A Fine Slice Of SQL Server
Andy Leonard troubleshoots an error:
Have you encountered this error: “Failed Get Parameter Info of parameter ____”? I ran into this error a couple times while consulting for a client to lift and shift SQL Server Integration Services (SSIS) to Azure Data Factory (ADF).
Click through for an example and what is the most likely cause of the problem.
Comments closedHarshvardhan Singh has a few tips for us:
As with the other databases, indexing is the first go-to option to improve query performance. The same is the case with Cosmos DB as well. Below are a few points which you can leverage to optimize the indexing strategy for Cosmos DB.
Indexes are kind of similar to indexing in SQL Server in intent, though different enough in implementation that you’ll want to read up on them. Harshvardhan also includes some tips around data modeling and querying data.
Comments closedJose Manuel Jurado Diaz does some sleuthing:
In this blog article, we will delve into a common error encountered when synchronizing data with Azure SQL DataSync. We’ll explore the error message “Error #1: SqlException Error Code: -2146232060 – SqlError Number: 515, Message: Cannot insert the value NULL into column ‘ID’, table ‘dbo.Customers’; column does not allow nulls. INSERT fails. SqlError Number: 3621, Message: The statement has been terminated.” We will provide a detailed explanation of the error and its possible causes, followed by a T-SQL code snippet that reproduces the error scenario.
Click through for four possible causes.
Comments closedSabyasachi Samaddar has an interesting project:
In today’s digital age, video content has become a powerful medium for communication and storytelling. Whether it’s for marketing, education, or entertainment purposes, videos could captivate and engage audiences in ways that traditional text-based content often cannot. However, creating compelling videos from scratch can be a time-consuming and resource-intensive process.
Fortunately, with the advancements in artificial intelligence and the availability of cloud-based services like Azure Open AI and Cognitive Services, it is now possible to automate and streamline the process of converting text into videos. These cutting-edge technologies provide developers and content creators with powerful tools and APIs that leverage natural language processing and computer vision to transform plain text into visually appealing and professional-looking videos.
This document serves as a comprehensive guide and a starting point for developers who are eager to explore the exciting realm of Azure Open AI and Cognitive Services for text-to-video conversion. While this guide presents a basic implementation, its purpose is to inspire and motivate developers to delve deeper into the possibilities offered by these powerful technologies.
Click through for a guide on how to do it.
Comments closedDavid Heinemeier Hansson shares a story:
The back of the napkin math is that we’ll save at least $1.5 million per year by owning our own hardware rather than renting it from Amazon. And crucially, we’ve been able to do this without changing the size of the operations team at all. Running our applications in the cloud just never provided the promised productivity gains to do with any smaller of a team anyway.
I’ve never been a big fan of the “Move to the cloud to save money!” story that vendors tell. There are specific advantages, but saving money (as in, my overall IT expenditures are less than what I was spending before moving to the cloud) is more rare than common, in my experience.
Comments closedA lot of my customers have a business requirement that –
- once a document is written in storage account, nobody shall be able to modify or delete it, including the administrators
AND / OR- audit data can be written only once, and nobody shall be able to alter them.
These kind of business requirements are called WORM (Write Once, Read Many) and are common for various industries such as ISVs, financial or healthcare. Have you run into these mission-critical requirements? If yes, then immutable storage would be the solution.
Read on to see how this works, using retention policies. But ash Khushbu notes, if you set an absurd retention policy (up to 400 years), you can’t change the data while that policy is active.
Comments closedBeginner’s Hadoop gives us an overview:
The Databricks Unity Catalog is a feature provided by Databricks Unified Data Analytics Platform that allows you to organize and manage metadata about your data assets, such as tables, databases, and views. It provides a centralized metadata repository that enables users to discover, understand, and collaborate on data assets within a Databricks environment. The Unity Catalog integrates with various data sources and supports different metadata management capabilities.
Read on for an overview of what it does.
Comments closedDid you know Azure Data Factory (ADF) will actually list available properties? It will. One of the things I cover in my ADF training titled Master the Fundamentals of Azure Data Factory is this handy troubleshooting tip.
Read on to see how, though I’d personally like something which is a bit faster than waiting for the thing to execute and getting back what my choices are.
Comments closedUst Oldfield ties together Databricks and Microsoft Fabric:
We’ve built countless Lakehouses for our customers and influenced the design of many more. With the advent of Fabric, many organisations with existing lakehouse implementations in Azure are wondering what changes Fabric will herald for them. Do they continue with their existing lakehouse implementation and design, or do they migrate entirely to Fabric?
For many, the answer will be to continue as-is. They’ve invested a lot of time and money in establishing a Lakehouse – to migrate now to a slightly different technology stack would be a very costly exercise! There also isn’t a need to migrate from a lakehouse implementation in Databricks to one in Fabric as there aren’t concrete benefits to be realised.
For those using Power BI as their semantic and reporting layers, as well as using Databricks SQL or Synapse Serverless as the serving layer, Fabric provides a perfect opportunity to rationalise the architecture and to bring about substantial performance gains through the Direct Lake connectivity and V-Order compression in Fabric.
Read on to see what Ust means, using a couple of architecture diagrams along the way.
Comments closedKhushbu Ghandi puts a padlock on it:
Resource locks are just locks that we can associate to different scopes in Azure allowing us to override permissions at that resource scope and down. When we talk about the scope of the resource lock, we can lock subscriptions, we can lock resource groups and individual resources, and the lock restrictions that we have based off the type of lock we select will apply to all users and roles that have access to that resource. Also, it’s worth noting that locks are inherited by child resources. So, if we apply a lock on a subscription, it is inherited by all the resource groups that have been created under that subscription along with the resources that will be created under the resource groups.
Resource locks come with their own considerations, and Khushbu dives into those. This is a concept I like more in theory than in practice, save for pretty stable systems where you keep things running 24/7.
Comments closed