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

TDAN

AUGUST 18, 2020

Standards exist for naming conventions, abbreviations and other pertinent metadata properties. Consistent business meaning is important because distinctions between business terms are not typically well defined or documented. What are the standards for writing […].

Management 96

Management Metadata Data Architecture IT 96

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

TDAN

AUGUST 16, 2022

In the first 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 the Ubiquitous Language that defines the Bounded Context (..)

Data-driven 59

Data-driven Management Modeling Data Architecture 59

AWS Big Data

APRIL 19, 2023

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization. Mike is the author of two books and numerous articles.

Technology 82

Technology Data-driven Machine Learning Sales 82

TDAN

JULY 5, 2022

Bounded Contexts / Ubiquitous Language My new book, Data Model Storytelling,[i] contains a section describing some of the most significant challenges data modelers and other Data professionals face. Like most of its predecessors, including Agile development and […].

Data-driven 102

Data-driven Modeling Data Architecture IT 102

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Peter James Thomas

AUGUST 18, 2018

No this article has not escaped from my Maths & Science section , it is actually about data matters. The image at the start of this article is of an Ichthyosaur (top) and Dolphin. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Ontotext

MAY 30, 2019

In this article, we are bringing science fiction to the semantic technology (and data management) talk to shed some light on three common data challenges: the storage, retrieval and security of information. We will talk through these from the perspective of Linked Data (and cyberpunk).

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

TDAN

APRIL 4, 2023

Why would Technics Publications publish a book outside its specialty of data management? First, Graham is a world-renowned data modeler and the author of Data Modeling for Quality, and therefore many of his examples are in the field of data management. Second, and more […]

Publishing 52

Publishing Modeling Management Data Architecture 52

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

TDAN

JULY 19, 2022

In reference to the prior column on enterprise data management and high level lego framework, this column reviews in detail the foundational layer of Organization Mission, Level 1. These six lego blocks […].

Strategy 52

Strategy Enterprise Management Modeling 52

TDAN

JUNE 30, 2020

About a week ago, I was teaching a data modeling class, and an attendee asked me to explain the concept of a data catalog. However, I had recently read the book, The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics by […]. Like a lot of hype-related terms in IT, there is more than one definition.

Modeling 52

Modeling Analytics Data Architecture IT 52

TDAN

AUGUST 18, 2020

Flexibility is one strong driver: heterogeneous data, integrating new data sources, and analytics all require flexibility. We are in the era of graphs. Graphs are hot. Graphs deliver it in spades. Over the last few years, a number of new graph databases came to market. As we start the next decade, dare we say […].

Data Integration 119

Data Integration Marketing Analytics Data Architecture 119

TDAN

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Publishing 78

Publishing Data Quality Data Architecture IT 78

TDAN

SEPTEMBER 16, 2020

Differences in Terminology and Capability Building on the terms and concepts introduced in Part I of this white paper, Part II digs deeper into the difference in the meaning of some key terms used in both Property Graphs and Knowledge Graphs, including LABELS, TYPES, and PROPERTIES. Key terms such as these actually mean very different […].

Data Architecture 92

Data Architecture Metadata Data Strategy Strategy 92

TDAN

SEPTEMBER 7, 2022

Many developers pooh-pooh OWL (the dyslexic acronym for the Web Ontology Language). Many decry it as “too hard,” which seems bizarre, given that most developers I know pride themselves on their cleverness (and, as anyone who takes the time to learn OWL knows, it isn’t very hard at all). It does require you to think […].

IT 52

IT Data Architecture Metadata Modeling 52

TDAN

MARCH 31, 2020

Executive Summary It seems obvious enough that companies, government agencies and non-profits would benefit from a common language. Without it, coordinating work is more difficult, computers “don’t talk,” and basic questions such as “how many customers do we have?” yield differing answers, making it more difficult to run the business.

IT 84

IT Data Architecture Metadata Data Strategy 84

TDAN

MAY 31, 2022

In my September 2020 Data is Risky Business column for TDAN.com, I wrote about the strategy lessons for data that we can learn from the writings of a 16thcentury Japanese swordsman. To summarize: – We need to study different disciplines to understand how they relate to each other.

Strategy 52

Strategy Data Architecture Data Strategy Metadata 52

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

IBM Big Data Hub

JANUARY 18, 2023

This article endeavors to alleviate those confusions. Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. This adds an additional ETL step, making the data even more stale. It can be codified.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

TDAN

MAY 14, 2019

Welcome to DAMA Corner, a source of information for data management professionals here in TDAN.com, an industry-leading publication for people interested in learning about data administration, data management disciplines, and best practices.

Management 40

Management Data Quality Data Architecture Metadata 40

TDAN

NOVEMBER 5, 2019

This series of columns will focus on many things including the nature of a graph database, how we evolved to a graph database, how a graph database is different from a relational database, two classes of graph databases – property and semantic, how property and semantic graph databases differ, use cases, challenges, how to map […].

Metadata 40

Metadata Data Strategy Data Architecture Business Intelligence 40

IBM Big Data Hub

AUGUST 4, 2023

When workers get their hands on the right data, it not only gives them what they need to solve problems, but also prompts them to ask, “What else can I do with data?” ” through a truly data literate organization. What is data democratization?

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59