Cloud computing has, in recent years, become both an essential service used in many industries and a ubiquitous part of the daily lives of consumers. By offering remote access to computing services that can be rented out on a flexible, efficient, as-needed basis, it gives companies access to greater computer power and storage capabilities than […]
Data Modeling and Data Models: Not Just for Database Design
“The main purpose of a data model is actually not to design a database – it’s to describe a business,” said Christopher Bradley, information strategist at DMA Advisors. Bradley spoke at a recent Data Architecture Online conference about the purpose of Data Modeling and its role in Data Governance and the modern successful business. Are […]
Knowledge Graphs: Context, Compliance, and Connections
“Graph is leaving a larger and larger footprint. And that is good,” said Thomas Frisendal in Knowledge Graphs and Data Modeling. Gartner named knowledge graphs as part of an emerging trend toward digital ecosystems, showing relationships among enterprises, people, and things, and enabling seamless, dynamic connections across geographies and industries. Elisa Kendall and Deborah McGuinness, […]
Fundamentals of Dimensional Data Modeling
In today’s data-driven business environment, organizations demand reliable and stable business insights to make informed decisions. To cater to this demand, over 60% of companies turn to data warehouses (DWs) to store, manage, and analyze their data efficiently. The success of these DW implementations depends on dimensional data modeling – an analytical approach that organizes and categorizes data for efficient analysis and […]
Graph Databases: Benefits and Best Practices
Graph databases have improved significantly since the 1990s, with new developments and a better realization of best practices. Graph technology has become one of the most popular methods of performing big data research. Its focus on finding relationships and its flexibility make it ideal for a variety of research projects. An awareness of new developments […]
A Brief History of Data Ontology
It can be said that the history of data ontology starts with the development of ontology as a concept in Greece, back in the fourth century B.C.E. It was developed by Aristotle, the famous philosopher. Ontology is a branch of philosophy that is used to classify and explain “that which exists” or answer the question […]
In-Memory Databases: An Overview
In-memory databases work faster than databases with disk storage. This is because they use “internal” optimization algorithms, which are simpler and faster, and this type of system requires fewer CPU instructions than a disk storage system. Additionally, accessing data that has been stored “in-memory” eliminates the need for seek time while searching for data. As […]
Data Warehouse vs. Database
What are data warehouses and databases? How are they different, and when should you use a data warehouse vs. database to store data? Below, we will look at the differences and similarities between them. What Is a Database? In a database, data is presented in a structured manner for easy access and manipulation. Vast amounts […]
How to Become a Data Architect
Being a data architect requires a good understanding of the cloud, databases in general, and the applications and programs used to maximize their potential…
2023 DATAVERSITY Top 20
As the year draws to a close, we here at DATAVERSITY have an annual tradition of digging deep into our data and reflecting on the hits and misses. What was the most popular Data Management content on dataversity.net and our training center over the past 12 months? Which core topics did you – our data […]