Tag Archives: power query

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

    0 Comments

    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

    0 Comments

    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

    0 Comments

    image

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

    0 Comments

    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

    0 Comments

    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

    0 Comments

    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

    0 Comments


    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

    0 Comments

    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

    0 Comments

    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.

  • Clever Filters in Power BI / Power Query with Merge Operations

    0 Comments

    Power BI Clever Filters

    Have you ever wanted to do a specific type of filter that might be too specific to do with just the regular filter drop down or even the advanced filter operations in Excel?

    Let me give you an example of one of those scenarios. Imagine that you have a table like the following:

  • Extracting Header and Footer Values from Documents, Files using Power BI + Using PDF Connector

    0 Comments

    image

    Have you ever had a similar situation where a REALLY important value of the file is in either a header or a footer section? Let me give you a clear example with the following file:

    SNAGHTML18603940

    In the image above you’ll see that we have 2 values in the header section right under the logo of my company. Now, this is a PDF file, so we’ll connect to that PDF file, get the data underneath those header values (which is basically a table) and then create a new column specifically for the value of the Sales Group. You can imagine that I have a bunch of PDF files in a folder and each of those PDF files is for a specific Sales Group, so I need to have that value as a new column.