Performance, Optimization, and Intelligent Error Handling in Power Query

There are two cornerstones to building optimized and low maintenance queries in Power BI. The first is making sure queries have been designed to refresh at optimal speeds. Primary topics for performance tuning include: removing columns and rows, applied step configuration and order precedence, query folding, managing variables, and tables vs lists for transformations.

The other important cornerstone is intelligently identifying and handling errors as they occur during scheduled refreshes. Primary topics for error handling include: replacing vs removing errors, collecting error metadata, and configuring the refresh to either fail or refresh successfully when errors occur.

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Performance, Optimization, and Intelligent Error Handling in Power Query
Ruth  Nabimanya

Ruth Nabimanya

1625027400

Projection Queries: A Way to Optimize Data Traffic

JPA provides several solutions for projection queries and DTO mapping. It is up to us to choose the most appropriate solution for each of our use cases.

In our modern, highly concurrent world, enterprise application developers have to deal with new challenges like huge data volumes, diversity of clients, and permanently changing business requirements. Now, it is a usual case when a microservice application has to serve various clients, and some of them are other microservices. These factors imply higher requirements for controlling data traffic. We cannot afford to send any excessive data and we need to respond to each request with data well-tailored for this particular client.

One option of customizing data traffic is the usage of projection queries; that is, queries that return a projection of domain objects. Almost all enterprise applications use some kind of ORM technology, and JPA is a standard way for its implementation. So, let’s see how we can implement projection queries based on JPA 2.2 specification.

Suppose we are to implement a collection management online application. The domain system is the following.

#tutorial #big data #optimization #querying #projection queries #projection queries: a way to optimize data traffic

Ahebwe  Oscar

Ahebwe Oscar

1620185280

How model queries work in Django

How model queries work in Django

Welcome to my blog, hey everyone in this article we are going to be working with queries in Django so for any web app that you build your going to want to write a query so you can retrieve information from your database so in this article I’ll be showing you all the different ways that you can write queries and it should cover about 90% of the cases that you’ll have when you’re writing your code the other 10% depend on your specific use case you may have to get more complicated but for the most part what I cover in this article should be able to help you so let’s start with the model that I have I’ve already created it.

**Read More : **How to make Chatbot in Python.

Read More : Django Admin Full Customization step by step

let’s just get into this diagram that I made so in here:

django queries aboutDescribe each parameter in Django querset

we’re making a simple query for the myModel table so we want to pull out all the information in the database so we have this variable which is gonna hold a return value and we have our myModel models so this is simply the myModel model name so whatever you named your model just make sure you specify that and we’re gonna access the objects attribute once we get that object’s attribute we can simply use the all method and this will return all the information in the database so we’re gonna start with all and then we will go into getting single items filtering that data and go to our command prompt.

Here and we’ll actually start making our queries from here to do this let’s just go ahead and run** Python manage.py shell** and I am in my project file so make sure you’re in there when you start and what this does is it gives us an interactive shell to actually start working with our data so this is a lot like the Python shell but because we did manage.py it allows us to do things a Django way and actually query our database now open up the command prompt and let’s go ahead and start making our first queries.

#django #django model queries #django orm #django queries #django query #model django query #model query #query with django

sophia tondon

sophia tondon

1620885491

Microsoft Power BI Consulting | Power BI Solutions in India

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sophia tondon

sophia tondon

1619670565

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Performance, Optimization, and Intelligent Error Handling in Power Query

There are two cornerstones to building optimized and low maintenance queries in Power BI. The first is making sure queries have been designed to refresh at optimal speeds. Primary topics for performance tuning include: removing columns and rows, applied step configuration and order precedence, query folding, managing variables, and tables vs lists for transformations.

The other important cornerstone is intelligently identifying and handling errors as they occur during scheduled refreshes. Primary topics for error handling include: replacing vs removing errors, collecting error metadata, and configuring the refresh to either fail or refresh successfully when errors occur.

#artificial intelligence