I was privileged to deliver a workshop at Enterprise Data World 2024. Publishing this review is a way to express my gratitude to the fantastic team at DATAVERSITY and Tony Shaw personally for organizing this prestigious live event. Part 1 of this article considered the key takeaways in data governance, discussed at Enterprise Data World 2024. Part […]
Data-Ed Webinar: Data Modeling Types – Conceptual, Physical, Logical
Download the slides here>> About the Webinar A model is developed for a purpose. Understanding the strengths of each of the three Data Modeling types will prepare you with a more robust analyst toolkit. The program will describe modeling characteristics shared by each modeling type. Delegates will be able to trace model components as they […]
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, […]
Why Your Business Needs Data Modeling and Business Architecture Integration
In the contemporary business environment, the integration of data modeling and business structure is not only advantageous but crucial. This dynamic pair of documents serves as the foundation for strategic decision-making, providing organizations with a distinct pathway toward success. Data modeling provides organization to your facts, whereas business architecture defines the operational mechanisms of your […]
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 […]
ADV Webinar: What The? Another Database Model — Vector Databases Explained
Download the slides here>> About the Webinar Vector databases are a type of database that use graph embeddings to represent and compare data, making them ideal for fuzzy match problems. Graph embeddings are created using machine learning algorithms and compress the attributes of data into a low-level representation. The process of creating a new embedding […]
Granularity Is the True Data Advantage
Commerce today runs on data – guiding product development, improving operational efficiency, and personalizing the customer experience. However, many organizations fall into the trap of thinking that more data means more sales, when these two factors aren’t directly correlated. Often, executives will become overzealous in their digital transformations and cut blank checks for data collection, […]
Webinar: Accelerate Data Product Delivery
Download the slides here>> This webinar is sponsored by: About the Webinar High-value data use cases should be iterative, effective and simple to implement. For example, anyone in your organization should be able to request a new data product that contains data, reports, and even an AI model without having to go through a time-consuming […]
How to Become a Data Engineer
The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. A data engineer needs to have a solid understanding of commonly used scripting languages and is expected to support the steady evolution of improved Data Quality, […]