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Day: April 12, 2022

From Confluent Cloud into Azure Synapse Analytics

Jacob Bogie and Dustin Vannoy show how to integrate Kafka in Confluent Cloud with pools in Azure Synapse Analytics:

Just released this fall, is the fully managed Synapse Connector. Azure Synapse Analytics provides a platform for data analysts and data scientists to analyze and combine data from multiple sources. Within Confluent Cloud, data can be synched to dedicated SQL pools via the fully managed Synapse sink connector and attached to Synapse Analytics workspace. Once added to the Synapse Analytics workspace, analysts have the ability to perform advanced analytics and reporting on data in the Confluent pipeline. The ability to access event-level data enables event-level analytics and data exploration.

Click through for two examples, one of loading data into a dedicated SQL pool and one of streaming data into Spark Streaming running on (naturally) a Spark pool.

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Role-Based Access Controls in Redshift

Milind Oke, et al, describe RBAC in Amazon Redshift:

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. One of the challenges with security is that enterprises don’t want to have a concentration of superuser privileges amongst a handful of users. Instead, enterprises want to design their overarching security posture based on the specific duties performed via roles and assign these elevated privilege roles to different users. By assigning different privileges to different roles and assigning these roles to different users, enterprises can have more granular control of elevated user access.

In this post, we explore the role-based access control (RBAC) features of Amazon Redshift and how you can use roles to simplify managing privileges required to your end-users. We also cover new system views and functions introduced alongside RBAC.

Read on to learn about system-defined roles as well as creating user-customizable roles.

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Filter Context in DAX

Marco Russo and Alberto Ferrari explain the idea of filter context:

This article is part of a series of articles about the basics of DAX. In a previous article, we introduced the first evaluation context in DAX: the row context. If you are not familiar with the row context, we strongly suggest that you start by reading that article first. Here, we build upon your knowledge of the row context to introduce the second evaluation context: the filter context.

Be mindful that the most relevant information you need to master about evaluation contexts is the difference between the row context and the filter context. You cannot appreciate any difference until you know exactly what the two contexts are. This is the reason why approaching the filter context without any existing knowledge about the row context would be only partially useful.

Read on to understand how this all differs from row context.

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Using the Azure Synapse Analyzer Report

Sanjay Raut introduces an interesting report:

The Azure Synapse Analyzer Report was created to help you identify common issues that may be present in your database that can lead to performance issues. This report focuses on known best practices that Microsoft has identified with SQL Dedicated Pools. Following these best practices will help to get the best performance out of your solution.

One thing I appreciate about this is that it covers many items which people don’t know to think about when moving over from SQL Server or Azure SQL Database.

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Thinking Azure Data Platform Security Architecture

Craig Porteous begins a new series:

Reference architectures are great! You’ve got all of the key components in there, nice and clear. Colourful lines showing how data moves through each stage, product, or service. Great for a slide deck or a proposal to get rid of that old creaking data warehouse and into a shiny new Data Lakehouse.

Not so great for the finer details demanded by security operations teams however.

This promises to be an interesting series.

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Restarting Azure Data Factory Triggers

Andy Leonard provides an after-action report:

During delivery of the class, I popped over to a much older data factory and fired up a couple integration runtimes (IRs). You see, on this older data factory, I trigger a couple pipelines that check to see if I’ve left an IR running. If so, each pipeline will shut down its respective IR. The trigger fires each evening. I blogged about the pipeline design almost two years ago in a post titled  Stop an Azure-SSIS Files Integration Runtime (Safely).

Read on for the full report, some takeaways on how to limit the risk, and possible next steps if you find yourself in a situation like Andy did.

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Walking through the Azure Log Analytics User Interface

Robert Cain starts a new series on KQL:

The area in the upper half is where you enter the query you want to run. The lower half is where the results are displayed. We’ll see an example of this in action later in this post.

Just above the query area is a toolbar. The Run button will execute the query you’ve entered. Note too, you can use the keyboard command SHIFT+ENTER to run a query. I’m a keyboard guy, so this is what I use most often to run queries, which you’ll see if you take either of my KQL courses on Pluralsight (I’ve linked to them in the Conclusion of this post).

Read on for a walkthrough of the product. Robert also mentions his Pluralsight course, which I thoroughly enjoyed and used as research materials for a talk I put together.

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