erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. What Is Metadata? Analyst firm Gartner defines metadata as “information that describes various facets of an information asset to improve its usability throughout its life cycle. It is metadata that turns information into an asset.”.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

O'Reilly on Data

DECEMBER 12, 2023

If the output of a model can’t be owned by a human, who (or what) is responsible if that output infringes existing copyright? In an article in The New Yorker , Jaron Lanier introduces the idea of data dignity, which implicitly distinguishes between training a model and generating output using a model.

Modeling 335

Modeling Sales Software Statistics 335

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. Smart content includes labeled (tagged, annotated) metadata (TAM).

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter. Graph Databases vs Relational Databases.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

AWS Big Data

JULY 29, 2024

In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient. You will learn about an open-source solution that can collect important metrics from the Iceberg metadata layer. This ensures that each change is tracked and reversible, enhancing data governance and auditability.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

erwin

OCTOBER 24, 2019

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. And to truly understand it , you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

CIO Business Intelligence

JANUARY 9, 2025

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. The commodity effect of LLMs over specialized ML models One of the most notable transformations generative AI has brought to IT is the democratization of AI capabilities.

Software 128

Software Enterprise Key Performance Indicator Machine Learning 128

O'Reilly on Data

JUNE 14, 2024

Generative AI models are trained on large repositories of information and media. They are then able to take in prompts and produce outputs based on the statistical weights of the pretrained models of those corpora. The newest Answers release is again built with an open source model—in this case, Llama 3.

Metadata 299

Metadata Publishing Data-driven Modeling 299

AWS Big Data

MAY 2, 2025

They consist of: A data sample of the documents you want to index. A pipeline of processors that apply transforms on ingested documents. An index constructed from the processed documents. This template requires us to select a text embedding model. Ingest flows are created to enrich data as its added to an index.

Machine Learning 92

Machine Learning Visualization Dashboards Metadata 92

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

MARCH 17, 2020

Teams need to urgently respond to everything from massive changes in workforce access and management to what-if planning for a variety of grim scenarios, in addition to building and documenting new applications and providing fast, accurate access to data for smart decision-making. Enterprise Architecture & Business Process Modeling.

Data Governance 138

Data Governance Enterprise Modeling Metadata 138

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. They have documented 200 business processes in this way.

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

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

CIO Business Intelligence

NOVEMBER 27, 2024

Data quality for AI needs to cover bias detection, infringement prevention, skew detection in data for model features, and noise detection. Not all columns are equal, so you need to prioritize cleaning data features that matter to your model, and your business outcomes. asks Friedman.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

erwin

NOVEMBER 6, 2019

Often these enterprises are heavily regulated, so they need a well-defined data integration model that will help avoid data discrepancies and remove barriers to enterprise business intelligence and other meaningful use. The post Metadata Management, Data Governance and Automation appeared first on erwin, Inc.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

Rocket-Powered Data Science

SEPTEMBER 20, 2021

They realized that the search results would probably not provide an answer to my question, but the results would simply list websites that included my words on the page or in the metadata tags: “Texas”, “Cows”, “How”, etc. The semantic layer bridges the gaps between the data cloud, the decision-makers, and the data science modelers.

Data Science 286

Data Science Forecasting Business Intelligence Sales 286

CIO Business Intelligence

APRIL 8, 2025

These strategies, such as investing in AI-powered cleansing tools and adopting federated governance models, not only address the current data quality challenges but also pave the way for improved decision-making, operational efficiency and customer satisfaction. Data fabric Metadata-rich integration layer across distributed systems.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

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

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In this post: What Is a Data Model? Why Is Data Modeling Important? What Is a Data Model?

Modeling 111

Modeling Cost-Benefit Visualization Data Warehouse 111

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling.

Modeling 98

Modeling Metadata Data Governance Visualization 98

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. There is no GitHub for data, though we are starting to see version control projects for machine learning models, such as DVC. Automation is more than model building. Toward a sustainable ML practice.

Machine Learning 279

Machine Learning Software Metadata Testing 279

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

erwin

FEBRUARY 12, 2021

Shockingly, a lot of organizations, even today, manage this through, either homemade tools or documents, checklists, Excel files, custom-made databases and so on and so forth. Traditionally, these are manually documented, monitored and managed. Processes produce, process and consume data –information captured in the metadata layer.

Risk 98

Risk Slice and Dice Management Enterprise 98

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

Smart Data Collective

SEPTEMBER 26, 2021

Data visualization enables you to: Make sense of the distributional characteristics of variables Easily identify data entry issues Choose suitable variables for data analysis Assess the outcome of predictive models Communicate the results to those interested. Choosing the right data storage model for your requirements is paramount.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

CIO Business Intelligence

SEPTEMBER 19, 2024

This enables companies to directly access key metadata (tags, governance policies, and data quality indicators) from over 100 data sources in Data Cloud, it said. 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

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 348

IT Modeling Testing Risk 348

Ontotext

JANUARY 10, 2025

Generative AI (GenAI) models, such as GPT-4, offer a promising solution, potentially reducing the dependency on labor-intensive annotation. 70b-Instruct (via databricks), against state-of-the-art (SOTA) NER models like BioLinkBERT (trained on BioRED) and BERT (trained on AIDA). We benchmarked GPT-4o 3 and Llama-3.1-70b-Instruct

Informatics 59

Informatics Modeling Metadata Experimentation 59

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. The solution integrates data in three tiers.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

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. A change in the source-column header may impact 1,500 design mappings.

Metadata 140

Metadata Digital Transformation Data-driven Enterprise 140

erwin

OCTOBER 18, 2019

erwin positioned as a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions”. We were excited to announce earlier today that erwin was named as a Leader in the @Gartner _inc “2019 Magic Quadrant for Metadata Management Solutions.”. The Gartner document is available upon request from www.erwin.com/GartnerMMMQleader.

Metadata 63

Metadata Management Reporting Publishing 63

erwin

SEPTEMBER 3, 2020

It documents your data assets from end to end for business understanding and clear data lineage with traceability. Data governance and EA also provide many of the same benefits of enterprise architecture or business process modeling projects: reducing risk, optimizing operations, and increasing the use of trusted data.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

DECEMBER 10, 2024

In the Create function pane, provide the following information: For Select a template , choose v2 Programming Model. For Programming Model , choose the HTTP trigger template. Save the federation metadata XML file You use the federation metadata file to configure the IAM IdP in a later step. choose Next.

Sales 105

Sales Metadata Enterprise Testing 105

Ontotext

FEBRUARY 16, 2023

This data can then be easily analyzed to provide insights or used to train machine learning models. Ontotext’s approach is to optimize models and algorithms through human contribution and benchmarking in order to create better and more accurate AI. What Are The Benefits Of Using Ontotext Metadata Studio?

Metadata 59

Metadata Measurement Metrics Modeling 59

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. All of these factors have an impact on a well-defined data integration model. Stop Wasting Your Time.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

AWS Big Data

APRIL 2, 2024

We also detail how the feature works and what criteria was applied for the model and prompt selection while building on Amazon Bedrock. Data consumers need detailed descriptions of the business context of a data asset and documentation about its recommended use cases to quickly identify the relevant data for their intended use case.

Metadata 111

Metadata Metrics Data-driven Contextual Data 111