AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

Data Quality 89

Data Quality Data Lake Data Warehouse Metrics 89

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 98

Metadata Management Data Quality Data Governance 98

Alation

JULY 19, 2021

What Is Metadata? Metadata is information about data. A clothing catalog or dictionary are both examples of metadata repositories. Indeed, a popular online catalog, like Amazon, offers rich metadata around products to guide shoppers: ratings, reviews, and product details are all examples of metadata.

Metadata 105

Metadata Management Data Governance Machine Learning 105

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

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

TDAN

MAY 1, 2024

Well, of course, metadata is data. Our standard definition explicitly says that metadata is data describing other data. The reason I ask it is because we seem to think about and manage metadata as somehow different than “normal data” such as business operations […]

Metadata 52

Metadata Management Data Quality IT 52

Octopai

OCTOBER 18, 2021

First, what active metadata management isn’t : “Okay, you metadata! Now, what active metadata management is (well, kind of): “Okay, you metadata! Data assets are tools. Metadata are the details on those tools: what they are, what to use them for, what to use them with. . Quit lounging around!

Metadata 98

Metadata Management IT Data Quality 98

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

TDAN

MAY 4, 2022

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

Data Quality 114

Data Quality Enterprise Metadata Data Strategy 114

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

erwin

SEPTEMBER 2, 2024

Added data quality capability ready for an AI era Data quality has never been more important than as we head into this next AI-focused era. erwin Data Quality is the data quality heart of erwin Data Intelligence. erwin Data Quality is the data quality heart of erwin Data Intelligence.

Data Quality 52

Data Quality Data Processing Measurement Metadata 52

Cloudera

JANUARY 26, 2024

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. In a good data governance strategy, it is important to define roles that allow the business to limit the level of access that users can have to their strategic data assets.

Metadata 73

Metadata Data Governance Management Finance 73

Ontotext

JUNE 10, 2021

Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter. To be able to automate these operations and maintain sufficient data quality, enterprises have started implementing the so-called data fabrics , that employ diverse metadata sourced from different systems. Such examples are provenance (e.g.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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

Alation

MAY 24, 2022

In a sea of questionable data, how do you know what to trust? Data quality tells you the answer. It signals what data is trustworthy, reliable, and safe to use. It empowers engineers to oversee data pipelines that deliver trusted data to the wider organization. Today, as part of its 2022.2

Data Quality 52

Data Quality Metadata Reporting Metrics 52

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. There’s always more data to handle, much of it unstructured; more data sources, like IoT, more points of integration, and more regulatory compliance requirements.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Cloudera

MARCH 4, 2024

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. In a good data governance strategy, it is important to define roles that allow the business to limit the level of access that users can have to their strategic data assets.

Metadata 52

Metadata Data Governance Management Finance 52

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

DECEMBER 7, 2021

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly. Do we have end-to-end data pipeline control?

Data Quality 52

Data Quality Metadata Testing Data Governance 52

IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

Alation

MARCH 2, 2023

Analysis, however, requires enterprises to find and collect metadata. This data about data is valuable. In fact, Gartner’s “Market Guide for Active Metadata Management” points to “ active metadata management ” as the key to continuous data analysis – which supports smarter human usage and more valuable insights.

Metadata 52

Metadata Marketing IT Data Quality 52

TDAN

DECEMBER 5, 2023

In part one of “Metadata Governance: An Outline for Success,” I discussed the steps required to implement a successful data governance environment, what data to gather to populate the environment, and how to gather the data.

Metadata 52

Metadata Data Governance Data Quality Business Intelligence 52

AWS Big Data

NOVEMBER 13, 2024

Onboard key data products – The team identified the key data products that enabled these two use cases and aligned to onboard them into the data solution. These data products belonged to data domains such as production, finance, and logistics. It highlights the guardrails that enable ease of access to quality data.

Metadata 75

Metadata Data Quality Digital Transformation Data-driven 75

Octopai

JUNE 26, 2020

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

AWS Big Data

OCTOBER 31, 2024

In this post, we discuss how Volkswagen Autoeuropa used Amazon DataZone to build a data marketplace based on data mesh architecture to accelerate their digital transformation. Data quality issues – Because the data was processed redundantly and shared multiple times, there was no guarantee of or control over the quality of the data.

Digital Transformation 98

Digital Transformation Metadata Manufacturing Data Quality 98

IBM Big Data Hub

JULY 28, 2022

Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively. Scalability and elasticity. Public API.

Metadata 56

Metadata Machine Learning Data Quality Statistics 56

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 52

Metadata Data Governance Digital Transformation Data Quality 52

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. Conclusion.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. Additional to that, we are also allowing the metadata inside of Alation to be read into these agents.”

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

Octopai

MARCH 23, 2022

Data lineage tools give you exactly that kind of transparent, x-ray vision into your data quality. Data Supervision. This is why effective data management and governance requires actually appointing people to be data owners and data stewards. Everyone agrees that data quality is important.

Data Quality 98

Data Quality Reporting Modeling Interactive 98

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Why Have a Data Dictionary? #1

Metadata 72

Metadata Enterprise Management Data Warehouse 72

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

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. Ontotext’s GraphDB Give it a try today!

Data Quality 64

Data Quality Testing Reporting Metadata 64

Ontotext

NOVEMBER 23, 2023

While these provide no instructions to a SHACL engine, the use of non-validating characteristics such as sh:name and sh:description can add metadata to your shapes that make them easier to maintain as they scale up. The next step is to get out there and challenge your data quality dragons. Non-validating characteristics.

Data Quality 69

Data Quality Reporting Metadata IT 69

TDAN

AUGUST 31, 2021

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it? These are not new questions, but many people still do not know how to practically […].

Data Quality 105

Data Quality IT Metadata Data Strategy 105

DataKitchen

AUGUST 16, 2024

At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data. Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata.

Marketing 126

Marketing Data Quality Testing Metadata 126

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. This is commonly a data catalog or a marketplace. Let’s take a look.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52