Press "Enter" to skip to content

Author: Kevin Feasel

Microsoft Fabric and Dataverse

Jose Mendes let us know what’s going on with Dataverse:

If like me, you’ve been keeping taps on what Microsoft has been up to on the Power Platform world, you would have noticed that there are two concepts that are regularly referenced in their architectures and generally associated to each other, Azure Data Lake Storage (ADLS) Gen 2 and Common Data Model (CDM).

As Francesco referred in his blog, Microsoft ultimate vision is for the CDM to be the de facto standard data model, however, although there is a fair amount of resources talking about the capabilities and features, it can be a bit confusing to understand how you can actually store your data in the CDM format in ADLS and use it to run data analytics such as data warehousing, Power BI reporting and Machine Learning.

Read on for more of what’s happening on that front. I will admit that Dataverse tends to be way down on my list of priorities, but that’s because I’m a relational database snob.

Comments closed

Data Activator in Microsoft Fabric

Toby Smith looks at the current state of Data Activator in Microsoft Fabric:

Fabric is the newest all-in-one analytics solution from Microsoft. It combines multiple components (some existing, some new) into a single integrated environment. One of these new components is Data Activator. As Data Activator is still in development, there is still more functionality to be added. This blog shares some of the current abilities and uses for Data Activator, along with ideas for how you can use it in your own business situations.

One of the biggest challenges with big data is understanding it. With tools like Power BI, we are now able to understand and analyse data better than ever before. But when do we act on it? Do we have to manually look at these reports daily just to check everything is going ok? This is where Data Activator comes in. Data activator is a no-code tool that automatically takes actions when certain conditions are met in the data. These actions can vary from alerts in Microsoft Teams, calling stored procedures, triggering other fabric items like a pipeline, or even retraining AI models.

This is a feature which has enormous potential for near-real-time alerting and automating workflows. But do read on to learn about some of the limitations currently in the product.

Comments closed

Microsoft Fabric Roadmap

James Serra shares some thoughts on the Microsoft Fabric roadmap:

Just released was the Microsoft Fabric roadmap that you can check out at https://aka.ms/FabricRoadmap. It’s great to see Microsoft be transparent on what features they are working on and when they will be available.

Here are my top 18 features on the roadmap that I am most excited about (in the order found in the roadmap):

Seems like about half of what James is looking forward to releases in Q4 and the other half releases in mid-2024.

Comments closed

Updates to Power BI Field Finder

Stephanie Bruno has an update for us:

The Power BI Field Finder is a standalone .pbix file you can download and hook up to your reports and data model to. The Field Finder helps you visually analyze where fields are used in reports.

I’ve used this to great effect on a prior project where I had to figure out what was going on in a report with about 20-25 pages that other people had put together.

Comments closed

Apache Kafka 3.6 Released

Satish Duggana announces what’s new in Apache Kafka 3.6:

The ability to migrate Kafka clusters from a ZooKeeper metadata system to a KRaft metadata system is now ready for usage in production environments. See the ZooKeeper to KRaft migration operations documentation for details. Note that support for JBOD is still not available for KRaft clusters, therefore clusters utilizing JBOD can not be migrated. See KIP-858 for details regarding KRaft and JBOD.

Support for Delegation Tokens in KRaft (KAFKA-15219) was completed in 3.6, further reducing the gap of features between ZooKeeper-based Kafka clusters and KRaft. Migration of delegation tokens from ZooKeeper to KRaft is also included in 3.6.

Tiered Storage is an early access feature. It is currently only suitable for testing in non-production environments. See the Early Access Release Notes for more details.

Read on for more details around what’s new in Apache Kafka.

Comments closed

Apache Spark Execution Plan Analysis

Karthik Penikalapati digs into Spark SQL explain plans:

In this blog post, we will explore how the Explain Plan can be your secret weapon for debugging and optimizing Spark applications. We’ll dive into the basics and provide clear examples in Spark Scala to help you understand how to leverage this valuable tool.

All I’m saying is, if some company wants to create SQL Sentry Plan Explorer for Apache Spark, I’d be down with it. That loss of an intuitive and powerful graphical interface for execution plans is definitely a point of friction when working with Apache Spark and Spark SQL.

Comments closed

Reasons Your SQL Server Query Performance Fluctuates

Aaron Bertrand starts the count:

Query performance can fluctuate over time, and it is not necessarily due to a change to the query itself (or to the application code that calls it). Users often ask why a query suddenly got slower even though they haven’t published any changes to the application and the underlying data hasn’t changed drastically. This article points out some other reasons – and there are many – that a query might be slower today than it was 10 minutes ago, two weeks ago, or last summer.

Read on for a bulleted list of reasons. Of course, it would be extremely challenging to create a comprehensive list—for example, in the Same Plan section, in addition to there being more data, changes in the statistical distribution of data can cause performance profiles to change over time. But this is a really good starting point.

Comments closed

SQL Server Security Updates

Srinivas Kandibanda announces a series of security updates for all supported versions of SQL Server:

The Security Update for SQL Server 2022 RTM CU8 is now available for download at the Microsoft Download Center and Microsoft Update Catalog sites. This package cumulatively includes all previous SQL Server 2022 fixes through CU8, plus it includes the new security fixes detailed in the KB Article.

I linked specifically to the SQL Server 2022 RTM CU8 blog post, but there are security bulletins for all versions of SQL Server going back to 2014. If you’re running SQL Server 2012 or earlier, no updates for you.

Also, the highest-risk CVE items are in SQL Server 2019 and 2022; for 2017 and below, the one security bulletin covers a moderate-severity denial of service attack.

Comments closed

Oracle Errors: Snapshot Too Old and LOB Columns

David Fitzjarrell tackles a pair of errors:

One of the few errors taht strikes fear in the heart of a DBA is the dreaded:

ORA-01555 snapshot too old
and
ORA-22924 snapshot too old

Of course there are plenty of blogs instructing the DBA to simply “increase the undo_retention”, and there are cases where this works as expected. However, LOBs can be different as two different mechanisms exist for undo management. A LOB column can be configured to use retention to manage before mages of the data, but that can be confusing as each LOB column MAY have its own retention setting. The DBA_LOBS view reports whether LOG column uses retention or pctversion to manage undo, and the associated setting being used. Let’s -dig into this a bit deeper.

Read on to learn more about how LOB retention works, the types of issues you can run into with it, and how to correct those issues.

Comments closed

Augmenting the Gold Layer in Microsoft Fabric with Semantic Link

Nikola Ilic shows off one use case for Semantic Link:

I won’t spend time explaining what Semantic Link is – you can check a wonderful article written by my friend Sandeep Pawar, or refer to the official blog post. Sandeep’s blog post does a great job explaining not just what Semantic Link is, but also what are the possible use cases of this new feature.

Therefore, I will focus on explaining how you can leverage Semantic Link for a specific use case: I call it “Augmenting Gold Layer” (copyrights reserved). And, we will perform this “operation” by using SQL! Yes, you heard me well – we will leverage SparkSQL language to go above and beyond and “transform” the data currently sitting in Power BI datasets.

I will say that, for obvious reasons, this blog supports the Raw/Refined/Curated naming convention rather than Bronze/Silver/Gold, so I’d posit that this should be called the Augmented Curated Layer.

I can also recommend reading the blog post from Sandeep Pawar. It did a really good job of explaining why Semantic Link is worth getting excited about.

Comments closed