What are Monkey Shorts?

The whole concept of this series of videos is to provide short videos on Excel and Power BI content.  Each of them is quite targeted, with a maximum of 3 minutes of technical content.  Today's episode - on sorting Power Pivot backed Slicers and Pivots - is actually the 6th in the series:

I'm releasing new episodes released every Thursday at 9AM Eastern Time.  You can find the entire playlist (and subscribe) here.

What else is on Skillwave's YouTube channel?

Great question!  In addition to the Monkey Shorts videos, you'll also find more free video content as well:

• Matt and I will be hosting a monthly "Ask Skillwave" livestream, where you can ask questions you'd like us to answer related to Excel, Power BI, Power Query, Power Pivot, DAX and generally all things data.  You can find that playlist here.
• As Skillwave is the main sponsor for the free Vancouver Power BI and Modern Excel Usergroup meetup, that's where we will be hosting all meeting recordings in future.  So feel free to join as live, or watch it later.
• We've also just added a new playlist for non-scheduled "video blog" content.  While we don't have anything in that playlist just yet, you should see some material coming there fairly soon.

In short, if you haven't landed there yet, you definitely should.  And don't forget to subscribe to Skillwave's YouTube channel so that you can get updates as we release new content there.

What's the Blog's Future?

As many of you know, I have a lot of irons in the fire.  This is not an exhaustive list, but here's just a few:

• Producing content for the the Skillwave YouTube channel
• Producing new and updated material for our Skillwave Training courses
• Coaching the students of my Self Service BI and Excel Fundamentals boot camps
• Supporting Monkey Tools

So while I will continue to blog from time to time, the reality is that I'm going to be focusing more on these other areas.  I'm finding that the video and in-person offerings are more satisfying as a creator, as it gives me the chance to interact with more people.  So it's not going anywhere, but my free content will definitely be shifting more to Skillwave' YouTube for the foreseeable future. I hope to see you there!

The post Monkey Shorts appeared first on The Excelguru Blog.

Maybe you're interested in knowing:

• Why this book isn't just called 'M is for Data Monkey v2"?
• Where the title 'M is for Data Monkey' came from?
• How Miguel and I determined what was going to be included?
• Why it took so darned long to get finished?
• When hard copies will be available?
• How you can get started writing your own book?
• Something else entirely!

Overall, Fireside Chat with a Data Monkey is intended to be a relaxed and social discussion around writing and publishing a technical book on an ever changing technology.  It's a place for me to connect with you, and just chat.

In preparation for the chat, I'd like to invite you to ask the questions you'd like me to answer, which you can do via the Fireside Chat survey. This session is intended to answer YOUR questions, so please feel free to submit any (and all) questions your have, including items from the list above (if they are of interest to you.)

In addition, if you'd like to join the webcast, why not add it to your calendar now so that you don't miss it!

We put a great deal of thought and work into writing Master Your Data with Excel and Power BI. I'm very much looking forward to chatting with you all, and sharing some of the experiences that went into making writing it.  So grab a beer and/or a coffee, and I hope to see you there!

The post Fireside Chat With a Data Monkey appeared first on The Excelguru Blog.

Monkey Tools Roundup - Summary Jan to Aug 2021

Monkey Tools automatically checks for updates every couple of weeks, and most of the time you’ll find that a new one is available for installation.  Once thing we don’t do a very good job of, however, is telling you what’s in them.  Often times they are just bug fixes, but they also include new features.  Typically we’ll announce those during user group presentations with a demo, but not always.

Release Summary

Here’s a summary of the major releases we’ve released so far in 2021:

For reference, this isn’t all of the releases, just the biggest ones.  There were about a dozen other releases scattered throughout this window as well.  Those were mostly related to fixing bugs, but also included some internal work that we did in order to improve our Monkey’s brain, as well as provide us with the ability to incorporate Beta features to specific audiences.

Monkey Tools Roundup – Features Released

A big reason for the Monkey Tools Roundup is that we’ve been a bit remiss in telling people about these new features.  So let’s look at the specific features that we’ve added to the tool so far in 2021.  We’ll start with the oldest first…

Added Option flag for new PivotTable buttons

If you are on Office365, you may have received the new experience where the Insert -> PivotTable menu no longer contains “PivotTable” and “Recommended PivotTables”, but rather is split across three buttons (as shown in item 1 of the image below).

We love this new menu, and really wanted to incorporate those buttons on our Pivots & Filters menu as shown in item 3 above.  Unfortunately, we have no way to programmatically identify if you have them or not, which meant that we have to serve a menu that looks like item 2.  To solve this we added an option under Options -> Global Options -> Use Legacy PivotTable Menu Buttons.  By default this is checked, returning the view shown in item 2. But if you have the left hand menu shown above, just uncheck it and you’ll have a menu that shows like item 3.

