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

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

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 72

Metadata Data Governance Management Finance 72

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

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

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

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

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 87

Metadata Data Quality Digital Transformation Data-driven 87

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

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

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

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

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

AWS Big Data

OCTOBER 31, 2024

This is a joint blog post co-authored with Martin Mikoleizig from Volkswagen Autoeuropa. 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. This led to reduced trust in the data.

Digital Transformation 98

Digital Transformation Metadata Manufacturing Data Quality 98

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

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

Octopai

JANUARY 31, 2021

We have identified the top ten sites, videos, or podcasts online that deal with data lineage. Our list of Top 10 Data Lineage Podcasts, Blogs, and Websites To Follow in 2021. Data Engineering Podcast. This podcast centers around data management and investigates a different aspect of this field each week.

Data Governance 83

Data Governance Data Processing Data Quality Metadata 83

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

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

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

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

AWS Big Data

SEPTEMBER 11, 2024

This blog post is co-written with Hardeep Randhawa and Abhay Kumar from HPE. Each file arrives as a pair with a tail metadata file in CSV format containing the size and name of the file. This metadata file is later used to read source file names during processing into the staging layer.

Data Architecture 89

Data Architecture Optimization Data Warehouse Metadata 89

Cloudera

JULY 10, 2024

Observability for your most secure data For your most sensitive, protected data, we understand even the metadata and telemetry about your workloads must be kept under close watch, and it must stay within your secured environment. The post Introducing Cloudera Observability Premium appeared first on Cloudera Blog.

Cost-Benefit 97

Cost-Benefit Metadata Optimization Measurement 97

Ontotext

MAY 26, 2021

This happens through the process of semantic annotation , where documents are tagged with relevant concepts and enriched with metadata , i.e., references that link the content to concepts, described in a knowledge graph. When “reading” unstructured text, AI systems first need to transform it into machine-readable sets of facts.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

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

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. The data you’ve collected and saved over the years isn’t free. Analyze your metadata. Real-time, cloud-based data ingestion and storage.

IT 135

IT Metadata Data-driven Data Governance 135

erwin

MARCH 30, 2020

To marry the epidemiological data to the population data it will require a tremendous amount of data intelligence about the: Source of the data; Currency of the data; Quality of the data; and. Unraveling Data Complexities with Metadata Management. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

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

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

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

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. A slightly different angle to the same problem is discussed in a recent Ontotext blog post. So, they become very data-driven.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

IBM Big Data Hub

JANUARY 17, 2023

These new technologies and approaches, along with the desire to reduce data duplication and complex ETL pipelines, have resulted in a new architectural data platform approach known as the data lakehouse – offering the flexibility of a data lake with the performance and structure of a data warehouse.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

MARCH 3, 2022

In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. The medical insurance company wasn’t hacked, but its customers’ data was compromised through a third-party vendor’s employee. 86% of Experian survey respondents’, for instance, are prioritizing moving their data to the cloud in 2022.

Data Governance 99

Data Governance Enterprise Data Quality Metadata 99

IBM Big Data Hub

MARCH 25, 2022

Automated data enrichment : To create the knowledge catalog, you need automated data stewardship services. These services include the ability to auto-discover and classify data, to detect sensitive information, to analyze data quality, to link business terms to technical metadata and to publish data to the knowledge catalog.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104