by Angela Guess Eran Levy recently wrote in Smart Data Collective, “For many non-technical individuals in the business world, data modeling can seem like a strange and somewhat terrifying realm. Even those who are data-savvy and regularly consult and analyze data in their day-to-day operations will often view modeling as perplexing under-the-hood stuff that is […]
Execs Starting to Take Charge of Modeling and Analyzing Data
by Angela Guess Hugo Moreno reports in Forbes, “According to a recent Forbes Insights executive brief, “Decisions, Decisions: How Leading Firms Are Arming Frontline Executives With Data-Driven Insight,” sponsored by Qlik, business executives are no longer satisfied with the long waiting periods, high costs and questionable quality of data- driven decision support being developed on […]
Glassbeam Unveils Data Transformation and Edge Computing Capabilities for Its IoT Platform
by Angela Guess According to a new article out of the company, “Glassbeam, Inc., the machine data analytics company, announced today two revolutionary product enhancements for the IoT analytics market. Glassbeam Studio™ is the IoT industry’s first data transformation and preparation tool focused on automating cumbersome manual work required to convert raw machine log data into […]
Foreign Keys and the Delete Performance Issue
Eventually you’ll run into a simple delete instruction that takes minutes (I mean, years!) to get executed. It’s just a hundred-row table, and, still, it takes a lifetime to get the rows deleted. Here’s a small tip: you’re probably missing some indexes. Foreign Keys and their dirty secrets There is a very basic, yet very […]
Primary Key and Foreign Key Errors to Avoid
Few IT applications are truly grass roots. Rather most new applications are intended to replace or complement existing applications. As a result, we often find ourselves working with legacy databases. This article is based on 50 legacy databases that we’ve studied over the years. In our experience about 20% of database designs are clean and […]
Data Rationalization – The Next Step in Semantic Resolution
With the Web 2.0, ontologies are being used to improve search capabilities and make inferences for improved human or computer reasoning. By relating terms in an ontology, the user doesn’t need to know the exact term actually stored in the document. Data Rationalization is a Managed Meta Data Environment (MME) enabled application which creates/extends an ontology for a domain into the structured data world, based on model objects stored in various models (of varying levels of detail, across model files and modeling tools) and other meta data.