Query Monkey -> Create Query From M Code

There are many times where I copy a query and need to paste it into Power Query.  The feature allows you to do this, but also allows indenting and choosing the load destination right up front. It was designed primarily to assist with copying and pasting samples when helping users in forums, but can also be a handy form if you have a library of queries that you maintain outside Monkey Tools.

The SCD2 Monkey

In our Dimensional Modeling course at Skillwave, we spend about an hour going through the manual process in order to solve the Type 2 Slowly Changing Dimension challenge.  This feature allows you to solve the same goal in under one minute.  It is fully configurable for keys with or without meaning. Granted, it does require some understanding of dimensional modeling, but for those who run into the issue, it’s sure to save you a TON of time.

If you’d like to understand the background of how (and why) this feature exists, you should watch the recording of Quickly Solving the SCD Challenge on my YouTube channel.  The first 48 minutes show the manual way to solve the challenge. From minute 48 on you can see the demo of this tool in action.

Import Monkey

Since the initial release of Monkey Tools, I’ve always had the goal of adding this feature.  Import Monkey allows you to import your models from either a Monkey Tools backup file or – more impressively – Power BI Desktop files, recreating them in Excel.  While there are things in Power BI that we can’t bring backwards, there is a great deal that we can recreate including queries, relationships and measures.  And what we can’t build for you, we’ll report.

For a full demo of how the Import Monkey works – as well as an overview of a ton of other Monkey Tools features – check out the webcast that I did with Reid Havens.

Measure Monkey -> Filter Context Measure

One of my students asked for this during one of the AMA sessions of my Self Service BI Bootcamp. We thought it was a good idea as they were copying and pasting back and forth from other applications to make it happen.  This feature basically allows you to create a measure to return the filter context of a given cell into a PivotTable.  I can’t claim credit for the DAX pattern itself, but giving you a variety of options to create the measure is something that we’re proud of:

And after adding this measure to a PivotTable, it nicely shows the filter context at every given row/column intersection:

DAX Table Monkey

This feature was discussed and demonstrated in my Creating Unpivotable Charts presentation for the Vancouver Power BI and Modern Excel user group.  (It makes its first appearance at approximately minute 48 of the presentation.)  Basically, what it does is allow you to create tables in the Excel worksheet that retrieve values from the data model via DAX queries.  While the meet-up recording does still mention that it is in Beta, it is fully release in the software.

Detailed Error Logging diagnostics

This is honestly something that I hope you’ll never need: in order to help debug issues with Monkey Tools, we’ve added a flag to turn on detailed error logging to a file for the current session.  It can be turned on in the Global Options and is super helpful tracking down the source of bugs that people report to us so that we can fix them.

Insert a fnGetMonthEnds function

This new feature injects a handy little function which will return a table of the Month-Ends between two dates, as shown here:

This pattern is actually super helpful, especially if you need to allocate items over a given number of months: a technique that I’m going to be demonstrating in a session called “Several Ways Since Sunday” on August 29, 2021.

Monkey Tools Roundup – What We Are Working On

To finish off our roundup, I figured I should add a quick note as to what is coming up next.  We’re not promising a lot of new features over the next couple of months.  The reason for this is that we are actually doing a lot of internal work on the Monkey’s brain at the moment.  We’re refactoring a lot of old code to make it more robust and scalable, which will allow us to add some other cool things that we are unable to accomplish currently.

Having said that, we do have some features in the pipeline as well, but it is a bit too early to share details about what they are.  If you have ideas that you’d like to see in Monkey Tools, please do share them with us.  You can do so via our Feature Request form.

I hope that this has helped enlighten you as to the new features that have arrived this year.  We’ve still got a lot of stuff on our list, one of which is being a bit more pro-active about announcing what has happened!

The post Latest Monkey Tools Roundup appeared first on The Excelguru Blog.

The Goal:  Label Duplicates with Power Query

Our original source data is shown in blue columns below, with the green column on the right being the one that we want to add via Power Query.  (The white column on the far left contains rows numbers.  They aren’t actually part of our source data at all and are only intended to make it easier to follow the explanation below the image.)

The important things to notice here are:

• Row 2 of the table records the initial entry for SKU 510010 (Canadian), with a duplicate on row 12
• We have an original entry of SKU 510032 on row 15 and a repeat on row 18.

The key thing that we want to ensure as we flag the duplicates in this scenario is that the sort order is always retained as per the original order of the data source.  While you’d think this shouldn’t be hard, the reality is that there are many occasions where Power Query will re-sort your data on the fly, and we cannot let that happen here.

