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 52

Metadata Management Business Intelligence Data Governance 52

BI-Survey

MARCH 4, 2022

“We are a data-driven company,” is a familiar refrain we hear from business leaders and managers. This is evidence of a fundamental shift in mindset, reflecting the fact that leaders have now understood and internalized the concept of the data-driven enterprise.

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

Ontotext

JANUARY 10, 2024

Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

IBM Big Data Hub

MARCH 25, 2022

To simplify data access and empower users to leverage trusted information, organizations need a better approach that provides better insights and business outcomes faster, without sacrificing data access controls. There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate.

Metadata 107

Metadata Data Quality Data Governance Data Integration 107

Ontotext

NOVEMBER 16, 2023

Data mesh is still in its infancy, and data personas and organizations are craving clarity and specificity. It is critical to be aware of the “why” and “what” and fully understand the role that knowledge graphs play when considering adopting a data mesh strategy. The debate on what constitutes a data mesh rages on.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance. In 2019, the U.K.’s

Data Governance 98

Data Governance Enterprise Data Quality Metadata 98

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Both nodes and edges have associated properties modeled as key-values with primitive data types and are single-valued.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Ontotext

FEBRUARY 12, 2024

Part one of this three-part series discussed the concept of data mesh and explored what it is and why an organization should care. Here, part two provides best practices for data mesh, including practical guidance, challenges, and limitations. Enterprises should identify and adopt specific data mesh elements to achieve velocity.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 81

Management Metadata Data Architecture Data Lake 81

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. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Complexity. Five Steps to GDPR/CCPA Compliance. Govern PII “at rest”.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Alation

MARCH 14, 2023

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. According to Gartner, Inc.

Metadata 100

Metadata Machine Learning Unstructured Data Data Lake 100

Ontotext

JANUARY 26, 2023

In today’s world, we increasingly interact with the environment around us through data. This might include a range of tasks such as searching weather conditions on an app, looking at the temperature at home, reviewing electricity usage on a dedicated web platform, all the way to managing and utilizing data in a professional system at work.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Ontotext

JULY 29, 2021

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? Source: tag.ontotext.com.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Alation

JUNE 30, 2022

As important as the responsibilities of a data curator are to self-service analytics, data curation best practices are still in their infancy. And as new technology allowed for more publishers and created a higher volume of content, information curation thrived. Exploring the New World of Data Curation. Who built it?

Metadata 52

Metadata Data Warehouse Data Quality Data-driven 52

Anmut

OCTOBER 29, 2020

Data governance - who's counting? The role of data governance. 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?

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., internal metadata, industry ontologies, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

AWS Big Data

AUGUST 14, 2023

This post is the first in a series dedicated to the art and science of practical data mesh implementation (for an overview of data mesh, read the original whitepaper The data mesh shift ). Taken together, the posts in this series lay out some possible operating models for data mesh within an organization.

Management 81

Management Risk Measurement Optimization 81

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 327

Management Machine Learning Experimentation Metrics 327

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 84

Data Lake Data Governance Data Architecture Machine Learning 84

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. I try to relate as much published research as I can in the time available to draft a response. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Andrew White

JANUARY 11, 2021

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. Gartner also published the same piece of research for other roles, such as Application and Software Engineering. Some data is more a risk than valuable.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109