Ontotext

MAY 26, 2021

In much the same way, in the context of Artificial Intelligence AI systems, the Gold Standard refers to a set of data that has been manually prepared or verified and that represents “the objective truth” as closely as possible. 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

Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. Machine Learning Technology. from cognilytica.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 311

Data Quality Metadata Data Governance Publishing 311

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

MAY 2, 2024

Every new dataset and new user adds a little more friction that hits the core metric of the velocity of data and brings it down to zero. Another challenge is the data models that represent how insights and analytics teams see the world. Here we talk about metadata management, catalog of catalogs, and so on.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

IBM Big Data Hub

JULY 6, 2022

Businesses of all sizes, in all industries are facing a data quality problem. 73% of business executives are unhappy with data quality and 61% of organizations are unable to harness data to create a sustained competitive advantage 1. Data observability as part of a data fabric . Instead, Databand.ai

Metadata 56

Metadata Data Quality Snapshot Cost-Benefit 56

Ontotext

DECEMBER 1, 2023

Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

Metadata 78

Metadata Sales Consulting Enterprise 78

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’

Data Governance 145

Data Governance IT Risk Data Lake 145

DataKitchen

AUGUST 3, 2021

Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. You must detect when the model has become stale, and retrain it as necessary. The Marketing team built the first model, but because it was from marketing, the model optimized for CTR and lead conversion.

Marketing 363

Marketing Experimentation Metrics Testing 363

IBM Big Data Hub

APRIL 10, 2023

That is, it should support both sound data governance —such as allowing access only by authorized processes and stakeholders—and provide oversight into the use and trustworthiness of AI through transparency and explainability.

Strategy 86

Strategy Data Architecture Cost-Benefit Reporting 86

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

Alation

MAY 17, 2022

And today, it’s much harder to scale a person than a machine learning model. An enterprise data catalog is one such key asset. Modern data catalogs, such as Alation, use machine learning to improve search results. Beyond sampling, analysts must take care to validate data in other ways.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

IBM Big Data Hub

JUNE 23, 2022

Data governance – Some of the most exciting governance capabilities of the IBM Data fabric include automatically applying metadata to new datasets using machine learning as well as auto-generated data quality assessments and scoring and AI-based dataset recommendations. Providing the semantic.

Enterprise 52

Enterprise Metadata Data Governance Machine Learning 52

Alation

FEBRUARY 13, 2020

In an increasingly noisy data cataloging space, this recognition is a reminder that Alation continues to lead the pack with 100+ customers and a unique solution built on the combination of human collaboration and machine learning. IDC Innovators: Data Intelligence Software Platforms, 2019 Report. Stay tuned!

Machine Learning 52

Machine Learning Big Data Data Governance Digital Transformation 52

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Unlike ingestion processes, data can be transformed as per business rules before loading.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Cloudera

MARCH 22, 2023

Cloudera Data Platform (CDP) is no different: it’s a hybrid data platform that meets organizations’ needs to get to grips with complex data anywhere, turning it into actionable insight quickly and easily. And, crucial for a hybrid data platform, it does so across hybrid cloud.

Metrics 88

Metrics Data Governance Cost-Benefit Dashboards 88

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

MARCH 29, 2022

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. You’ve lost that opportunity if the data has been thrown away. . •

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

IBM Big Data Hub

JUNE 30, 2022

The right data strategy and architecture allows users to access different types of data in different places — on-premises, on any public cloud or at the edge — in a self-service manner. Learn more about how to design and implement a data strategy that takes advantage of a hybrid multicloud landscape.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

Ontotext

MARCH 18, 2020

Consequently, many data leaders today are striving to overcome these barriers by streamlining their enterprise knowledge management processes and practices. The knowledge graph model is one way of doing it and, not surprisingly, it has been in increasing demand in the last decade. Ontotext Knowledge Graph Platform.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Alation

FEBRUARY 3, 2022

For example, previously identified data stewards should become natural candidates for new and related assets as those assets are discovered. And with AI and machine learning helping along the way, less and less work will be required in successive cycles. 7 Steps to Continuous Improvement Data Governance.

Data Governance 98

Data Governance Measurement Metadata Testing 98

Alation

OCTOBER 5, 2021

Without a doubt, no company can achieve lasting profitability and sustainable growth with a poorly constructed data governance methodology. Today, all companies must pursue data analytics, Machine Learning & Artificial Intelligence (ML & AI) as an integral part of any standard business plan.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

AWS Big Data

NOVEMBER 6, 2023

Setup and Teardown tasks It’s common to build workflows that require ephemeral resources, for example an S3 bucket to temporarily store data, databases and corresponding datasets to run quality checks, or a compute cluster to train a model in a machine learning (ML) orchestration pipeline.

Metrics 104

Metrics Metadata Snapshot Management 104

Timo Elliott

JANUARY 5, 2022

Because all that info is sorted in data silos. So, the Chief Data Officer is in fact just someone in your organization who keeps that holistic view, whose job is to insert those data into your future business model. The first one is: companies should invest more in improving their data quality before doing anything else.

Digital Transformation 115

Digital Transformation Machine Learning Enterprise Insurance 115

AWS Big Data

APRIL 19, 2023

However, when a data producer shares data products on a data mesh self-serve web portal, it’s neither intuitive nor easy for a data consumer to know which data products they can join to create new insights. This is especially true in a large enterprise with thousands of data products.

Technology 83

Technology Data-driven Machine Learning Sales 83

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 83

Data Lake Data Governance Data Architecture Data Warehouse 83

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Model development. Model governance.

Modeling 195

Modeling Machine Learning Testing Metrics 195

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 85

Enterprise Data Warehouse Snapshot Cost-Benefit 85

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

Ontotext

JUNE 22, 2023

On top of that, data is sometimes unreliable , and inaccurate or missing metadata makes it hard to decide which information to trust. The data model can adapt effortlessly to the iterative development of use cases across different therapeutic areas.

Metrics 52

Metrics Statistics Visualization Metadata 52

Jet Global

JULY 2, 2019

Ungoverned or uncatalogued data can leave businesses vulnerable both in terms of data quality (and organizational trust in that data), as well as in terms of security, regulatory, and compliance risks.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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 93

Metadata Management Data Quality Data Governance 93