Alation

JANUARY 9, 2023

But data leaders must work quickly, and use the right tools, to understand, manage, and protect data while complying with related regulations and standards. The Increasing Focus On Data Risk Management. The Australian Prudential Regulation Authority (APRA) released nonbinding standards covering data risk management.

Risk Management 52

Risk Management Risk Management Metadata 52

Alation

MARCH 2, 2023

Analysis, however, requires enterprises to find and collect metadata. 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. What Is Active Metadata Management?

Metadata 52

Metadata Marketing IT Data Quality 52

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. Case Introduction In this article we will take the example of a data governance office that wants to control access to metadata objects in the company’s central data repository.

Metadata 52

Metadata Data Governance Management Finance 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. I expect to see the following data and knowledge management trends emerge in 2024.

Strategy 52

Strategy Management Metadata Data-driven 52

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. and later supports the Apache Iceberg framework for data lakes. The Iceberg catalog stores the metadata pointer to the current table metadata file.

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

IBM Big Data Hub

JUNE 12, 2023

This post provides a view of how these layers should be managed and implemented across different teams. Public cloud support: Many CSPs use hyperscalers like AWS to host their 5G network functions, which requires automated deployment and lifecycle management. It also takes care of the major upgrades on the network function.

Testing 71

Testing Data Processing Metadata Management 71

erwin

NOVEMBER 19, 2020

erwin has once again been positioned as a Leader in the Gartner “2020 Magic Quadrant for Metadata Management Solutions.”. The post erwin Positioned as a Leader in Gartner’s 2020 Magic Quadrant for Metadata Management Solutions for Second Year in a Row appeared first on erwin, Inc.

Metadata 98

Metadata Management Digital Transformation Data Governance 98

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 76

Risk Modeling Management Metadata 76

erwin

FEBRUARY 28, 2024

Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Examples of complementary technologies include technology for data warehouse automation, change data capture and master data management. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

IBM Big Data Hub

OCTOBER 4, 2022

According to Gartner 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted.” Challenges around managing risk. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle.

Metadata 102

Metadata Risk Risk Management Experimentation 102

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. Then there’s unstructured data with no contextual framework to govern data flows across the enterprise not to mention time-consuming manual data preparation and limited views of data lineage. They might have 300 applications, with 50 different databases and a different schema for each one.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

IBM Big Data Hub

MAY 9, 2023

There are 3 main reasons why organizations struggle with adopting AI: a lack of confidence in operationalizing AI, challenges around managing risk and reputation, and scaling with growing AI regulations. This solution is designed to include everything needed to develop a consistent transparent model management process.

Metadata 77

Metadata Risk Experimentation Dashboards 77

IBM Big Data Hub

DECEMBER 16, 2022

At the same time, governments around the world are continuously evaluating and implementing new AI guidelines and AI regulation frameworks. The post The importance of governance: What we’re learning from AI advances in 2022 appeared first on Journey to AI Blog. Advances across AI technology are happening quickly.

Uncertainty 117

Uncertainty Metadata Modeling Data Collection 117

IBM Big Data Hub

APRIL 10, 2023

A well-designed data foundation can also be a game-changer when it comes to managing ESG (environmental, social, and governance) commitments. Reporting on all three pillars of ESG should begin with evaluating your framework and the kinds of data needed to be included to support a credible and transparent disclosure report.

Strategy 93

Strategy Data Architecture Cost-Benefit Reporting 93

erwin

JANUARY 30, 2020

However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions. erwin Named a Leader in Gartner 2019 Metadata Management Magic Quadrant. Top Five: Benefits of An Automation Framework for Data Governance. Stop Wasting Your Time. appeared first on erwin, Inc.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

Ontotext

MAY 2, 2024

These models are as important to companies as their frontline products and determine how data is managed, consumed, combined, joined, and analyzed. Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources. Use case-driven growth How do we take data and create value?

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Alation

APRIL 18, 2023

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. Data profiling helps organizations holistically comprehend their data landscapes, as it documents data assets and dependencies, including data lineage , metadata, and data relationships.

IT 52

IT Data Quality Metadata Data Governance 52

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We pioneered the world’s first machine learning data catalog, centralizing technical, operational, business and behavioral metadata into one place. Activating metadata with Alation Anywhere.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

AWS Big Data

SEPTEMBER 13, 2023

However, managing, integrating, and authenticating the processing framework (Apache Spark Structured Streaming) with the ingesting framework (Kafka) poses significant challenges, necessitating a managed and serverless framework. This table acts as a metadata layer for the data.

Management 87

Management Data Processing Interactive Metadata 87

Ontotext

JUNE 10, 2021

This is a graph of millions of edges and vertices – in enterprise data management terms it is a giant piece of master/reference data. Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter. open-world vs. closed-world assumptions).

