TDAN

SEPTEMBER 3, 2019

As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.” Sorry, I’m going to have to disagree with you there. You are on a fool’s errand that will just provide […].

Metadata 65

Metadata Data Governance Big Data Modeling 65

TDAN

SEPTEMBER 14, 2021

In this article, I describe a method of modelling data so that it meets business requirements. Central to this method is that modelling not only the required data, but also the subset of the real world that concerns the enterprise.

Modeling 52

Modeling Enterprise Data Quality IT 52

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 253

Modeling Software Sales Statistics 253

TDAN

JUNE 20, 2023

These days, there is much conversation about the necessity of the data model. The data model has been around for several decades now and can be classified as an artifact of an earlier day and age. But is the data model really out of date? And exactly why do we need a data model, anyway? […]

Modeling 52

Modeling Metadata Data Strategy Data Governance 52

TDAN

MAY 20, 2020

Data modeling and database design is an in-demand career path, and database design is a crucial skill set that experienced DBAs must possess. In this article, we’re going to look at some common “beginner” questions, though written with the assumption you’re familiar with some aspects of data modeling and database design.

Modeling 64

Modeling Data Quality Metadata Management 64

Rocket-Powered Data Science

MARCH 10, 2020

And this: perhaps the most powerful node in a graph model for real-world use cases might be “context”. How does one express “context” in a data model? Ahh, that’s the topic for another article. Hence, the graph model can be applied productively and effectively in numerous network analysis use cases.

Metadata 250

Metadata Machine Learning ROI Prescriptive Analytics 250

Ontotext

JUNE 27, 2019

It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical. GraphDB: MongoDB Document Store Integration for Large-scale Metadata Management. Choose The Best RDF Database for Metadata Management. Prerequisites.

Metadata 40

Metadata Management Enterprise Optimization 40

DataKitchen

OCTOBER 20, 2023

In this article, we explore the role of Payload DJs in addressing these complexities, illustrated with examples from industries like drug discovery and insurance. Payload DJs facilitate capturing metadata, lineage, and test results at each phase, enhancing tracking efficiency and reducing the risk of data loss.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

Ontotext

MARCH 13, 2024

OTKG models information about Ontotext, combined with content produced by different teams inside the organization. Our standard methodology for such projects is to start by defining competency questions that would help us understand what we need to model in our graph. What is OTKG?

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

Ontotext

JUNE 27, 2019

For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information. It sends requests to MongoDB queries and then transforms the extracted data to an RDF model. Choose The Best RDF Database for Metadata Management.

Metadata 40

Metadata Management Optimization Enterprise 40

TDAN

MAY 18, 2021

Three different types of data models exist, each of which plays a distinct role in data modeling. There are three stages of data modeling, with each stage pertaining to its own type of data model – conceptual data models, […].

Modeling 75

Modeling Enterprise IT Metadata 75

O'Reilly on Data

MARCH 22, 2019

We are surrounded by systems that make ethical decisions: systems approving loans, trading stocks, forwarding news articles, recommending jail sentences, and much more. In recent articles, I've suggested the ethics of artificial intelligence itself needs to be automated. It’s easy to mark a message as “spam” or “not spam.”

Metadata 242

Metadata Advertising Insurance Modeling 242

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us. Ayres MBA.

Data Governance 145

Data Governance IT Risk Data Lake 145

TDAN

JULY 6, 2021

Larry Burns’ latest book, Data Model Storytelling, is all about maximizing the value of data modeling and keeping data models (and data modelers) relevant. In his roles as Data Architect, Data Modeler, and Database Administrator, he has had to complete challenging projects and also fix […].

Modeling 52

Modeling Manufacturing Metadata Management 52

IBM Big Data Hub

JUNE 26, 2023

Possibilities are growing that include assisting in writing articles, essays or emails; accessing summarized research; generating and brainstorming ideas; dynamic search with personalized recommendations for retail and travel; and explaining complicated topics for education and training. in 2022 and it is expected to be hit around USD 118.06

Risk 70

Risk Deep Learning Metadata Modeling 70

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? You must detect when the model has become stale, and retrain it as necessary. The development phases for an AI project map nearly 1:1 to the AI Product Pipeline we described in the second article of this series.

Marketing 362

Marketing Experimentation Metrics Testing 362

TDAN

FEBRUARY 1, 2022

But decisions made without proper data foundations, such as well constructed and updated data models, can lead to potentially disastrous results. For example, the Imperial College London epidemiology data model was used by the UK Government […].

Modeling 52

Modeling Data-driven Metadata Data Strategy 52

TDAN

FEBRUARY 1, 2022

But decisions made without proper data foundations, such as well constructed and updated data models, can lead to potentially disastrous results. For example, the Imperial College London epidemiology data model was used by the UK Government […].