Getting Set to Label Duplicates with Power Query

The way I would approach this task – providing that the data has already been loaded to Power Query – is to do this:

• Add an Index Column --> From 1
• Select the SKU column --> Transform --> Group By
• Configure the “New Column Name” to call it “Data” using the “All Rows” aggregation --> OK

• Go to Add Column --> Add Custom Column and use the following formula:
  • Table.AddIndexColumn( [Data] , "Instance" , 1 )
• Right click the Custom column --> Remove Other Columns
• Expand all columns from the Custom column

Now, if you’ve been following my work at all, you may recognize the data pattern I just used.  It’s called Numbering Grouped Rows, as is available as one of the Power Query Recipe cards and is also illustrated in Chapter 13 of my Master Your Data for Excel and Power BI book.  The result is a data table that looks like this:

As you can see, the Index column preserves the original row numbers of the data set.  In addition, the “Instance” correctly records the order of their appearance in the data set.

Applying Labels to the Duplicates

This is the easy part:

• Go to Add Column --> Conditional Column --> name it “Occurrence” and configure it as follows:
  • if the Instance column equals 1 then return the Original column else return the Duplicate column
• Sort the Index column --> Sort Ascending
• Select the Index and Instance columns --> press the DEL key
• Set the data types of each of the columns

And that’s it. The data points have all been labeled and can now be loaded to the desired destination:

If you'd like to play with this scenario, you can find the completed sample file here.

Learning More

I love data patterns and include a ton of them in Master Your Data with Excel and Power BI, our Power Query Recipe cards.  Both of those resources are also included in our Power Query Academy video course as well, where you can actually see them performed live.  I have to say - of all the recipes I have - Numbering Grouped Rows is one of my particular favourites.  It has a ton of utility in all kinds of scenarios.

The post Label Duplicates with Power Query appeared first on The Excelguru Blog.

You may have noticed that the past few months have been pretty quiet on the Excelguru blog.  A big reason for this is that I essentially went offline to focus on finishing this book.  As many of you know, it’s been pushed back before (more than once), and we wanted to ensure that this would not happen again.  I’m pleased to say that the final version has now gone to the printers, and we’ll see physical copies start being distributed by Mr. Excel and Amazon on November 1, 2021.  The even better news however, is that you can get your hands on a digital copy today, as Master Your Data for Excel and Power BI is now available for sale at Skillwave.Training.

What’s in Master Your Data for Excel and Power BI?

Miguel and I are super proud of what we’ve put together here.  This has been a very long journey to get to this point, and we wanted to make sure that we delivered the best book we possibly could.  With the exception of a few of the paragraphs in the Foreword and Chapter 0, the book has been re-written from scratch, covering much more material than was covered in M is for Data Monkey.  How much more?  M is for Data Monkey was 226 pages long.  Master Your Data for Excel and Power BI clocks in at 369 pages in total.

To give you an idea of the topics we covered in this book, have a quick peek at the table of contents:

• Chapter 0 - The Data Revolution
• Chapter 1 - Power Query Fundamentals
• Chapter 2 - Query Management
• Chapter 3 - Data Types and Errors
• Chapter 4 - Moving Queries Between Excel & Power Bl
• Chapter 5 - Importing from Flat Files
• Chapter 6 - Importing Data from Excel
• Chapter 7 - Simple Transformation Techniques
• Chapter 8 - Appending Data
• Chapter 9 - Combining Files
• Chapter 10 - Merging Data
• Chapter 11 - Web Based Data Sources
• Chapter 12 - Relational Data Sources
• Chapter 13 - Reshaping Tabular Data
• Chapter 14 - Conditional Logic in Power Query
• Chapter 15 - Power Query Values
• Chapter 16 - Understanding the M Language
• Chapter 17 - Parameters and Custom Functions
• Chapter 18 - Date and Time Techniques
• Chapter 19 - Query Optimization
• Chapter 20 - Automating Refresh

One of the biggest changes you’ll see up front is that in Master Your Data for Excel and Power BI, we tried to make sure we covered a lot up front about getting started with Power Query, understanding errors and query management.   It wasn’t until we got through those topics that we dove into specific data transformation techniques.  This was a slightly different approach to what we did with our first book.  While query management was covered briefly near the end of M is for Data Monkey, we changed that up this time, as we wanted to make this a practical guide that sets our users up for long term success as they build their solutions.  Mastering your data is about much more than just getting a transformation complete – it is about making sure that you can re-use it in future.

The Tricky Bits (for us)

When we were laying out the book, Miguel and I had a few different goals:

1. Make this an awesome resource for beginners
2. Include great material to up the game of intermediate users as well as seasoned pros
3. Create a useful resource that you’d go back to again and again
4. Write a book that will survive longer than six months
5. Deliver the book without delaying it again

Each of these is a challenge in its own way, of course.

