Category Archives: Speaking

SQL Saturday #796 – Minnesota, 2018

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First, many thanks to the SQL Saturday and MNPass team for putting on another great event and letting me participate.

I co-presented with Joshuha Owen (@JoshSQL) in a precon on Modern Enterprise Data Warehousing on Azure. Thanks to those who attended and participated in the conversations around changing the way we implement data warehouse capabilities in Azure. Josh and I will be talking more about this in the future.

Now, those of you who attended my Saturday presentation on Consumption Based Architecture, I wanted to get you the slide deck and reference materials here. Thanks again for attending.

The slide deck from the session is here.

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I also have blog post around this topic: Consumption Based Architecture for Modern Data Analytics. Feel free to join the conversation there around this.

ERPs and the Consumption Based Architecture Conversation

One of the key topics that came up during the session was related to handling ERPs with minimal change. The key issue surrounding ERP solutions is with the data structure in those systems. Whether you work with SAP, JackHenry, or Dynamics, you have a situation where the data model is very complex and definitely not user friendly. In Consumption Based Architecture, we try to minimize data transformation and reshaping, but ERP solutions are by nature cryptic and complex. By definition, they are not consumable. So in the consumable space, we typically recommend using the vendor supplied solutions such as JHKnow, SAP BW and so on. These solutions provide a vendor managed interpretation of the data in the ERP for reporting and other solutions.

Security in this Architecture

The question was raised during the session around how to secure this. This does not have a simple answer. Each solution may have implemented security differently. For instance, an Oracle database may use user names and not have AD integration. This means that you need to determine how to secure your consumable space. For instance, if you pick Azure Active Directory, you would move data to AAD compliant structures in Azure such as Azure SQL Database, Azure SQL Datawarehouse, and Azure Databricks. This means you might need to use a tool like Goldengate with CDC to update a SQL DB which you can apply security to. This will allow you to centralize security for your consumable data. You will need to plan for security in whatever you do and create what you need to support it.

Thanks again everyone for joining us at SQL Saturday.

 

 

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Minnesota BI User Group – Powering Up HDInsight with Power BI (December 2015)

On Wednesday, December 16, I presented on this topic at the Minnesota BI User Group.  This session is based on five blog posts that I created in August 2015.

You can find the presentation here: Powering Up HDInsight with Power BI (pdf).

The details can be found in the blog posts noted below:

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Setting Up and HDInsight Cluster (No Scripts Required)

Exploring the Microsoft Azure HDInsight Query Console (No Scripting Required)

Uploading Files to an HDInsight Cluster (No Scripting Required)

Using Power BI with HDInsight Part 1: Power Query and Files

Using Power BI with HDInsight Part 2: Power BI Desktop and Hive

My goals for this series

1. Document using Power BI with HDInsight

2. Prove that you can set up a HDInsight Cluster with no scripts

Other References from the Session

Azure: http://azure.microsoft.com/en-us/

Cloud Berry: http://www.cloudberrylab.com/free-microsoft-azure-explorer.aspx

 

Thanks for attending my session.

SQL Saturday #437–Boston BI Edition 2015–You Can Still Analyze Data with T-SQL

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Thanks for attending my session on analyzing data with TSQL. I hope you learned something you can take back and use in your projects or at your work. You will find an link to the session and code I used below. If you have any questions about the session post them in comments and I will try to get you the answers.

The presentation can be found here: Analyzing with TSQL

The code was put into a Word document that you can get here: Code to support the analysis with TSQL Sessions

This session is also backed by an existing blog series I have written.

T-SQL Window Functions – Part 1- The OVER() Clause

T-SQL Window Functions – Part 2- Ranking Functions

T-SQL Window Functions – Part 3: Aggregate Functions

T-SQL Window Functions – Part 4- Analytic Functions

Microsoft Resources:

Powering Up HDInsight with Power BI–

On Tuesday, September 15, I presented on this topic for Pragmatic Works. You can find that session here. This session is based on five blog posts that I created in August 2015.

Powering Up HDInsight with Power BI (pdf)https://dataonwheels.files.wordpress.com/2016/02/powering-up-hdinsight-with-power-bi.pdffoundin the

HDInsight Series Featured Pic

Setting Up and HDInsight Cluster (No Scripts Required)

Exploring the Microsoft Azure HDInsight Query Console (No Scripting Required)

Uploading Files to an HDInsight Cluster (No Scripting Required)

Using Power BI with HDInsight Part 1: Power Query and Files

Using Power BI with HDInsight Part 2: Power BI Desktop and Hive

My goals for this series

1. Document using Power BI with HDInsight

2. Prove that you can set up a HDInsight Cluster with no scripts

Other References from the Session

Azure: http://azure.microsoft.com/en-us/

Cloud Berry: http://www.cloudberrylab.com/free-microsoft-azure-explorer.aspx

Wrap Up from the Session

A few questions were asked during the session and I wanted to handle some of them here.

Why did you not use Azure Resource Manager to deploy storage?

I did this as simple as possible and did not need to use the Resource Manager for my demos. However, if you need to rebuild the cluster quickly, the Azure Resource Manager would be a good option. Find out more here: https://azure.microsoft.com/en-us/documentation/articles/hdinsight-provision-clusters/. This site will also walk through scripts and other options for setting up HDInsight clusters.

Why didn’t the table structure show up in the Power Query demo?

The Power Query demo worked with the data from a file approach. This approach is more “raw”. The files did not have column headers, so no headers were created in the table. However, when working with the Power BI Desktop demo, I used Hive. The table was defined in Hive and were easily seen. This is another case for using Hive or something similar to define the schema for ease of use.

What are the differences between Hadoop, Hortonworks, and HDInsight?

Starting from the top, Hadoop is the Adobe open source specification. All of the products listed above are based on Hadoop. Hadoop

Hortonworks and Cloudera are examples of Hadoop distributions. These companies have worked with the various versions of open source technologies around Hadoop and created a supported distribution as a result.

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Finally, HDInsight is Microsoft’s cloud-based Hadoop implementation. They continue to add functionality including Spark, R, Giraph, and Solr. You can expect Microsoft to continue to grow the capabilities of HDInsight as part of their cloud-based analytics solutions.

Thanks for attending my session.