A Fine Slice Of SQL Server
Steven Sanderson joins on multiple columns:
Let’s start with a simple scenario. You have two data frames, and you want to merge them based on two columns:
IDandYear. The goal is to combine the data where theIDandYearvalues match in both data frames.
All of the examples here use the merge() function, so check them out.
Marco Russo compares and contrasts:
What is the right choice between Direct Lake and Import mode in Power BI?
At SQLBI, we do not publish content until we have had enough time to experiment with and collect data about new features. We usually don’t break the news unless we have enough time to test a feature in preview and consider the released service solid enough. This did not happen with Direct Lake, and we have not published any Direct Lake content yet, but it seemed not urgent for reasons we will see soon. However, the feedback collected from many attendees of SqlBits 2024 and the first Microsoft Fabric Conference raised the alarm: too many people have an incorrect perception of Direct Lake, which should be addressed as soon as possible to avoid architectural mistakes and unnecessary additional implementation costs.
Click through for the tl;dr version, followed by the explanations.
Leave a CommentJosephine Bush sets up a failover group in Azure SQL Database:
In today’s fast-paced digital world, keeping your data safe and accessible is more important than ever. That’s where Azure SQL Database steps in, offering a suite of tools to ensure your information is always within reach. Among these tools, failover groups shine, ready to jump into action whenever there’s a hiccup. So, let’s explore how failover groups in Azure SQL Database work their magic, ensuring your data stays safe and sound despite unexpected challenges.
Read on for the step-by-step instructions.
Leave a CommentElena Drakulevska takes us through some of the accessibility features in Power BI:
As data professionals, we’re constantly striving to create reports that effectively communicate insights to our audience. Did you know that within Power BI, there are hidden accessibility features that can enhance the usability for all users—with minimal effort on your part? Today, we’re digging into this overlooked aspect of Power BI and exploring how these features can elevate your data visualization projects.
Click through for three features.
Leave a CommentNikola Ilic performs a migration:
Here is my scenario: there is an existing Power BI semantic model in import mode (in reality, there are many of them, but for the sake of keeping things simple for this blog post, let’s pretend that there is only one semantic model to be migrated).
Click through to see what the current state of the semantic model looks like, as well as the way to migrate. It’s not trivial, but Nikola does take us through it step by step.
Leave a CommentChris Webb shows a map in a paginated report:
The built-in mapping functionality in Power BI paginated reports is fairly basic. However the integration of Power Query into Power BI paginated reports gives you an interesting new way of creating maps in paginated reports: you can call the Azure Maps API using Power Query and display the image returned in an Image report item. In this blog post I’ll show you how.
Click through for the demo.
Leave a CommentMuhammad Ali explains quite a few of the security terms in PostgreSQL:
PostgreSQL has a fine grained system for for managing user roles and privileges. This helps admins decide who can access certain data and what they’re allowed to do with it. It’s about managing permissions, where you can create different roles and roles can be a member of other roles.
In this blog, we will dive into PostgreSQL user roles and permissions, covering databases, schemas, and other objects level privileges, following a FAQ format.
Most of this is similar to security in SQL Server, though there are some differences to watch out for.
Leave a CommentSteven Sanderson is from the 5th dimension:
Visualizing similarities between data points can be tricky, especially when dealing with many features. This is where multidimensional scaling (MDS) comes in handy. It allows us to explore these relationships in a lower-dimensional space, typically 2D or 3D for easier interpretation. In R, the
cmdscale()function from base R and is a great tool for performing classical MDS.
Click through to see how this works. In case you’re curious, cmdscale() is an example of principal coordinates analysis. If you’re familiar with principal components analysis, that’s a different form of multidimensional scaling.
Rhian Davies consults the map:
I love playing with spatial data. Perhaps because I enjoy exploring the outdoors, or because I spend hours playing Geoguessr, or maybe it’s just because maps are pretty but there’s nothing more fun than tinkering with location data.
However, reading in spatial data, especially large data sets can sometimes be a pain. Here are some simple things to consider when working in spatial data in R and breaking large data sets into more manageable chunks.
Click through for three tips when dealing with spatial data. The code is in R but the tips make sense in any language.
Leave a CommentKurt Buhler digs into scatter plots:
In many reports, it is common to find large tables or matrixes with a lot of information. Business users come to these reports to get the details they need to answer questions, make decisions, and take actions. However, these detailed tables can be inefficient, requiring users sort, drilldown, and filter them to find actionable data.
Consider the following example of a matrix to analyze gaps in year-over-year growth by product, and dissect those by region. In this scenario, the intended purpose of the report is for a sales team to analyze why we did not hit our revenue growth target.
Read on to learn what you can do with a scatter plot, either natively in Power BI or via custom visual.
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