Machine learning (ML) is empowering average business users with superior, automated tools to apply their domain knowledge to predictive analytics or customer profiling. The article What is Automated Machine Learning (AutoML)? discusses a prediction that by 2020, augmented analytics capabilities will play a key role and be a “dominant driver” in the growth (and purchase) […]
Data Models That Build Themselves
Click to learn more about author Mike Brody. Self-service Business Intelligence (BI) is about bridging the knowledge gap that has historically separated business professionals from their data. It’s about doing away with intimate knowledge of information systems as a prerequisite for finding out last quarter’s growth margin. And when it comes to replacing SQL statements with […]
Modeling Sets of Data
Click to learn more about author Thomas Frisendal. Remember? People of my age were taught set algebra at high-school (in my case in the late seventies). Today it is elementary school stuff. And it is indeed a useful tool with applications in many real-life situations. Why did Set Algebra not Become More Popular? In retrospect, […]
The Atoms and Molecules of Data Models
Click to learn more about author Thomas Frisendal. I realized that I needed to know what the constituent parts of data models really are. Across the board, all platforms, all models etc. Is there anything similar to atoms and the (chemical) bonds that enables the formation of molecules? My concerns were twofold: As part of […]
Unstructured Data: Everything Your Company Should Know About It
Click to learn more about author Chirag Shivalker. Unstructured data, in its simplest form means “Data in any form which does not easily fit into a data model or belong to a dataset of database tables.” Unstructured data prevails in formats including books, audios, videos, and even collections of documents. Such unstructured data can be […]
Data Modeling Trends in 2019
IT technologies are rapidly changing our lives. Whether it’s your daily grocery purchase, monthly bill payments, booking railway tickets, or receiving online healthcare consultation, data technologies have penetrated every business model, large, medium, or small. Recent cloud platforms, coupled with Big Data and IoT technologies, have ushered in a new era of “smart technologies” powered […]
2019: Full Scale Schema Modeling
Click to learn more about author Thomas Frisendal. Using Concerns to Navigate Data Architectures Welcome to 2019! This is the year that offers us a unique opportunity to re-architect the way we think schemas, data models and Data Architecture. We do indeed need to do some things better. The real world is full of concerns, […]
Solving Knowledge Graph Data Prep with Standards
Click to learn more about author Dr. Jans Aasman. There’s a general consensus throughout the data ecosystem that Data Preparation is the most substantial barrier to capitalizing on data-driven processes. Whether organizations are embarking on Data Science initiatives or simply feeding any assortment of enterprise applications, the cleansing, classifying, mapping, modeling, transforming, and integrating of data […]
Monetizing Information? Show Me Your Data Model
Click to learn more about author Thomas Frisendal. I recently (finally) had the opportunity to read Doug Laney’s fine book about Infonomics. I have followed his work on this for years, because we share the ambition that data and information should be recognized as assets, just like factory equipment and trucks. Because data keep the […]
The Value of Strong Metadata Discovery
Too often professionals such as Data Analysts, Data Architects, and Compliance Specialists find themselves at a loss when it comes to being able, on their own, to discover, understand and use the rich Metadata within large enterprise ERP and CRM applications. It becomes complicated, costly, and time-consuming for these users to pull relevant business-context subsets […]