Power BI Report Builder Map Gallery Customization

David Eldersveld shows off how you can customize maps in the Power BI Report Builder Map Gallery:

One of the defining features of Power BI’s [paginated] Report Builder vs the current geospatial offerings in Power BI Desktop is the native support for ESRI Shapefiles. If you have worked with maps in Report Builder over the years, you may have used the Map Gallery. The Map Gallery offers a collection of built-in geographies, but you can also customize and enhance what’s available out of the box.

David takes us through an example of simplifying one map, but the same technique can help in other ways.

Multi-Pattern Replacement with SQL Server

Hugo Kornelis has a pattern matching problem to solve:

The actual use case and the list of patterns that I had to remove are considered a confidential competitive advantage by my client, so I will just make up a list here to illustrate the problem. In this fake requirement, the following patterns must all be removed if anywhere in the string: “[email protected]@%”, “@@%”, “[email protected]%”, “@%”, “No.X#X”, and “^^^”. Also, “@X” needs to be removed when at the end of the string. In these patterns, @ is a placeholder for a numeric symbol, X for an alphabetic symbol, and # for an alphabetic or numeric symbol. All other symbols are to be taken literally. (So “%” is the percent mark, not the LIKE pattern for any character!).

This is a problem for regular expressions, but without built-in regular expressions (and I’d guess no desire to use the CLR), Hugo gives us a workable solution.

Connecting with Read Intent

John McCormack shows two ways to connect to an Availablity Group listener with read-only intent:

SQLCMD
The -Kreadonly switch is your key to success here but remember to also specify the database using -d. When not set (and with an initial catalog of master for my login), I found I always got the primary instance back during my check. This simple omission cost me hours of troubleshooting work, because I was convinced my listener wasn’t working correctly. In fact, I just wasn’t testing it correctly.

There’s some good information in here for sqlcmd and for SQL Server Management Studio.

Query Editing with Azure SQL Database

Dave Bland shows off the Azure SQL Database query editor built into the Azure portal:

We have all been using SQL Server Management Studio to query and manipulate data, even for an Azure SQL database.  There is also an option to do this same thing built into the SQL Azure database interface in the Azure portal.  Although there have been a number of posts related to this topic dating back a few years, this feature is still marked as “preview” in the Azure portal.

Click through to see how it works, what you can do with it, and some of its limitations.

Temporary Staging with SSIS

Andy Leonard shares one technique for reusing a data set in SSIS:

A work table is a table defined in a nearby data location; either a schema in the source or target database or in a database on the same instance. I take a constraint-driven approach to work table location selection. Closer – a schema in the same database – is often better for performance.

I write this knowing some folks will frown at the suggestion of polluting a data source or target database with additional schemas and tables. Best practices exist for a reason. It’s helpful to maintain a list of best practices and to include in this list the reasons each practice exists. This could be a case where violating one or more best practices is justified.

Andy throws out a few ideas as alternatives but states his preference for using work tables to solve this problem.

Forensic Accounting: Cohort Analysis

I continue my series on forensic accounting techniques with cohort analysis:

In the last post, we focused on high-level aggregates to gain a basic understanding of our data. We saw some suspicious results but couldn’t say much more than “This looks weird” due to our level of aggregation. In this post, I want to dig into data at a lower level of detail. My working conception is the cohort, a broad-based comparison of data sliced by some business-relevant or analysis-relevant component.

Those familiar with Kimball-style data warehousing already understand where I’m going with this. In the basic analysis, we essentially look at fact data with a little bit of disaggregation, such as looking at data by year. In this analysis, we introduce dimensions (sort of) and slice our data by dimensions.

Click through for some fraud-finding fun.

Backing Up Database to Azure Blob Storage

Jamie Wick shows us how we can back up database directly to Azure Blob Storage:

Azure storage, as a backup destination for SQL backups, is a great option for organizations that are contemplating replacing older on-prem NAS appliances or improve their Disaster Recovery functionality. The tiered storage pricing, along with local and global redundancy options, can be much more cost-effective than many traditional backup options.

In this post, we’re going to look at some of the key concepts and restrictions, along with how to back up an SQL database to an Azure storage location.

Click through for the demo.

Qualitative Analysis with Dendograms

Stephanie Evergreen explains what denodgrams are and when they can be useful visuals:

Dendrograms are not THE most common qualitative visual because they require a data generated through a hierarchical cluster analysis. Cluster analysis can be a useful tool in analyzing qualitative data. By clustering groups of participants with similar qualitative codes, you can better understand your findings. According to Henry & team, this analysis can help “reveal things like participant motive and the reasons behind counterintuitive findings.”

Check out Henry’s article to learn more about the analysis. Here, let’s just focus on describing a dendrogram that could display those hierarchical cluster analysis findings. They can be a little confusing at first, especially since the x-axis has 100% closest to the y-axis when we aren’t used to seeing it that way. Walk through this example with us.

Click through for an example. If it’s confusing at first, read to the end, as I think the concrete example helps everything click.

Errors Updating Stats on Columnstore Indexes

Max Vernon walks us through some problems trying to update statistics on columnstore indexes:

The first error above would be seen if you have a SQL Server Agent job that updates statistics. The second error is how it looks in an SSMS Query window.

The error message claims that UPDATE STATISTICS can only be used on a columnstore index with the STATS_STREAM option. However, the Microsoft Docs UPDATE STATISTICS shows very “thin” documentation for the option, showing only these two tidbits:

<update_stats_stream_option>
Identified for informational purposes only. Not supported. Future compatibility is not guaranteed.

Columnstore indexes really don’t want their stats updated, apparently, and will fight you tooth and nail to prevent it.

Long Weekend Learning Items

Kevin Chant has a few things you should check out if you’ve got several days of downtime:

Install and learn Docker
You can take the time over the Easter weekend to download and install Docker to see how you can use it. In addition, there are multiple posts online by people online that you can use as a starting point.
However, to start with you can read how to download and install it in detail here.

There are some good things on this list. Even if you don’t have a long weekend ahead of you, pick up some of these items gradually.

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