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

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?

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

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. How erwin Can Help. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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

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

CIO Business Intelligence

APRIL 1, 2024

Deloitte 2 meanwhile found that 41% of business and technology leaders said a lack of talent, governance, and risks are barriers to broader GenAI adoption. Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Assess your readiness.

Data Lake 130

Data Lake Consulting Uncertainty Risk 130

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

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 142

Digital Transformation Unstructured Data Machine Learning Risk Management 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

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

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

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.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

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

JULY 15, 2022

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

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. Is it sensitive or are there any risks associated with it?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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

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

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

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. Is it sensitive or are there any risks associated with it?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

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

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. A product needs to balance the investment of resources against the risks of moving forward without a full understanding of the data landscape. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

Ontotext

MARCH 18, 2020

To access this knowledge, enterprises need tools to help them integrate the data scattered across the organization. The third challenge is how to combine data management with analytics. In today’s business climate, data quality and governance are no longer enough. Ontotext Knowledge Graph Platform.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

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

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

Andrew White

NOVEMBER 14, 2022

How is it that trying to be aware of all your data is the first step to working out what data (or analytic) actually needs to be governed first? Catalog are useful in a small number of data governance programs only. By documenting an organizations data issues. Or second and tenth? Maybe much later.

Data Integration 52

Data Integration Technology Data Governance Analytics 52

Alation

FEBRUARY 13, 2020

Important evaluation features include capabilities to preview a dataset, see all associated metadata, see user ratings, read user reviews and curator annotations, and view data quality information. Benefits of a Data Catalog. Improved data efficiency. Improved data context. Reduced risk of error.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy. But it’s still not easy.

Data Governance 82

Data Governance Metadata Data-driven Enterprise 82

Domino Data Lab

OCTOBER 1, 2020

It allows compliance to not only govern what information can be accessed, but also to audit and have visibility into how the data is actually being accessed – when, by who, through what tools, how much data was viewed, etc. So what does this look like?

Enterprise 105

Enterprise Metadata Cost-Benefit Data Processing 105

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

Enterprise 81

Enterprise Data Integration Data Quality Contextual Data 81

IBM Big Data Hub

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

Cost-Benefit 84

Cost-Benefit Metadata Data Governance Modeling 84

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

erwin

MARCH 21, 2019

With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Historically, BPM didn’t necessarily have to be tied to an organization’s data governance initiative. Choosing a BPM Tool: An Overview. Silo Buster.

Modeling 75

Modeling Metadata IT Data Governance 75

erwin

OCTOBER 24, 2019

Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104