The last point on the list is not totally in our control, of course.  In fact, less than an hour after I posted on my personal Facebook that the first draft of the book was done and sent to the publisher, Microsoft announced a visual refresh of Office on their blog.  (Fortunately, all screenshots that rely on the Excel ribbon have been updated to reflect the new design, putting that to bed for now!)  Naturally, new features will get added to Power Query, but our hope is that this book will still be accurate and useful for years to come.

With regards to making this an awesome resource for beginners, we have been teaching Power Query to beginners for a long time via our Power Query Academy, as well as in-person courses.  We have taken lessons from those experiences when deciding how to approach the material, balancing the speed and techniques used as we move through the material.  We’re confident that a new user to Power Query will be able to find the material accessible and approachable, and that the material in these pages will change their (data) life forever.

Building a book that also answers the needs of the intermediate and seasoned pro is a lot tougher, especially when trying to keep the material accessible to newer users.  We believe we’ve hit that balance and have added a ton of material to help people get deeper into Power Query.  From deeper explanations of Query Folding and the Lazy Evaluation engine, completely redesigned chapters on the M language and material that deals with Privacy and the ever-irritating Formula Firewall, we are sure that even the most seasoned pro will pick up some tips and knowledge from the material.

My Favourite Chapters

Honestly, I’m very proud of how everything came together, as well as the journey that we lay out for the reader.  But like anything that I put together, there are some chapters that I feel especially good about.

Chapter 2 on Query Management was something that I have wanted to include ever since I started teaching my Dimensional Modeling courses.  The section of that course is always an eye opener and I’ve lost count of how many times people tell me that it has changed the way they approach building their solutions.  It’s awesome to be able to put that information in writing, in a place that all our readers will be able to see it.

Chapter 9 on Combining Files is pretty awesome too.  It follows the steps outlined in my Power Query Recipe cards and will probably be one of the most impactful chapters in the book for many users: especially those who receive files on a monthly basis that need to be cleaned and combined.  The whole Combine Files experience was released to Power Query about six months after M is for Data Monkey went to print, so it’s great to finally be including the modern experience in Master Your Data for Excel and Power BI.

Chapter 10 is one that I’m particularly jazzed about.  My initial page estimate for this chapter was 12 pages… it ended up taking 21.  In that chapter we cover every native join that Power Query provides, plus a discussion on the Full Anti Join, Cartesian Products (cross-joins), Approximate Match joins and a comprehensive coverage of Fuzzy Matching.

Chapter 17 on Parameters and Custom Functions is another one that I just love.  Within the last two weeks I’ve actually reached back into that chapter twice on a personal basis to build solutions for clients.  We cover how to manually rebuild the whole Combine Files experience that Power Query does for you, and then build some increasingly complex examples, eventually landing on an improved fnGetParameter function that is built from scratch.  Super cool stuff.

Then there is Chapter 18, which begins with building several varieties of dynamic Calendar tables.  We’re not just talking about a list of dates, we’re talking about the patterns needed to build 12-month calendars with non-standard year ends, 445 calendars and more, including the columns that return the period IDs and dimensional fields for each. (These are the same patterns that we build with Monkey Tools!)  But that’s not all that is nestled in Chapter 18…  I also snuck in some methods to answer some questions that I get frequently from accountants: “How do I allocate my sales/expenses over x periods?”

There is so much material that we ended up getting into this book – some of which has never been seen before… I can’t wait for people to see it.

Getting Your Copy of Master Your Data for Excel and Power BI

If you are an active member of our Power Query Academy, or my Self Service BI Bootcamp, you’ve already got a copy waiting for you in your Skillwave dashboard.  And if you are an alumnus of the Academy (your subscription is no longer active), you’ll be getting an email over the next week to let you know how to claim your copy.

Physical copies won’t be fulfilled by until Nov 1, 2021 but can be pre-ordered via either the Mr. Excel store, or Amazon.  But if you’d like to pick up the PDF version, you can do so right now at Skillwave.Training.

The post Master Your Data is Now Available! appeared first on The Excelguru Blog.

Here is a fairly simple example with only three input queries (although my true setup actually has seven potential queries to select from:

How the setup is intended to work:

I have a named range called “User_Select” on my sheet that has a Data Validation dropdown with the names of my source queries:

And what I want to do is read the value from the User_Select named range into my query named Selection_Query. This provides a scalar value that matches the query I’d like to execute.

The Issues

• I do not want to land the multiple input queries on sheets (too much data involved).
• I am not a fan of Power Query Parameters for this approach, as they must be changed from within the Power Query user interface (I don’t really want my users going in there.)
• I do not want to use “brute force” – I want to do this programmatically so that it is easy to maintain in future.

What is the “brute force” method?

