Power BI

  • Parameters and Functions in Power BI / Power Query–Custom Functions

    image

    Power Query has over 600 native functions and the Power Query team keeps adding more and more.

    I wouldn’t recommend memorizing them, but you do need to understand the concept of parameters and arguments in order to understand what functions are.

    In this blog post I’ll go over what Custom Functions are and how you can create them. Be sure to check out Part 1 of this series before reading this one.

    M Functions

  • Parameters and Functions in Power BI / Power Query – Main Concepts

    image

    Power Query or the Power BI Get Data Experience uses a functional language called M to perform its Data Preparation or Data Transformation processes.

    You can read this article to get to know more about Power Query and the M language, but in short, Power Query is the interface that assists you, through buttons and dialogs, to create the M code for you.

    Now, where would I see a function, an argument or a parameter in Power Query ?…and what are they? Let’s have a quick example to see them in real life.

  • The most important thing to learn when using Power BI

    image

    You’ve started OR you’re in the middle of your Power BI journey and you’re confused as to where you should allocate your learning time and efforts

    Should it be DAX? Understanding the visualizations? the M language? Power Query? Power Pivot?

    SOOOO many keywords that appear when doing a simple online search, but WHAT is the core of everything inside of Power BI?

    This article covers my thoughts on where you should primarily focus your efforts when learning Power BI – let’s find out what is the HEART of Power BI.

    After spending more than 6 years using the toolset and going through various iterations and stages of what we now know as Power BI, these are my own thoughts and what I’ve found works best for the people that I’ve trained over the years.

  • New and First Forum for Power BI, Power Pivot and Power Query in Spanish

    image

  • Merge Operations in Power BI / Power Query – Part 6: Full Outer Join

    image

    This is the last post in the series! I highly encourage you to read Part 5 of this series before reading this one, but nevertheless, you can jump right in if you know the basics of Merge / Join Operations inside of Power BI / Power Query.

    We will be using the same sample data that we used in Part 5, but this time we’ll have a completely new goal which is probably one of the most frequent ones that I’ve had when Modelling data for Power BI.

    In this, Part 6, we’ll go over the Full Outer Join from a purely practical standpoint.

  • Merge Operations in Power BI / Power Query – Part 5: Inner Join

    image Similar to the previous posts in this series, I highly encourage you to read the first 4 Parts ( 1 | 2| 3 | 4 ) that I’ve published so far around Merge / Joins inside of Power BI / Power Query.

    So far I’ve covered:

    • Left Outer Join
    • Right Outer Join
    • Left Anti Join
    • Right Anti Join

    In this, Part 5, we’ll go over the Inner Join from a purely practical standpoint.

  • Merge Operations in Power BI / Power Query – Part 4: Right Anti Join

    image

    Similar to the previous posts in this series, I highly encourage you to read the first 3 Parts ( 1 | 2 | 3 ) that I’ve published so far around Merge / Joins inside of Power BI / Power Query.

    So far I’ve covered:

    • Left Outer Join
    • Right Outer Join
    • Left Anti Join

    In this, Part 4, we’ll go over the Right Anti Join from a purely practical standpoint.

  • Merge Operations in Power BI / Power Query – Part 3: Left Anti Join


    If you haven’t read Part 1 and Part 2 of this series, I highly recommend that you read those prior to this post.

    In those previous posts, we went over the Left Outer Join and Right Outer Joins. At this point we got the basics on how Joins / Merge operations work inside Power Query / Power BI. It’s time to get even more clever with the usage of Merge Operations.

    In this, Part 3, we’ll go over the Left Anti Join from a purely practical standpoint.

  • Merge Operations in Power BI / Power Query – Part 2: Right Outer Join

    image

    If you haven’t read Part 1 of this series, I highly recommend that you read that prior to this post.

    In that previous post, we went over the Left Outer Join and some basics on how Joins / Merge operations work inside Power Query / Power BI where the position of the table (first one or second one), the columns being used of the join and my desired goal (aggregation vs expand operation) all have an impact on the whole Merge experience.

    In this , Part 2, we’ll go over the Right Outer Join from a purely practical standpoint.

  • Merge Operations in Power BI / Power Query – Part 1: Left Outer Join

    If you’ve used Power Query or Power BI before, you’ve probably seen the “Merge” button which displays a window like the following:

    image

    and this let’s you join 2 tables (or queries), and one of the questions that I get pretty often is: “What’s up with all of those ‘Join Kinds’ ? when should I choose which one?”

    and that’s why I’m writing this series of blog posts around this specific topic from a purely practical standpoint so you can get a glimpse of what each one of those merge operations can bring to the table.

    In this, Part 1, we’ll start with the default join which is the Left Outer Join.

  • Comparing Similar Products (Movies) with Power BI

    Back Story: Back in the day, I used to work for this company with a truly all-star / amazing team. We were all part of this company called 20Th Century Fox, and we were in charge of the Theatrical distribution of films in Central America.

    Business Intelligence wasn’t a standard in the industry – at least not how we know BI nowadays, and I was the main person leading the charge of using BI tools to analyze the sales aspect of the business – specifically the Box Office. And that’s how I found PowerPivot (without the spaces back then) and the DAX language. I went deep into it and even took the online Power Pivot Workshop that Marco & Alberto used to deliver back in December of 2011 .

    I was able to implement a WHOLE bunch of reports, analysis and dashboards thanks to Power Pivot, but one thing that I couldn’t implement back then (because I started the journey with my own company), was a Comparison of “Similar” movies for the release planning of an upcoming movie.

    See…before a film gets to a certain theater / cinema / studio / location, it has to go through a certain planning phase. It starts with an estimate on how much that movie might be able to make, but….how can we tell?

    Well, you had a few options, but in the end it was all a manual approach where you’d need to think about what movies might be similar to this one (from every single perspective that you can imagine). Then you’d go through the system and search for every single similar movie one by one so you can grab what was the total gross revenue for each.

    What if…you had a table for all the similar movies (usually called Comps) and you could simply select the Movie that you’re interested in and it’ll display all of the Comps?

    Of course, this doesn’t only apply to movies, but to any product / service that you’d like to compare against similar products.

    This is where this blog post comes in!