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

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

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

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

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

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

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

Ontotext

MAY 26, 2021

Without all this background knowledge, before computers can perform like humans, they need a machine-readable point of reference that represents “the ground truth”. One of the main uses of the Gold Standard is to train AI systems to identify the patterns in various types of data with the help of machine learning (ML) algorithms.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

AWS Big Data

FEBRUARY 29, 2024

Implement data privacy policies. Implement data quality by data type and source. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail. Link structured and unstructured datasets.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

Insurance 173

Insurance Metadata Data-driven Data Quality 173

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 89

Data Architecture Optimization Data Warehouse Metadata 89

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

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

DataKitchen

SEPTEMBER 21, 2023

.’ It’s not just about playing detective to discover where things went wrong; it’s about proactively monitoring your entire data journey to ensure everything goes right with your data. What is Data in Place? There are multiple locations where problems can happen in a data and analytic system.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

AWS Big Data

MAY 7, 2024

Figure 1: Flow of actions for self-service analytics around data assets stored in relational databases First, the data producer needs to capture and catalog the technical metadata of the data asset. The producer also needs to manage and publish the data asset so it’s discoverable throughout the organization.

Metadata 81

Metadata Data Lake Data Processing Data-driven 81

Octopai

JUNE 19, 2023

In an era where data is often referred to as the new oil, having a well-organized and easily accessible data catalog is no longer a luxury but a necessity as organizations deal with the deluge of too much data (data bloatedness) coming from every system and landscape.

Metadata 98

Metadata Data Governance Measurement Risk Management 98

Ontotext

JULY 15, 2024

It also adds flexibility in accommodating new kinds of data, including metadata about existing data points that lets users infer new relationships and other facts about the data in the graph. Schemas are an example of how the right metadata can add value to the data it describes.

Contextual Data 52

Contextual Data Metadata Data Quality Publishing 52

Alation

NOVEMBER 4, 2021

The practitioner asked me to add something to a presentation for his organization: the value of data governance for things other than data compliance and data security. Now to be honest, I immediately jumped onto data quality. Data quality is a very typical use case for data governance.

Data Governance 94

Data Governance Metadata Data Quality Enterprise 94

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

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

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. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

DataKitchen

OCTOBER 11, 2021

Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. While implementing a DataOps solution, we make sure that the pipeline has enough automated tests to ensure data quality and reduce the fear of failure. Monitoring Job Metadata.

Testing 154

Testing Metadata Dashboards Statistics 154

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

Ontotext

JANUARY 29, 2024

As companies in almost every market segment attempt to continuously enhance and modernize data management practices to drive greater business outcomes, organizations will be watching numerous trends emerge this year. Sometimes, the challenge is that the data itself often raises more questions than it answers.

Strategy 52

Strategy Management Metadata Data-driven 52

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

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. You can see why it’s referred to by number and not by the title.) BCBS 239 and Automated Metadata Management Tools. You may recognize the common thread running through all of these principles: Metadata.

Metadata 89

Metadata Risk Management Business Intelligence Data Governance 89

Alation

NOVEMBER 30, 2022

Solving this problem requires a unified, universally accessible single source of reference. Alation is the leading platform for data intelligence , delivering critical context about data to empower smarter use; to this end, it centralizes technical, operational, business, and behavioral metadata from a broad variety of sources.

Metadata 52

Metadata Data Quality Dashboards Sales 52

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing. For Matching conditions , choose Match all conditions.

Metadata 91

Metadata Sales Data Lake Big Data 91

AWS Big Data

NOVEMBER 6, 2023

Refer to the Configuration reference in the User Guide for detailed configuration values. The following graph describes a simple data quality check pipeline using setup and teardown tasks. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation.

Metrics 111

Metrics Metadata Snapshot Management 111

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. The RDF data model and the other standards in W3C’s Semantic Web stack (e.g.,

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. We also used AWS Lambda for data processing. To query data from REST APIs and other data sources, we used PySpark and JDBC modules.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Alation

JULY 19, 2022

A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms. How Data Catalogs Help Data Scientists Ask Better Questions.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

JUNE 21, 2022

Analysts didn’t just want to catalog data sources, they wanted to include dashboards, reports, and visualizations. Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it? Data engineers want to catalog data pipelines.

Metadata 52

Metadata Data Quality Visualization Data Lake 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 74

Data Strategy Strategy Data Warehouse Prescriptive Analytics 74

Ontotext

MAY 22, 2023

Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. Master data management (MDM), on the other hand, is focused on ensuring data quality and consistency across different systems and applications.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59