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, […]
Elastic Introduces Elastic Common Schema (ECS) to Enable Uniform Data Modeling
According to a new press release, “Elastic N.V., the company behind Elasticsearch and the Elastic Stack, announced the general availability of version 1.0 of the Elastic Common Schema (ECS), an open source specification developed with support from the Elastic user community that provides a consistent and customizable way for users to structure their event data […]
The Three Pillars of Agile Data Mastering
Click to learn more about author Mark Marinelli. We’ve explored the benefits of an agile data mastering approach in a previous post, but let’s do a quick recap: Many businesses that collect a large amount of data have an accumulating data mastering issue that leaves their data largely untouchable and riddled with inaccuracies. The problem […]
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 […]
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, […]
Ten Myths About Data Science
Click to learn more about author Daniel Jebaraj. Introduction Data Science is now being used as a competitive weapon. As with other technologies and processes that can transform the way companies operate, there’s a lot of contradictory information about it that’s causing considerable confusion. Most of today’s business leaders have heard that Data Science can […]
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 […]
Why Data Science is Not Statistics
Click to learn more about author Alex Paretski. Statistics as a branch of applied mathematics plays an important role in identifying hidden patterns in data. That’s why it is frequently used interchangeably with broader terms such as Data Science, Data Analytics, Business Analytics, and Machine Learning. Not only is this comparison technically incorrect, but it […]
How an Agile Approach Can Help Solve Your Data Problems
Click to learn more about author Mark Marinelli. Think of your current Data Management process. Is it effective? Are you able to get reliable data you need to carry out business functions served up to you in a timely, actionable manner? Today’s Data Challenge Businesses today face an ongoing data mastering challenge. Too many organizations […]