytics software, and/or regularly consolidating data in key subject areas will find themselves looking into data governance tools to help them achieve their goals.

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Data Governance Metadata Unstructured Data Software 42

Ontotext

FEBRUARY 12, 2024

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations. Not all organizations are ready to make that investment.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Octopai

MAY 15, 2023

Data lineage helps identify redundant or inefficient data integration steps, allowing organizations to streamline their processes and reduce development, maintenance, and operational costs associated with ETL. Data quality costs: Poor data quality can result in significant costs for organizations.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

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 Data Quality Metadata Data Governance 52

CIO Business Intelligence

DECEMBER 19, 2023

Create these six generative AI workstreams CIOs should document their AI strategy for delivering short-term productivity improvements while planning visionary impacts. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

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. Managing metadata should not be a sub-goal of data governance. The Role of Metadata in Data Governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Alation

JULY 15, 2022

And, while change at large organisations is tough, data leaders would be wise to reframe such transformations as business opportunities rather than burdens. Data as an Insight: Operational Transformation. Under GDPR Article 30, the Record of Processing Activity (ROPA) document needs to be created and maintained. The mandate.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

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. Managing metadata should not be a sub-goal of data governance. The Role of Metadata in Data Governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Early on, analysts used data catalogs to find and understand data more quickly.

Management 52

Management Data Quality Metadata Testing 52

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

erwin

JANUARY 17, 2019

Data governance is more important to the enterprise than ever before. It ensures everyone in the organization can discover and analyze high-quality data to quickly deliver business value. A mature and sustainable data governance initiative must include data integration.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63

Alation

JULY 19, 2021

This requires a metadata management solution to enable data search & discovery and data governance, both of which empower access to both the metadata and the underlying data to those who need it. In today’s world, metadata management best practices call for a data catalog. Administrative information.

Metadata 105

Metadata Management Data Governance Machine Learning 105

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Sanjeev Mohan

FEBRUARY 6, 2019

Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance. I ended up writing two documents on data governance. To address client questions about cloud, I wrote a document on GCP. That’s where the bulk of my time was spent.

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Data Analytics Analytics Data Governance Experimentation 49

Alation

MARCH 11, 2022

Leaders must use the data catalog to establish governance principles that clarify best practices for data usage across the enterprise. Documenting key guidance, like ownership rights and consequences, aligns all people on usage expectations. Tip 3: Never, ever skip data governance.

Metadata 52

Metadata Data Governance ROI Data Quality 52

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Alation

MARCH 14, 2023

Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision. Creating a clear process with documented steps will help. For further information, download our whitepaper and eGuide here or book a personalised demo with one of our experts today.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 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

erwin

OCTOBER 29, 2020

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. Earlier this year, erwin conducted a research project in partnership with Dataversity, the 2020 State of Data Governance and Automation.

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89