As more and more companies start to use data-related applications to manage their huge assets of data, the concepts of data modeling and analytics are becoming increasingly important. While they typically rely on one each, they are two very distinct concepts. Companies use data analysis to clean, transform, and model their sets of data, whereas they […]
What Data Practitioners Need to Know (and Do) About Common Language
“Unless and until all members of a team have a common understanding of the problem, attempts to solve the problem are just so much wasted energy.” –Gerald M. Weinberg [1] In March 2019, one of us (Thomas C. Redman) served as the judge in a mock trial of a data architect (played by Laura Sebastian Coleman) […]
Knowledge Graph Standards in Ambient Computing
Ambient computing is a broad term that describes an environment of smart devices, data, AI decisions, and human activity that enables computer actions alongside everyday life, without the need for direct human commands or intervention. Ambient computing represents an unparalleled opportunity to enhance almost every sphere of society – from the professional to the personal. And in […]
What Every Business Leader Needs to Know About Data Modeling
The COVID-19 pandemic has meant that data-driven decisions have influenced all our lives over the last two years. 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 U.K. Government in 2020 […]
11 Intriguing Roles for Data Scientists in 2022
Data Science is a diverse field with an array of career and job options out there to pursue. The modern economy is dependent on data and data analysis so, naturally, data scientists are in high demand and enjoy good salary and job security prospects. With that in mind, below are 11 intriguing roles for data […]
Tales of Data Modelers
Reading Larry Burns’ “Data Model Storytelling” (TechnicsPub.com, 2021) was a really good experience for a guy like me (i.e., someone who thinks that data models are narratives). I agree with Larry on so many things. However, this post is not a review of Larry’s book. Read it for yourself – highly recommended. Reading it triggered […]
Quick, Easy, and Flexible Data Model Diagrams
Click to learn more about author Thomas Frisendal. Many of us have a lot to do. And we have short delivery cycles, sprints, and a lot of peers to share data models with. In search of something lightweight, which is quick and easy, and may be produced (or consumed) by other programs? Stay with us on a […]
Machine Learning Transformed: Data Quality and Operational Necessities
Machine learning elicits mixed reactions. On the one hand, some consider machine learning a company’s new super power that has “swept enterprise technology, using mass amounts of data and algorithms to make predictions.” At the same time machine learning has been considered an overhyped fad and a panacea, failing to deliver. While both can be […]
Data Architecture with Data Governance: A Proactive Approach
“Data Architecture is the physical implementation of the Business Strategy,” said Nigel Turner, Principal Consultant in E.M.E.A. at Global Data Strategy, speaking at the DATAVERSITY® Enterprise Data Governance Online Conference. “It’s a key part of the whole continuum that you need to build within an organization to manage data effectively,” and Data Governance forms an […]
Cloudera Delivers Open Standards Based MLOps
A new press release states, “Cloudera, the enterprise data cloud company, today announced an expanded set of production machine learning capabilities for MLOps is now available in Cloudera Machine Learning (CML). Organizations can manage and secure the ML lifecycle for production machine learning with CML’s new MLOps features and Cloudera SDX for models. Data scientists, […]