The brute force method is essentially coding a great big IF/THEN statement that contains each possible query.  Looking at the M code, you’d end up with something like:

let
Source = if SELECTION_Query = "Query 1" then #"Query 1" else
if SELECTION_Query = "Query 2" then #"Query 2" else
if SELECTION_Query = "Query 3" then #"Query 3"
// (and so on, and so on, and shoobie-doobie-doo ?)
else null
in
Source

The problem however is that each time I create a new “Transform” for a new vendor, or retire it from production, I would also need to come back and update my brute force query to reflect these changes.  It would be MUCH simpler if I only had to add/remove the query name from my drop-down list, and not worry about messing with the M code of my Selector query.

Some hope for building a SelectQuery function

On 19 Feb, Gasper Kamensek presented a session at VANPUG’s Power BI track that got me excited. In his presentation, he showed how to programmatically select from some LANDED queries using the Excel.CurrentWorkbook() statement in Power Query:

let
Source = Excel.CurrentWorkbook({[Name=Selection_Query]}[Content]
in
Source

Enter Expression.Evaluate

Now, that worked great for items that had been landed to a worksheet table and got me thinking about this some more.  The challenge I’ve been facing is that I need to select from queries which were NOT landed to a worksheet table and therefore don’t show up via the Excel.CurrentWorkbook() function.  Wondering if this was even possible, I asked my friend Ken Puls. And guess what he Puls-ed out of his bag of tricks?

Source = Expression.Evaluate("some text string", #shared)

Now, I had encountered Expression.Evaluate() in the Power Query M function reference, but it was not clear to me what it was intended to do. But after Ken and I bashed this back and forth a bit… WOW!  Does this ever have potential!

Ken explained that Expression.Evaluate() works very similarly to Excel’s INDIRECT() function - it takes an input and tries to evaluate it at run-time.  Unlike Excel, which seems to just evaluate the provided term against any and all Excel items, Expression.Evaluate() requires you to specify the library you want to use to interpret the code.  And that’s where the #shared parameter comes in, as this parameter provides a list of not only all Power Queries in the solution, but also all of the available Power Query functions.

So Ken’s suggestion was to pass the name of the query I wanted in to the Expression.Evaluate function, and evaluate it against the shared library. At that point – he told me – it should give me the results of that query.

Armed with this theory, I was eager to plug it in to my SELECTOR query, which gave me this:

let
Source = Expression.Evaluate(Selection_Query, #shared)
in
Source

AND IT DIDN’T WORK. ?

Expression.Identifier to the Rescue!

Turns out, it’s not Ken’s fault – I like to name my queries with spaces and leading numbers.  After a little digging, it became apparent that the Expression.Evaluate() needed me to refer to “Query 1” with a pound sign and quotes.

In other words, this DOESN’T work:

=Expression.Evaluate(Query 1, #shared)

But this DOES:

=Expression.Evaluate(#"Query 1", #shared)

So now I just needed to figure out how to automatically “escape” the query with the #” “ requirement where necessary.  I suppose I could have put those into my Excel drop down, but that would make the list values look kind of ugly, so I went hunting something a bit more elegant.

After poking around in the M manual, I found Expression.Identifier(“some text”), and guess what it does? It converts the name we see in the Queries & Connections panel into the correct “# and quote” syntax.

So that gives me:

let
qName = Expression.Identifier(Selection Query),
Source = Expression.Evaluate(qName, #shared)
in
Source

AND IT WORKS!

Completing the Solution

To make this as flexible as possible (and allow me to use it in other projects), I decided that building a SelectQuery function was the way to go.  So here’s what I ended up with:

The fxSelectQuery function:

(qName) =>
let
Source = Expression.Evaluate( Expression.Identifier(qName) ,#shared)
in
Source

And at that point, I can invoke whatever query I need by passing the results of the Selection_Query to the fxSelectQuery function like this:

The Output Query:

let
Source = fxSelectQuery(#"Selection_Query")
in
Source

And the end result is that I select the query I want to run from an Excel data validation list, click update, and I’m done.  How cool is that?

One caveat that I should probably mention here is that you must disable the formula firewall in order to use this setup.  You can do this by going to Get Data -> Query Options -> Current Workbook -> Privacy ->  Ignore.

You can download the example file here if you’d like to see the results of building a SelectQuery function in action.

The post Building a SelectQuery Function appeared first on The Excelguru Blog.

Centralized Dashboard

When you log in, you’ll be taken to your Dashboard immediately.  This is the one stop console that will let you access any of your active course subscriptions, review forum posts, download your files, and manage your billing and profile details.  We’ve worked hard to make this dashboard intuitive and easy to use as possible, and to make it look great on mobile as well.