Modeling 52

Modeling Data-driven Metadata Data Strategy 52

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . This excerpt from the article sums it up:

Snapshot 90

Snapshot Data Science Digital Transformation Metadata 90

Ontotext

MARCH 15, 2024

Moreover, the complexity of medical language and concepts requires QA models to have a deep understanding of context, making it challenging to develop robust systems that can accurately interpret queries and provide relevant answers across languages. QA fine-tuning The next step in the training pipeline is task-specific fine-tuning.

Modeling 59

Modeling Metadata Testing Optimization 59

Ontotext

DECEMBER 16, 2021

In this article, the second entry in our Graphs on the Ground series ( see our first article on financial services ), we will explore how knowledge graphs combat these challenges across four critical activities within the world of life sciences and pharmaceuticals. That information enhances the graph, which improves the NLP model.

Metadata 98

Metadata Reporting Unstructured Data Risk 98

TDAN

JUNE 15, 2021

Data Governance describes the practices and processes organizations use to manage the access, use, quality and security of an organizations data assets. The data-driven business era has seen a rapid rise in the value of organization’s data resources.

Data Governance 105

Data Governance Modeling Data-driven Management 105

TDAN

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

Metadata 52

Metadata Data Governance Data Quality Management 52

Smart Data Collective

AUGUST 28, 2021

In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data lakes are much more flexible as they can store raw data, including metadata, and schemas need to be applied only when extracting data. Data Warehouses and Data Lakes in a Nutshell. Target User Group.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Structured Data 139

Ontotext

APRIL 15, 2020

The initial dataset consisted of 13,202 journal articles relevant to novel coronavirus research. The FHIR RDF version of CORD-19 plans to use the PICO ontology for modeling the annotations and to store them back in GraphDB. It contains more than 51,000 scholarly articles and is available to the global research community.

Publishing 105

Publishing Metadata Data mining Technology 105

Ontotext

FEBRUARY 1, 2024

We as a taxonomy community are facing rapid technological change and grappling with where our discipline fits into a world captivated by ChatGPT and other generative models. The challenge of complexity Knowledge models for taxonomy have responded to an increasing need for sophistication and expressiveness.

Enterprise 59

Enterprise Management Metadata Modeling 59

CIO Business Intelligence

JULY 8, 2022

This article will be updated once the new certifications are announced in the coming months. The eight questions are drawn from topics such as ADM phases, adapting the ADM, architecture content framework, TOGAF reference models, and the architecture capability framework. . TOGAF 9 Foundation and TOGAF 9 Certified.

Risk Management 105

Risk Management Risk Enterprise Metadata 105

IBM Big Data Hub

NOVEMBER 21, 2023

In this article, developer Michael Burgess provides an insight into the concept of schemas and schema management as a way to add value to your event-driven applications on the fully managed Kafka service, IBM Event Streams on IBM Cloud ® What is a schema? Kafka does not examine the metadata of your messages.

Data Quality 105

Data Quality Metadata Data-driven Optimization 105

TDAN

AUGUST 2, 2022

Canonical Data Models and Overlapping Connections In the previous article, I introduced and explained the approach to application development called ‘Domain-Driven Development’ (or DDD), explained some of the Data Management concerns with this approach, and described how a well-constructed data model can add value to a DDD project by helping to create (..)

Data-driven 59

Data-driven Modeling Management Data Architecture 59

datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. These needs are then quantified into data models for acquisition and delivery. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CDW Research Hub

MAY 29, 2020

Salesforce is an extremely powerful customer relationship management solution offered in a Software as a Service model, which greatly reduces the infrastructure and management needed to operate a solution of this nature. The other thing clients need to consider is protecting the metadata contained within their Salesforce account.

Metadata 53

Metadata Dashboards Reporting Management 53

Cloudera

SEPTEMBER 29, 2022

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. In this article, we attempt to show how these concepts may be related to each other, and even suggest thinking about all of them all at once (gasp!). The data itself is then treated as a product.

Data Architecture 73

Data Architecture Metadata Data Warehouse Sales 73

TDAN

MARCH 16, 2021

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

Data Governance 105

Data Governance Testing Modeling Data Quality 105

TDAN

APRIL 2, 2019

Although data modeling has been around for over 30 years, it ranks among the top areas from which database application problems arise. Today’s data modeling […]. Moreover, the severity of the problems ranges from totally incorrect functionality to freakishly miserable performance. The answer is quite unnerving.

Modeling 45

Modeling Data Architecture IT Metadata 45

Ontotext

FEBRUARY 14, 2024

CEEL is an end-to-end transformer-based model that includes mention detection and uses entity types and entity descriptions to perform entity linking. Out of the box, the model links to Wikidata IDs. That’s why such models must use context in order to differentiate between entities, just as humans do.

Cost-Benefit 52

Cost-Benefit Modeling Metadata Optimization 52

Smart Data Collective

MARCH 19, 2023

Paul Glen of IBM’s Business Analytics wrote an article titled “ The Role of Predictive Analytics in the Dropshipping Industry.” You can start dropshipping as a part-time business at any age and organize a successful business that can include other business models. The dropshipping industry is among them.

Predictive Analytics 128

Predictive Analytics Analytics Manufacturing Advertising 128