Power BI

  • Navigation Window / Folder in Power Query and Power BI

    Motivated by one of the latest videos from the MSFT guys behind Guy in a cube:

    where they talk about one of the hidden secrets behind Power Query / Power BI, I wanted to talk about another one of those hidden gems inside Power Query / Power BI that is not completely visible or intuitive for most folks when they start using the tool.

  • Results: The Best ETL tool for the Business Analyst–Tableau Prep vs Power BI vs Trifacta Wrangler (Google Prep)

    The results are in! Let’s find out which tool is better for the average Business Analyst based on the 3 scenarios that I showcased a few weeks ago here.

    I was able to get in touch with the Product Team from Microsoft’s Power Query and also the one from Trifacta’s Wrangler. I tried getting in touch with the Tableau folks, but they  never replied to my emails. Luckily, someone within Tableau’s Sales team did see my videos on YouTube and was able to give me a more refined view of what Tableau is capable of. Big thanks to everyone who helped me along the way through forum responses and multiple emails!

    We’re going to break this down by each scenario and then we’ll tally up the results to figure out who’s the winner.

  • New Web Scraping experience in Power BI / Power Query (Using CSS Selectors)

    The latest version of Power BI Desktop came out with a new Web Connector specifically designed for Web Scraping Scenarios. in this blog post I’ll try to go deep into how this new experience works and how you can take advantage of it.

    Before we move forward, you’re gonna need the latest version of Power BI Desktop (May 2018 for me) and also enable the Preview feature in the Options window:

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    My Scenario: Get Data From Amazon

    I want to find out how many books are out there that have anything to do with Power Query. I want the reviews that go with them, the name of the authors, when they were released and, of course, the names of these books.

    The best place to find this information is probably Amazon. So I went on Amazon and did a quick search using the keywords “power query”.

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  • First Impression on Power BI Incremental Refresh

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    Power BI just recently released the ability to set up Incremental refresh policies through the Power BI Desktop.

    This is a short blog post with my first thoughts on it.

    Everybody has been excited about the possibility of doing Incremental Refresh through Power BI. Back in the day, this was only something that you could accomplish using Partitions in SSAS, which would require a server and it didn’t use M syntax at all.

    Recently there have been new releases like Azure Analysis Services and new versions of Analysis Services that have Power Query integrated into it which allow for really dynamic M syntax. To this point, everything was through a SSAS but now we have the ability to basically create partitions through a Power BI Desktop model.

    I not only wanted to test this out by itself, but by combining it with my Custom Connectors. Could I create a scenario where I’m getting data from the WooCommerce API (using my Custom Connector from here) and set up an incremental refresh?

    Let’s find out.

  • The Best ETL tool for the Business Analyst–Tableau Prep vs Power BI vs Trifacta Wrangler (Google Prep)

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    I’ve been working with Power Query inside of Excel and Power BI for the past few years, but I’ve always tried to stay on top of its competitors, trying to make sure that I’m investing my time using the best tool that there is.

    This is one of those times where I allocate some time to find out if Power Query is still the best ETL tool for the Business Analyst out there.

    In this case I’m going to compare 3 tools:

    • Power Query inside of Power BI Desktop and representing Microsoft
    • Tableau Prep pka as Project Maestro ad representing Tableau
    • Trifacta Wrangler – representing both Trifacta and Google’s Data Prep (since for all intends and purposes, it provides the same UX for the end user)

    Disclaimer: I am in no way being sponsored nor promoted by any of these companies. I’m not a Microsoft MVP nor a Tableau Zen Master. My main goal with this comparison is to find the best ETL tool out there and use it.

  • Refreshing a Power BI Custom Connector in the Cloud

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    These are GREAT news! Finally we have a way to refresh data from custom connectors on the Power BI service.

  • The Navigation Step in Power Query and Power BI–Navigating to rows, columns and cells

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    What is a “Navigation” step in Power Query?

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    When using Power Query, you might’ve come across a step that reads “Navigation” and is usually automatically created for you by Power Query, but…what does it do?

    Well, if we look at the code that it was created for the Navigation step, it reads:

    = Source{[Item=”SalesTable”,Kind=”Table”]}[Data]

    It has some curly brackets mixed with some square brackets and some nomenclature that seems pretty strange at first. This is one of the ways that Power Query automatically creates a navigation step, but there are other ways to achieve the same result and depending on the situation Power Query might create a different code.

    This is the main reason why I’m writing this post. To document what are the ways that Power Query has in order to Navigate to a specific Column, Row or even a specific Cell.

  • Query Error Auditing in Power Query for Excel and Power BI

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    As any other programming language, Power Query handles errors in its own unique way and the goal of this blog post is to give you a few hints on how to audit the errors or warnings that Power Query might throw your way.

  • Data Types, Data Conversion and Ascribed Data Types in Power Query and Power BI

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    As we saw in a previous post, there are many things that we need to consider when dealing with Excel files since even the extension of an Excel file can dramatically impact your solution and how Power Query interprets the contents of that file.

    In a more broader sense, we also need to take in consideration 3 key elements that apply to every single data that lands inside Power Query :

    • Data Types – every field/column can have a specific Data Type associated to it
      • Data Type Conversion – every field/column can have its members (rows) converted to another Data Type as well as the Data Type of its field/column defined to a different Data Type.
      • Ascribing Data Types – instead of performing a conversion for every member of a field/column, we can simply define that the column should be considered of a specific Data Type without doing any conversion. This is considered ascribing a data type.

    You might’ve heard about Data Type Conversion, as it’s what Power Query automatically does when you click on the “Data Type” dropdown and select a data type for a column, but you can also do what it’s called Ascribing a Data Type, where you can define a new Data Type to a specific field/column without doing a conversion process. This post will showcase how to do this and what are the benefits of doing this.

  • Calculate Days between dates using Power Query / Power BI

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    Have you ever wanted to find out how many days you have between 2 dates? perhaps how many Mondays? how many Sundays? perhaps Saturdays and Sundays?

    Well, in this blog post I’ll show you how you can do that with Power Query inside of Excel and/or Power BI and how you can extend this to other scenarios.

  • Recurring dates with offset in Power Query


    Imagine this scenario, you are a Doctor who has multiple appointments with patients on a daily basis. Sometimes, you need to schedule follow up appointments with your patients just to make sure that everything is going according to plan and basically do a check up.

    You record these appointments in a simple spreadsheet like the following:

    Initial
    Appointment
    Patient
    Name
    Follow
    up Appointments Needed
    Frequency
    (every x days)
    11-Jan-18 Audie Livengood 3 14
    28-Oct-17 Curt Gatz 2 7

    Where, for example, the first row is telling me that the patient under the name of ‘Audie Livengood’ had a initial appointment on January 11th of 2018 and needs follow up appointments every 14 days, for a total of 3 follow up appointments needed.

    You want to calculate how your agenda might look like based on the appointments that you’re making and how many follow up appointments you’re needing on average per patient, so you want to use Power Query to calculate a table like the following:              

    Initial
    Appointment
    Patient
    Name
    Follow
    Up Appointments Dates
    1/11/2018 Audie Livengood 1/25/2018
    1/11/2018 Audie Livengood 2/8/2018
    1/11/2018 Audie Livengood 2/22/2018
    1/11/2018 Audie Livengood 3/8/2018
    10/28/2017 Curt Gatz 11/4/2017
    10/28/2017 Curt Gatz 11/11/2017

    Can you do this with Power Query? Yes! you can