A Fine Slice Of SQL Server
John Miner works a shift in the warehouse:
Many companies are leveraging data lakes to manage both structured and unstructured data. However, not all users are familiar with Python and the PySpark module. How can users with a solid understanding of ANSI SQL be effective in the Databricks environment?
Read on for the answer.
Comments closedReitse Eskens looks at a view of the data:
When you dig into Real time analytics, windowing has some extra fun stuff happening. A windowing function isn’t just a windowing function but it has something extra to go with it.
For this blog, I’m using the event stream created in an earlier blog.
Click through to see how it works and the types of windows that are available to you.
Comments closedJosephine Bush has an after-action report:
I did a couple of posts previously on dumping/restoring Azure PostgreSQL databases and also using the Azure migration tool. I had to ultimately do a combo of those because of the limitations of the Azure migration tool.
Read on for the process that Josephine went through to complete migration.
Comments closedMika Sutinen rounds up the usual suspects:
AWS, Azure and GCP all have a fully managed services for SQL Server databases. In this post, I’ll provide a brief overview of the offerings from these hyperscalers. While the main promise of the service remains the same across the hyperscalers, the capabilities, scale, and occasionally, the best use scenarios for each, differ.
Read on for a quick comparison of four offerings from the three cloud providers.
Comments closedAndy Brownsword has the right price in mind:
Its the time of year where things may winding down for the new year and we can get a bit of breathing room. With that free time you might want to try something new, let’s say some SQL Server in the cloud?
It could be a good time to start brushing up on new skills, seeing what the services have to offer, or maybe you want to start blogging!
You’re not going to be able to do a tremendous amount at these tiers, but it’s hard to beat that price.
Comments closedJon Voege has a collection of links for us:
This week, to round off the year, we try something different. I wanted to throw a shout out to all the community heroes out there, who also help make the most of Microsoft Fabric, through the use of Microsoft Power Platform (and vice versa).
Also, I wanted to highlight some of their contributions, and hopefully give you all a list of resources to peruse.
Click through for more than 20 links, showing how you can work with Power Automate, Power Apps, Power Pages, and data in Dataverse from Microsoft Fabric.
Comments closedTomaz Kastrun wraps up a series on Azure AI. First up is tracing in Azure AI Foundry:
Tracing is a powerful tool that offers developers an in-depth understanding of the execution process of their generative AI applications. Though still in preview (in the time of writing this post), It provides a detailed view of the execution flow of the application and the essential information for debugging or optimisations.
After that, we can see how to evaluate model results:
With evaluation you performing iterative, systematic evaluations with the right evaluators and measure and address potential response quality, safety, or security concerns throughout the AI development lifecycle, from initial model selection through post-production monitoring.
With the Evaluation in Azure AI Foundry, you can evaluation the GenAI Ops Lifecycle production. In addition, it also gives you the ability to assess the frequency and severity of content risks or undesirable behavior in AI responses.
Finally, Tomaz wraps up the series with some notes on documentation:
Documentation and material for Azure AI Foundry are plentiful and growing on a daily basis, since the topic on AI and GenAI is evermore so popular.
I appreciate the challenge that Tomaz has of putting together 25 blog posts in a month, especially when they’re all tied to a single theme.
Comments closedKevin Sookocheff noodles on a core concept:
At AWS re:Invent 2023, Amazon CTO Werner Vogels delivered a talk on the laws of frugal architecture. While I initially filed away those insights to review later, a year of cloud architecture experience crystallized a fundamental truth: in cloud computing, cost isn’t just a financial consideration — it is a first-class architectural concern through which we should design and optimize our systems.
Cloud providers charge for every conceivable resource: servers, API calls, data transfer, and computational milliseconds. But cost is more than just a line item on a monthly bill, it is a powerful forcing function that drives better architectural decisions.
Read on for more thoughts on the matter.
Comments closedTomaz Kastrun continues a series on Azure AI:
Models from the model catalog can be deployed using programming languages or using the Foundry studio.
Model deployment has two types: Deploy from the base model or deploy from the fine-tuned model. The difference is that fine-tuned model is model taken from the model catalog and later tuned to an additional dataset, as the base model is the model as it is available in Azure AI Foundry.
Click through for a bit more information on the process.
Comments closedTomaz Kastrun continues a series on Azure AI:
The management center is a part of the Azure AI Foundry portal. It gives you the overview on activities and governance. From management center you can manage Azure AI Foundry hubs, projects, resources, access, endpoints, models and other resources and general settings.
Click through for an overview of the management center and what it includes.
Comments closed