Re-Designed Course Player

The course player is a completely custom built as well.  Of course, you’d expect to see your navigation menu on the left to get to your lessons, but we’ve also added a “Materials” fly out menu on the right where you can access files specific to any given lesson.

Community Forum Overhaul

We said is was a major redesign at Skillwave.Training, and we meant it.  One of our big goals here was to do a better job with the Skillwave help forum and foster a sense of community within it.  Our belief is that learning is great, but there can be another hurdle when trying to convert theory into practice with your own data.  We see the forum experience and Skillwave community as a crucial part of solving this issue, giving students the ability to:

• Ask questions about the course materials,
• Get help with applying techniques to their own data,
• Interact with other people in the same training,
• Practice applying their skills to other data sets, and
• Reinforce their knowledge and help others in the process.

Any of our clients who have an active subscription to one of our paid products will find a completely revamped forum experience.  As forum posters ourselves, there were a couple of very important things that we wanted to make sure that our community was provided a good set of tools for:

1. Asking To this end, we’ve made sure that we support topic tags, image and file uploads, code tags and a variety of rich formatting options.  (Our old forum was quite weak in this regard).
2. Answering In addition to the tools above, we’ve added the ability to mark questions as solved. Our forums are searchable based on topic tags, answered status, solved status and more.
3. Ensuring high quality answers. Our forum is private and monitored by our admin team.  Even if Matt, Miguel or myself aren’t the ones answering specific questions, we have a special “Recommended Answer” tag that we can apply to answers.  This serves two purposes to us: the first is providing assurance to the asker that they got a great answer, while the second is providing validation to a poster that they’ve provided a high-quality response.

Course to Question Integration

There’s one more really cool thing though… We also now give you the ability to post a forum question directly from a given lesson and provide links to all other questions that have been posted in this manner.  This serves both askers and answerers as it links directly back to the source of the question.  We’re super proud of this little feature and feel that it sets us apart from other platforms out there.  Not because other platforms don’t offer the ability to ask questions – they do.  But we serve all of that up right inside the lesson page.

Check Out the major redesign at Skillwave.Training

If you haven’t checked out Skillwave.Training yet, you really should.  We’ve got all kinds of great courses related to Excel, Power BI, Power Query and DAX.  You can even try out the platform via our free Power Query Fundamentals course.  You won’t have access to the forums on the free tier, but you’ll be able to experience the rest of our new platform.

As we've just launched the site, we'd love to get your feedback.  For the next month or so, you can do that by clicking the little Feedback widget on the right side of any site page.  Let us know what you think!

The post Major redesign at Skillwave.Training appeared first on The Excelguru Blog.

The Table Monkey

This feature was actually released back in December. However, since we announced it at the KSA meetup (which you can see on YouTube), we decided that it needed a personality of its own.  So now, on the Query Monkey menu you'll find the Table Monkey: a monkey who is dedicated to helping you build queries from Excel tables.

Some of the cool features of this Monkey are:

• It can create multiple "From Table" queries at once.
• Tables can be excluded with a single click.
• It can create "Staging" layers for you - as per our Dimensional Modeling course on Skillwave.Training, with custom staging layer names or counts.
• You can rename the Excel tables by right clicking on the blue boxes that represent the Excel tables.
• You can rename the Queries by right clicking on the green boxes that represent the data model tables.
• It allows you to toggle the end query so you can load it to the data model or as a connection.
• It provides a data typing algorithm that is smarter than Power Query's native algorithm.

Overall, we find this to be super useful. It allows us to create multiple table connections in a few seconds, rather than the minutes it would take us to set things up manually.

This feature is a Pro feature, but is fully functional in our free trial.

Create Query from M Code

The next feature that we included is a nice interface to create a new query from M code.  If you post in forums and need to quickly create a query for testing, you can simply take their code, paste it into the form, give it a name and click create.  Much easier than having to create a new query, edit the code, select everything and then paste:

The main benefit of this form is saving you the headache of jumping into the query editor to create your query. Additionally, we also added the ability to indent the code right in the form. So if you're just trying to read it, it can be useful without ever creating a query at all.

We feel that this would be a super useful feature for those helping each other in the community. Thus, this feature falls in to our "Forever Free" category and works at all license levels (include after your trial expires).

Convenience Features - Pivots & Filters

Another one of the new Monkey Tools features that we've added is a Pivots & Filters menu to the Monkey Tools ribbon.  This is purely a convenience feature. It's designed to bring the commands closer to you so that you don't have to do as much tab switching:

The version on the left is what we are terming the "Classic" view, which shows you the Insert PivotTable button (as well as PivotCharts, Slicers & Timelines).  The view on the right is what your menu will look like once the new Insert PivotTable button rolls out to your Office 365 install.  (If your Monkey Tools menu starts with PivotCharts, then head to our Options screen and uncheck the "Use Legacy PivotTable Menu Buttons" option.)