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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. equivalent of GDPR] will not become effective until 2020, we believe that new developments in GDPR enforcement may influence the regulatory framework of the still fluid CCPA.”.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The active metadata helix Indeed, automation was on everyone’s minds. We couldn’t agree more.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

erwin

MAY 31, 2019

The typical notion is that enterprise architects and data (and metadata) architects are in opposite corners. Therefore, most frameworks fail to address the distance. So we created a set of methods, frameworks and reference architectures that address all these different disciplines, strata and domains.

Data-driven 104

Data-driven Enterprise Metadata Strategy 104

erwin

MARCH 12, 2020

Almost 70 percent of CEOs say they expect their companies to change their business models in the next three years, and 62 percent report they have management initiatives or transformation programs underway to make their businesses more digital, according to Gartner. Just like with cars, more horsepower in DevOps translates to greater speed.

Metadata 140

Metadata Digital Transformation Data-driven Enterprise 140

Ontotext

OCTOBER 12, 2023

LLMs] call into question a fundamental tenet of Data Management: that in order to address non-trivial information needs, the first step is to explicitly structure data in order to lift them from the ambiguous swamp of our human language. As with any technology, the thing that matters most is the knowledge we manage to transfer via it.

Modeling 75

Modeling Recreation/Entertainment Data Processing Metadata 75

Ontotext

NOVEMBER 4, 2021

Given all the advantages of the RDF model regarding enterprise data management, one no longer has good arguments why to bother with LPG at all. On the other hand, LPGs lack many features that are an absolute must for enterprise data management, e.g., standard schema language. Read on and watch the webinars to get convinced.

Metadata 98

Metadata Visualization Modeling Enterprise 98

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way. Enters data quality management. What Is Data Quality Management (DQM)? Why Do You Need Data Quality Management? Table of Contents.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

MARCH 14, 2023

A data strategy is a long-term plan setting out the technologies, processes, people, and rules that manage data. A well-executed data strategy ensures best practice in data management – and is therefore key for defence partners in meeting the outcomes and rules set out here. What is a data strategy? Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Alation

DECEMBER 15, 2022

August 2017: Alation debuts as a leader in the Gartner MQ for Metadata Management Solutions. August 2018: Gartner names Alation a 2X Leader in the MQ for Metadata Management Solutions. October 2019: Gartner names Alation a 3X Leader to the Gartner Magic Quadrant for Metadata Management Solutions.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

Alation

NOVEMBER 15, 2021

Most people close to data management are aware of the EDM Council. This highly respected standards & training organization was “created to elevate the practice of data management as a business and operational priority.” A key part of the framework is the definition of 14 key controls and capabilities. Autonomous Policy Bots.

Management 52

Management Testing Metadata Consulting 52

Ontotext

JULY 13, 2023

This blog gives an overview of a product bundling that relies on two industry leaders that help you do this. Knowledge graphs allow organizations to enrich it with semantic metadata, making it ready to be used across teams and enterprise systems. Partner with PoolParty and GraphDB to build knowledge graphs for enterprise applications.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

erwin

JANUARY 24, 2019

Organizations are responsible for governing more data than ever before, making a strong automation framework a necessity. But what exactly is an automation framework and why does it matter? With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

IBM Big Data Hub

JUNE 8, 2022

Here are a few common data management challenges: Regulatory compliance on data use. The challenges outlined above demand a data strategy that includes a governance and privacy framework. Furthermore, to help the framework scale across the enterprise, it needs to be automated.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

Alation

FEBRUARY 3, 2022

The goal of DataOps is to create predictable delivery and change management of data and all data-related artifacts. Data governance is a key data management process. Establish Governance Framework. Subscribe to Alation's Blog. So how does data governance relate to DataOps? For many, this may be a new way of thinking.

Data Governance 98

Data Governance Measurement Metadata Testing 98

Cloudera

JULY 15, 2021

This blog post provides an overview of best practice for the design and deployment of clusters incorporating hardware and operating system configuration, along with guidance for networking and security as well as integration with existing enterprise infrastructure. Introduction and Rationale. Role allocation.

Data Processing 96

Data Processing Metadata Testing Management 96

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. manage basic typedefs & classifications. manage entities (instances of typedefs). manage relations between entities.

Data Governance 93

Data Governance Metadata Enterprise Data Processing 93

Alation

MAY 24, 2022

The Open Data Quality Framework, or ODQF, describes the complete set of product capabilities that are included as part of this initiative. I sat down with Peter Wang, Alation’s senior product manager and data quality lead, to learn more about the initiative, product framework, and how data users at all levels will benefit.

Data Quality 52

Data Quality Metadata Reporting Metrics 52