While the data warehouse isn’t a new concept, many are left wondering – what is a data warehouse? And why do I need one? I'm sad to tell you that when we say "data warehouse", we aren't referring to a physical building that stores data! Datalere’s official definition of a data warehouse is the following [...]
Going into 2019, data science and machine learning is all the hype. Organizations in every industry are starting to realize that the key to success is held in the ability to make organization-wide data-driven decisions. Organizations previously stored data for regulatory reasons or because it was a necessary evil of doing business. Today, organizations are [...]
If there’s one thing to take away from this blog post, it’s that data science does not succeed in a bubble. Like any corporate initiative, launching a data science project requires forethought, planning, and successful execution to succeed. But what does that entail? What steps can I take to ensure that my organization’s data science [...]
When considering each of the three major cloud providers, Datalere is often asked, “Why would I switch to Google Cloud? What benefits does the Google Cloud platform provide that are different from what’s offered by AWS or Microsoft Azure? The truth is that while Microsoft has been a proven enterprise solution for many years and [...]
As a consultant, I’m often thrown into new databases and tables with a wide variety of schema variations. One of the challenges that I’ve often come across, is finding a field that belongs to a table or if the field has an alternative name. Another challenge is, even if you’ve familiar with the database, but [...]
With the Automating Database Deployment: Part 3 Running RoundhousE post we walked through running a RoundhousE deployment for the first time to create the database and several database objects. Script naming importance was talked about to help maintain the correct execution order. The tables were empty so a second deployment was run with new scripts added to [...]
Now that we have a basic understanding of RoundhousE database deployment from the first two parts of this series let’s get to the good stuff. If you haven't read the first articles you might take some time to go back through them. Here are links to those first two. Automating Database Deployment: Part 1 Introduction [...]
Remember from the introduction that RoundhousE is a command line driven database deployment engine. This article of the series will discuss the deployment flow and the RoundhousE environment, looking at the default behavior and how to modify it using command line switches. When a RoundhousE deployment is run the first step is a check to [...]
Database Deployment in DevOps One of the many obstacles to database development and DevOps is how to deploy databases consistently and how to automate the process. Database deployments have historically consisted of last minute treasure hunts to find or build scripts of the changes that have been made. Inevitably that leads to missed changes, no [...]
AWS EC2 Linux AMI with pyodbc, psqlODBC, Microsoft ODBC Drivers Context: Using pyodbc within a small python application to pull tracking data from an Azure SQL Server DB, do some work, and then store the results into AWS RDS PostreSQL DB. Problem: Default AWS EC2 Linux AMI 2017.09.1 does not come with unixODBC 2.3.x which [...]