Bug Fixes

And - of course - like every release we do, we have included a bunch of bug fixes. Fixes that are applicable for all users including Pro, Trial and Free.

How to you get the new Monkey Tools features?

If you already have Monkey Tools installed, then head in to Monkey Tools -> Options.  If you are running 1.0.7678.28973, then you already have them.  And if not, click Check for Updates Now to update.

Don't have Monkey Tools installed?  You can try the full feature set for free for two weeks before the license reverts to a "free" license.  We think you'll be pleasantly surprised with how useful Monkey Tools is on a free license, and yet how much more it does in the Pro version.

The post New Monkey Tools Features appeared first on The Excelguru Blog.

GetISOWeek Function

One of my friends saw the ability to create a calendar using the Calendar Monkey.  While he was suitably impressed, he did also ask me if it could do something he badly needed, which was to create a column displaying the ISO week that is commonly used in Europe.  Unfortunately, the Calendar Monkey had not learned enough about ISO weeks at that time, so was unable to help. So, we sent a couple of the Monkeys back to school…!

If you are on a trial or free version of Monkey Tools, you will find that the Query Monkey will now allow you to add a custom Power Query function called GetISOWeek to your file.  From there, you can manually call this function via the Invoke Custom Function button, or via writing a formula in the Custom Column dialog within Power Query.  Simply feed the function any date column to get the ISO Week Number, and include “true” for the final (optional) parameter if you prefer the “precise” text version:

Of course, adding a new function in to your workbook is great, but for our Pro users, the Calendar Monkey wanted to make it even easier, and added it as a default column choice.  No fuss, no mess, just choose the ISO date formats you need and let the Calendar Monkey do the rest!

Measure Monkey – Basic Explicit Measures

While we are also super proud of our Measure Monkey who will help create Multiple Explicit Measures, we also realize that there are times where you need to create individual measures.  For this reason, we trained another Measure Monkey to do exactly that.

The Measure Monkey that focuses on Basic Explicit Measures provides you with a no-code experience to create… well… basic explicit aggregations.  (Yes, you could make Implicit versions via drag and drop, but serious modelers far prefer the more customizable and scalable explicit versions.)

This Measure Monkey will help you create these measures without writing a single line of DAX (although it does show you the DAX it has created.)  You will be provided a list of relevant aggregations (go home COUNTA!) and smart default formatting choices.  The Monkey will even capture your preferred defaults to make you even faster next time.

And, like its brother who builds Multiple Explicit Measures, this Measure Monkey will work for you for free!

Support for Non-English Queries

Did I mention that my friend whom I referred to above, runs a French version of Excel?  Unfortunately, Monkey Tools had some challenges reading the queries in his model correctly.  While we have always claimed that we only support English versions of Excel, this still bothered us.

One interesting part about being a coder is that MOST coding is written in English. But every now and then, Microsoft localizes something that we did not expect.  So was the case with the underlying Power Query connection name.  To make a long story short, I have now learned that “Query” is “Requête” in French, “Abfrage” in German, and has other localized words among other languages.  And now that we know?  We have retrained our tool to deal with this challenge.

What this means to you if you are a user of a non-English version of Excel is – while we are not quite ready to say we fully support all non-English versions of Excel – we do believe Monkey Tools should work no matter the localization of your Excel install.  (We do still recommend caution here.  Until we say we OFFICIALLY support all languages, please do try the Trial version before you buy, and let us know if Monkey Tools has any issues reading your queries!)

Feedback Mechanisms

Another question we received from time to time was “How do I give you feedback?” or “How do I report a bug?”  It was enough that we realized that we had done a poor job of giving you a mechanism to do so.  So to that end, we have added the following to the Monkey Tools Help menu:

• Log a Bug
• QuerySleuth Indenter Issues (for issues specific to QuerySleuth indentation)
• Feature Suggestions

Each takes you to a form that you can fill out to get in contact with the dev team.  And yes, we are open to hearing your suggestions!

Various Other Bug Fixes

Of course, no release would be complete without a few bug fixes.  There were a half dozen fixes that were included in the various November updates (plus another half dozen published last night.)  Each was minor, and not really worth mentioning on their own, but rest assured that we are trying to fix bugs whenever we find them.

What is the Current Version?

To make sure you have all of the current features, go to Monkey Tools -> Options.  If you are running a version that is less than 1.0.7640.41496, then click Check for Updates Now to update.

And if you don’t have Monkey Tools installed yet… what are you waiting for?  You can try the pro features for free for two weeks, and there are a ton of useful tools even if you don’t elect to purchase a pro license.  Click here to get your copy of Monkey Tools.  And hey… if you decide to upgrade to a Annual Pro license today, you can get 20% off with the code BF20MONKEYTOOLS.

