In terms of a market perspective, Data Governance has increased in visibility partly because of the increase in security breaches, data security issues, and compliance requirements for various industry regulations. To secure and manage data properly, it helps to manage it at a higher level and know which of your data is sensitive in the […]
Data Modeling in the Machine Learning Era
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) […]
Timely Concerns in Data Models
Click to learn more about author Thomas Frisendal. The Component Parts of Data Models Back in March 2019 I published a post here on DATAVERSITY® titled The Atoms and Molecules of Data Models. The objective was to scope ”a universal set of constituents in data models across the board”. I used this classic data model, […]
Sigma Announces Visual Data Modeling, SQL Runner and One-click Snowflake Integration
According to a recent press release, “Today at the inaugural Snowflake Summit in San Francisco, Sigma, an innovator in cloud business intelligence (BI) and analytics, announced its forthcoming release of a visual data modeling capability, SQL Runner, and one-click Snowflake integration, allowing anyone to explore data in cloud warehouses and generate insights in minutes. Sigma’s […]
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 […]
Embracing Data Silos: Semantic Search and Analytics Innovation
Walk around any large organization and hear people groan about finding the right data to do their work. In the typical organization, data sits in multiple places, lost behind technical and functional boundaries. These isolated systems, referred to as “data silos,” have often existed for good purposes and reasons such as helping each business function […]
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, […]
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 […]