Blog

blog

Executive Lunch in Minneapolis

Concurrency pulled together clients and our sales excutive team for an Executive Briefing at Crave in Minneapolis to discuss a recent client success.  A midwest airline completed a success data project with Concurrency using PowerBI, Azure Data Bricks and Data Lake to load and analyze booking data across their enterprise.  The brief was attended by several other clients who are planning to enbarck on a simular engagement and wanted to learn more about the process.

Nick Rustad by Nick Rustad

Terraform 0.12 and Azure: Quirks to Keep in Mind

Some quirks of Terraform and Azure I noticed working with it for the first time. By no means is this a comprehensive list, but  a few that I found especially interesting.

Leo Ling by Leo Ling

Moving Big data in and around Azure using Azure Data Factory.

There are numerous data storage options available on Azure, each one designed and developed for different modern data storage scenarios. These storage options could be in the form of database, data warehouse, data caches and data lakes. Usage of these depends on the application and the scale that they serve. Within databases, some applications might need relational database, some might need NOSQL, or a key-value storage, or in-memory database (for caching), or blob storage (for media and large files). Another criteria to keep in mind when selecting a database for your application is the required read-write throughput and latency. Azure has a wide array of fully-managed database services which frees up the development teams valuable time in managing, scaling and configuring these databases.

Whatever database you choose, you should also keep in mind how easy or difficult it is to move the data in and out of that database. You might have a situation in future where you need to move to a new database solution because of reasons like change in application architecture, scale, performance, or even cost. Microsoft Azure has a very powerful ETL tool called Azure Data Factory to easily move data in and around Azure at scale. It has over 80 native connectors which can serve both as source and sink.  In this blog, I would like to highlight a few features and concepts of Azure Data Factory which will serve as a quick start guide for anyone looking to do data movement and transformation on Azure.

Siddharth Bhola by Siddharth Bhola

Intro to Azure Resource Management Templates

Azure resource manager allows the rapid deployment of multiple Azure resources. Unfortunately even relatively simple deployments turn into JSON files hundreds of lines long.  As a newbie to the process, I would like to provide some tips and resources that I found helpful during my quest to build a LAMP Server with load balancers. 

Leo Ling by Leo Ling

ServiceNow to Azure DevOps: Working Together in Harmony

Microsoft has been on the forefront of integrating with ServiceNow, but what solutions exist for getting ServiceNow records into Azure DevOps? Check out this post to learn more about outbound REST Messages out of the ServiceNow platform in order to create work items within Azure DevOps.

Michael Dugan by Michael Dugan

Creating a UI with Power BI

Highlights tips and tricks to maximize the built-in features of Power BI to create an appealing UI and group data inside dashboards.

Trevor Suarez by Trevor Suarez

The Creation Process of the Cloud Economic Assessment

Recently I joined the Cloud Data center and Dev ops team here at Concurrency, and right away I, along with two other interns, were given the project of creating a MVP of a Cloud Economic Assessment (CEA).  This assessment is a virtual tool that will be used to help clients understand how feasible it is to move to Azure, helping them understand the cost and logistics of their applications.

Jasmin Cox by Jasmin Cox