So… What’s Next?

We are working on something cool that will help Excel modelers get started quickly.  And if you want to be one of the first to hear about it and see it in action you should attend the inaugural KSA Excel Power Platform meetup, as I’ll be demoing this new feature.

The post More free features in Monkey Tools appeared first on The Excelguru Blog.

If you follow Monkey Tools already, you’ll know that our goal is to help you build better models faster.  We already include helpful functions such as:

• the ability to inject a query that can automatically switch between local folders and SharePoint folders
• manage your queries via our Query Sleuth
• build calendar tables on the fly against your data
• and so much more...

But while we’ve had a nice tool to trace DAX query chains, we haven’t included a lot of DAX functionality to date.  That is changing today.  And oh… before we dive into it, I want to be clear that this feature will be available to ALL users of Monkey Tools.  Yes, even those of you using a Free license!

The Sample Model

Before we dive into this, let’s take a look at a sample data model:

Notice that everything is nicely created and linked (by the way - we created that calendar in a few seconds with Monkey Tools’ Calendar Monkey…) but that there are no DAX Measures on our Sales and Budget tables.  Date and Category are both foreign keys that link each of the those tables to the Calendar and Categories tables.  However, we really want explicit measures to sum both the Sales[Amount] and Budget[Amount] columns.

Of course, these measures are easy to write, but what if your model is a bit more complicated and there are ton of them to do?

Creating Explicit Measures in Bulk with the Measure Monkey

As of version 1.0.7599.31348, you’ll find a new Measure Monkey menu on the Monkey Tools ribbon for this exact purpose:

Step 1A: Which Tables Host The Columns To Aggregate?

When you launch the new feature, you’ll be taken to a screen that looks like this:

This screen in intended to allow you to tell the Measure Monkey which tables hold the columns you need to aggregate.  Our aim in this screen is to give you the highest possible chance of just clicking "Next". That being said, we realize that this may not work for everyone, so we also allow some flexibility here.

In the top left, we pre-select the tables which we believe have the highest chance of needing aggregation: your fact tables.  (Those tables with only ‘many’ sides of relationships attached to them.)  But if we get this wrong for you, you simply need to check the other boxes to include basic aggregations for other tables.  (Ideally, you shouldn’t be aggregating dimensions, but there are – of course – exceptions to every rule.)  You’ll get immediate feedback in the box in the bottom left, as we show all the tables that will be included based on your checkbox selections.

Step 1B:  Tell the Measure Monkey Where to Store Your New Measures

In the top right, we also allow you to tell us where you want to store the measures.  If you have created a specific “Measures” table, we’ll provide that by default.  If you haven’t, we’ll offer to store the measures on the Host Table.  (In other words, all measures created to aggregate columns from the Budget table will be stored on that table, whereas columns from Sales will be stored on Sales.)

Forgot to set up a new Measures table before doing this?  No worries, click the + to add a measures table on the fly, give it a name, and we’ll create it for you:

There are a couple of Advanced options as well, but we believe most people will want to leave these set based on their defaults.  So let’s click Next, to go to page 2…

Step 2: Choose Your Aggregations

This page contains a ton of info, but again we’re trying to provide you the biggest chance of clicking “Create” right away. Unfortunately, this is something that we can’t do in the image above…

The reason our Create button is disabled is that we have two measures offered with the name “Sum of Amount”.  The blue one is the first instance, and any subsequent measures with the same name will highlight in red.  So let’s fix those, and choose a default data type format:

It’s all good to go now, except that I want to add a “Transactions” measure that counts the rows of the Sales table.  So I’m going to click the “Add another aggregation” button in the Sales table. Then I choose the name of the table from the drop down list:

That will give me a new row with a “Count Rows of Sales” measure, which I can quickly rename to “Transactions” before clicking “Create”.

During this process, the Measure Monkey will create your measures for you. Plus, if you created a Measures table, it gives you some advice on how to make it an “official” measures table.  You can see the results in my data model here:

That was Easy…

The demo above was obviously a fairly simple model. Yet it cuts my explicit measure creation time down to less than a minute to create these two measures.  Now consider the time savings when you get a bit more complicated:

So how do you get the Measure Monkey menu?

This update to Monkey Tools is available in Monkey Tools 1.0.7599.31348 or higher.  And it's will be a “forever free” feature, so you’ll be able to use it on either a Free or Pro license!

To try our free trial, head over to the Monkey Tools product page to download your copy.

If you already have Monkey Tools installed, it will automatically update within a couple of weeks. Alternatively, you can request the update now by going to Monkey Tools -> Options -> Check For Update Now…

The post Introducing the Measure Monkey appeared first on The Excelguru Blog.