ITDA - Western Technical College

Learn how to save and edit a Power BI Desktop project.

Boost Collaboration in Power BI Desktop Using GitHub Integration Source Control + Versioning + Team Collaboration = Better BI Development   Introduction In the evolving world of data analytics, collaboration and version control have become essential. Power BI has long been a go-to tool for building ...

This is part 1 in my series on writing modern idiomatic pandas. Modern Pandas Method Chaining Indexes Fast Pandas Tidy Data Visualization Time Series Scaling Effective Pandas Introduction This series is about how to make effective use of pandas, a data analysis library for the Python programming language. It’s targeted at an intermediate level: people who have some experience with pandas, but are looking to improve. Prior Art There are many great resources for learning pandas; this is not one of them. For beginners, I typically recommend Greg Reda’s 3-part introduction, especially if they’re familiar with SQL. Of course, there’s the pandas documentation itself. I gave a talk at PyData Seattle targeted as an introduction if you prefer video form. Wes McKinney’s Python for Data Analysis is still the goto book (and is also a really good introduction to NumPy as well). Jake VanderPlas’s Python Data Science Handbook, in early release, is great too. Kevin Markham has a video series for beginners learning pandas.

It's difficult starting out with Pandas DataFrames. Learn how to load, preview, select, rename, edit, and plot data using Python Data Frames in this post.

Get easy access to data, improve data quality, and create synthetic data with the YData Fabric platform.

Oct 10, 2021 | History of Artificial Intelligence: machine learning and expert systems

This article covers the history of artificial intelligence from its beginnings with the work of Alan Turing to advancements at the turn of the 21st century.

This article is about the state of AI tools with Power BI, and how to use the model context protocol (or MCP) to interact with and control Power BI or Fabri

Newsletter #300 is a significant milestone for SQLBI: it marks nearly 12 years of sending our updates every two weeks. I thought this was a good time to cla

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Code for "Advanced data transformations in SQL" free live workshop - josephmachado/adv_data_transformation_in_sql

Joins represent the denormalization of data to create dimensions and add dimension attributes to fact tables for reporting. Group bys enable the creation of metrics that determine how your data is used to make decisions. If you have wondered Why do your joins often end up in a dense block that's hard to pick apart. Why are people running nearly identical queries with only different join combinations. How to avoid losing data when performing joins How group bys have been used to mask underlying data modeling issues Why a group by all is considered a red flag Then this post is for you. In this post, we will cover how to use joins and group bys, as well as what to look out for when using them. By the end of this post, you will know what to watch out for when you perform joins or group bys.

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An attempt to explain the estimation process in statistics in the simplest form.

This dataset shows the Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) that are currently registered through Washington State Department of Licensing (DOL).

SUMMARIZE is a very powerful and very complex function to use. This article describes its internal behavior, and provides guidance on how to use it. If you

The context transition in DAX is the transformation of row contexts into an equivalent filter context performed by CALCULATE and CALCULATETABLE. Managing th

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Discover the differences between Databricks and Snowflake and the similarities they share.

Understanding the Basics and Advanced Levels of Database Normalization