Data Analytics

How to Upload and Query a CSV File in Databricks

Welcome to another post in our Azure Every Day mini-series covering Databricks. Are you just starting out with Databricks and need to learn how to upload a CSV? In this post I’ll show you how to upload and query a file in Databricks. For a more detailed, step by step view, check out my video at the end of the post. Let’s get started!

Andie LetourneauHow to Upload and Query a CSV File in Databricks
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A Tutorial of Azure Data Studio

What do you know about Azure Data Studio? This application is a cross-platform database tool for data professionals when analyzing data and doing ETL work. Azure Data Studio is similar to SQL Server Management Studio but has much more functionality for data engineering-type tasks.

Brian CusterA Tutorial of Azure Data Studio
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Using COVID-19 Data in Power BI to Understand Global and Business Impacts

The COVID-19 Coronavirus has made for some very challenging times. It is affecting us personally with our families and of course, in business. I began to think about ways we can learn from this data and analyze daily COVID-19 Coronavirus case data from the CDC to better understand global and business impacts.

Paul TurleyUsing COVID-19 Data in Power BI to Understand Global and Business Impacts
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Pragmatic Works Recognized as Finalist for 2019 Microsoft Data Analytics Partner of the Year Award

PotY Logo 2019

Pragmatic Works is excited to announce that we have been named a finalist for the 2019 Microsoft Data Analytics Partner of the Year Award. The company was honored among a global field of top Microsoft partners for demonstrating excellence in innovation and implementation of customer solutions based on Microsoft technology.

Tom WardPragmatic Works Recognized as Finalist for 2019 Microsoft Data Analytics Partner of the Year Award
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Technical Tips for a Successful Azure Data and Analytic Implementation

azure-icon-250x250This is my second attempt to articulate lessons learned from a recent global Azure implementation for data and analytics.  My first blog post became project management centered.  You can find project management tips here.  While writing it, it became apparent to me that the tool stack isn’t the most important thing.  I’m pretty hard-core Microsoft, but in the end, success was determined by how well we coached and trained the team — not what field we played on.

Turning my attention in this blog post to technical success points, please allow me to start off by saying that with over twenty countries dropping data into a shared Azure Data Lake, my use of “global” (above) is no exaggeration.  I am truly not making this all up by compiling theories from Microsoft Docs.  Second, the most frequent question people ask me is “what tools did you use?”, because migrating from on-prem, Microsoft SSIS or Informatica to the cloud can feel like jumping off the high dive at the community pool for the first time.  Consequently, I’m going to provide the tool stack list right out of the gate.  You can find a supporting diagram for this data architecture here.

Microsoft Azure Tool Stack for Data & Analytics
Hold on, your eyes have already skipped to the list, but before you make  an “every man for himself” move and bolt out of the Microsoft community pool, please read my migration blog post.  There are options!  For example, I just stood up an Azure for Data & Analytics solution that has no logic apps, Azure function, event hub, blob storage, databricks, HDI, or data lake.  The solution is not event-driven and takes an ELT (extract, load, and then transform) approach.  It reads from sources via Azure Data Factory and writes to an Azure Database logging the ELT activities in an Azure Database as well.  Now, how simple is that?  Kindly, you don’t have to build the Taj MaSolution to be successful.  You do have to fully understand your customer’s reporting and analysis requirements, and who will be maintaining the solution on a long-term basis.

If you still wish to swan dive into the pool, here’s the list!

Tom WardTechnical Tips for a Successful Azure Data and Analytic Implementation
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Building a More Effective Sales Team Using Analytics

Building a More Effective Sales Teams Using Analytics

Your sales team is the backbone of your business. Today I’d like to talk about using analytics to build a more effective sales team. This is a big topic for many of our customers and I’ll give you some insight into how we’ve been helping customers to use analytics to make their sales teams go from good to great.

Tom WardBuilding a More Effective Sales Team Using Analytics
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