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

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

erwin

DECEMBER 3, 2020

Being able to integrate all data touchpoints, including erwin DM for data modeling, Denodo for data visualization, and Jira for ticketing, has been key. Using erwin DI, customers are powering comprehensive data governance initiatives, cloud migration and other massive digital transformation projects.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 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)? Data Catalog and Master Data Management. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

Rocket-Powered Data Science

FEBRUARY 15, 2023

A business-disruptive ChatGPT implementation definitely fits into this category: focus first on the MVP or MLP. Love thy data: data are never perfect, but all the data may produce value, though not immediately. Clean it, annotate it, catalog it, and bring it into the data family (connect the dots and see what happens).

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

TDAN

SEPTEMBER 7, 2022

Fit for Purpose data has been a foundational concept of Data Governance for as long as I’ve been in the field…so that’s 10-15 years now. Most data quality definitions take Fit-for-Purpose as a given.

Data Governance 59

Data Governance Data Quality Metadata Management 59

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

CIO Business Intelligence

MARCH 4, 2024

Harmonizing these data sets with centralized enterprise data faces increasing challenges as shifts to data definitions, schema, and architecture require constant central data team efforts. To deliver a cohesive data strategy, seamless data access and sharing requires the breaking down of data silos.

Insurance 82

Insurance Strategy Data Governance Data Integration 82

Alation

FEBRUARY 13, 2020

These are all good questions and a logical place to start your data cataloging journey. This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

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

MARCH 11, 2022

A data catalog with a Behavioral Analysis Engine will measure human behavior around data to locate your most valuable and actionable data. This data about data, AKA metadata , is an essential layer of your new meshy fabric. Again, a data catalog can automate the tedium of compliance at scale.

Metadata 52

Metadata Data Governance ROI Data Quality 52

Cloudera

SEPTEMBER 15, 2022

What is a data fabric? Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.” The data fabric provides direct support for the first element of the architecture — linking the distributed source data into the hybrid, multi-cloud environment. .

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

CDW Research Hub

MAY 29, 2019

Start meeting, strategizing, and creating the justification for data governance. Agree on a definition of data governance for organization. Identify where your company currently stands in data governance, while keeping in mind your master data management plan, data quality goals, data stewardship, data lineage, and metadata.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

erwin

APRIL 15, 2020

In regard to third-party data, we should ask ourselves: How was the data created? Does the definition (description, classification, allowable range of values, etc.) of incoming, individual data elements match our internal definitions of those data elements? What formulas were used?

Data Governance 134

Data Governance Metadata Testing Reporting 134

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

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

DataRobot Blog

MAY 10, 2022

With this definition of model risk, how do we ensure the models we build are technically correct? The first step would be to make sure that the data used at the beginning of the model development process is thoroughly vetted, so that it is appropriate for the use case at hand. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Smart DwH Mover helps in accelerating data warehouse migration.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Alation

OCTOBER 5, 2021

For example, it may be helpful to track specific daily activities or benchmarks for all data-related processes. Numerous committees spend hours deliberating over every word in a Glossary definition, then 6 months down the line leaders complain there hasn’t been enough value shown. Roadblock #2: Data problems and inconsistencies.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data. In terms of data lineage, they offer an excellent definition here. .

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Anmut

OCTOBER 29, 2020

This large gap between reported figures raises tough questions on the reliability of COVID-19 tracking data. In dealing with situations like pandemic data, how important are aspects of data governance such as standardised definitions? As a result, concerns of data governance and data quality were ignored.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

Ontotext

NOVEMBER 9, 2023

While everyone may subscribe to the same design decisions and agree on an ontology, there may be differences in the data quality. In such situations, data must be validated. Instead, they provide metadata about the shapes. Sometimes there is no room for error. In such an environment, most tools relied on workarounds.

Data Quality 64

Data Quality Testing Reporting Metadata 64

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

TDAN

APRIL 2, 2019

If you are just starting out and feel overwhelmed by all the various definitions, explanations, and interpretations of data governance, don’t be alarmed. Even well-seasoned data governance veterans can struggle with the definition and explanation of what they do day to day.

Data Governance 72

Data Governance Data Quality Metadata Data Strategy 72

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

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? Make sure that the value of data increases over time.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Ontotext

MARCH 8, 2023

Solution Outcomes: A semantic recommendation service that is beating accuracy benchmarks and replacing manual processes aggregating content – that is supporting higher-quality, more advanced, and targeted recommendations with clear reasons. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Jet Global

JULY 2, 2019

Ungoverned or uncatalogued data can leave businesses vulnerable both in terms of data quality (and organizational trust in that data), as well as in terms of security, regulatory, and compliance risks.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

TDAN

APRIL 30, 2019

Roles and responsibilities are the backbone of a successful information or data governance program. To operate an efficient and effective program and hold people formally accountable for doing the “right” thing at the “right” time, it requires the definition and deployment of roles that are appropriate for the culture of the organization.

Data Governance 79

Data Governance Data Quality IT Metadata 79

Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Alation

OCTOBER 18, 2022

In the modern data stack, dbt is a key tool to make data ready for analysis. Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Improve data analysis accuracy.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Alation

MAY 31, 2023

How is the data architecture role evolving? As data governance gains importance, data architects must work with data stewards and owners to establish policies, develop governance frameworks, implement data quality programs, and provide guidance to other data professionals.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

AUGUST 11, 2022

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Jim Harris

MAY 5, 2017

Spelling, pronunciation, and examples of usage are included in the dictionary definition of a word, which is a good example of one of the many uses of metadata, namely to provide a definition, description, and context for data. In practice, I haven’t encountered a metadata dictionary that could deliver on that promise.

Metadata 61

Metadata Publishing Management IT 61