Monkey Tools is Here

We are super excited to announce that we’ve (at last) released the first version of our Monkey Tools software!  Ken has been working on this software on and off for the better part of 8 years now.  But after showing it to a friend in Wellington last year, we decided it was finally time to get serious.  We hired a full-time developer last summer and are finally ready to go live with the initial release!

What is Monkey Tools?

Monkey Tools is an Excel add-in (supported in Excel 2016 and higher) which provides tools for you - as a business intelligence author/reviewer - to:

  • Build models more rapidly
  • Follow recommended practices
  • Document your work
  • Audit files that you receive

It is targeted primarily at modelers and analysts who work primarily in Excel, but also push their models into Power BI.  (Our philosophy at Excelguru is to model in Excel first, then export to Power BI for reporting, sharing and security control.)

Oh, and super important… it installs on your system without requiring admin rights on your PC.  How cool is that?

What does Monkey Tools actually do?

Well… lots!  We’ve collected all the cool features under some themed buttons including:

  • QueryMonkey (for inserting new queries)
  • DestinationSleuth (to provide information on query load destinations)
  • QuerySleuth (helping understand your actual queries)
  • TimeSleuth (to benchmark query load times)
  • PivotSleuth (helping you diagnose Pivot Table field issues)
  • DAXSleuth (tools especially for working with DAX measures)
  • ModelSleuth (reporting on the properties of your queries and data model)

Cute names, right?  The Monkey builds things, and the Sleuths investigate things.  Here’s a high-level view of what they each contain.

QueryMonkey

Query Monkey gives you the ability to insert key queries like:

  • The famous “fnGetParameter” query and table (from Chapter 24 of M is for Data Monkey)
  • A “From Folder” setup that works with local and/or SharePoint hosted files
  • Dynamic calendar tables based on your data (for custom calendars, it even provides the option to insert the "periodicity" columns for Rob Collie's GFITW DAX pattern!)

The QueryMonkey provides a Dynamic Calendar generator

DestinationSleuth

Today, this is simply a viewer to visually indicate the load destinations of your tables (better than just “Connection Only” or “x Rows Loaded”).

The DestinationSleuth user form displays four different load destination types

QuerySleuth

This is a single form, packed with information and features such as:

  • A dependency/precedent tree view layout
  • Full colour display based on load destination
  • Colourful and indented M code
  • The ability to modify the M code and write it back to the editor WITHOUT LOCKING YOUR EXCEL User Interface!

The QuerySleuth shows a query dependency tree as well as indented and colourful M code

TimeSleuth

This feature allows you to time query execution in Excel, and even chart comparisons between them with or without privacy settings enabled.  If you’ve ever wondered which query is slowing down your workbook, or wanted to time test two different approaches, you may find this helpful!

A chart generated by Monkey Tools TimeSleuth user form

PivotSleuth

Have you ever seen that irritating “relationships may be needed” error when building a Power Pivot based Pivot Table, and wondered why?  Pivot Sleuth can tell you…

  • See the real, fully qualified names of the fields used in your Pivot Tables
  • Highlight potential or current issues in Pivot Table configurations
  • Debug cross filtering issues, “relationships may be needed” errors and errors where grand totals are returned for all rows on the Pivot Table

Debugging PivotTable errors with the PivotSleuth

DAXSleuth

We believe that measure dependencies are just as important as query dependencies, and this is the reason we build the DAXSleuth.  This form:

  • Displays a dependency/precedent treeview of your DAX measures
  • Provides a full colour display of Implicit and Explicit measures (with or without children), as well as Calculated Columns
  • Shows your DAX measures with colour highlighting in an indented format
  • Allows you to Indent, Un-Indent, Flatten, Duplicate and even Update measures without leaving the DAXSleuth
  • Exposes all locations a DAX Measure has been used (Pivot Tables, Pivot Charts, OLAP Formulae and Named Ranges), and even allows you to select those objects right from the DAX Sleuth!

Monkey Tools DAXSleuth user form in action

ModelSleuth

Have you ever had to provide documentation for your model?  Or picked up a model from someone else and had to review it?  The ModelSleuth provides reports and utilities such as:

  • A full model summary report showing key statistics about your tables, relationships, columns, measures and queries. (Trial and Free licenses are limited to every other record in this report.)
  • A model memory usage report, complete with how much memory is recoverable (for Excel based data models).
  • An unused columns report (for Excel based data models).
  • A DMV Explorer (for those who want to build their own reports).

Showing the impact of unused columns on memory via Monkey Tools ModelSleuth feature

Monkey Tools Supported File Types

The Monkey Tools add-in is compatible with Excel 2016 or higher, and can read from:

  • Excel files
  • Power BI Desktop files
  • Backup files (that you can export from the Monkey Tools software)

Will Monkey Tools get updates?

Oh yes, we have plans for many more features!

Our intended model is to deliver features (and bug fixes) as we develop them.  That means that there could be periods with no updates as we work on something big, or periods with multiple updates delivered in a single week.  We know that some people love frequent updates and some people don’t, so we let you control how often you get them:

Monkey Tools allows you to control update frequency

The key thing to recognize here is that we are not holding new features for a vNext. They’ll be delivered when they’re ready.

Can I try Monkey Tools before I buy it?

Ken did not become or remain a Microsoft MVP without contributing a large portion of tools and help to the community for free, and that won’t change.  Having said that, we’re paying a developer to work on this product full time and need to recoup those costs.  For that reason, we will always have both a Free version, as well as a Pro version.

Naturally, we want you to look at it, as we're convinced you'll like it.  And that's why we have a two-week trial that provides full access to almost all of the full feature set.  Once your trial expires, your license will automatically revert to a free license.  You’ll still get fixes and new features, they’ll just render in free mode (without colour, without field advice, etc.).  We do believe that you’ll still find the tool useful, just maybe not as useful without a Pro license.

Ready to learn more about pricing options and download the free trial?  Click here!

How do You Design Your Data Model?

On this blog, I showcase a lot of different techniques for manipulating and reshaping data.  For anyone that follows the blog, you already know this, and you know it's a pretty important topic to me.  But the thing we shouldn't lose site of is WHY we do this. It's to drive analytics. I'm fairly convinced that the majority of the loyal readers here already know this. Thus, I wanted to ask your opinion on something...

Raw data to data model, passing through the human brain

How do you design your data model?

What I'm specifically interested in is how you approach designing the Fact and Dimension tables you use for your Power Pivot model.  And I'm not specifically talking about Power Query here. We all know you should be using what you learned from our recently relaunched Power Query Academy to do the technical parts.  😉

What I'm more interested in is the thought process you go through before you get to the technical bit of doing the data reshaping.

If you read books on setting up a data model, you'll probably be told that you need to do the following four steps:

  1. Identify the business process
  2. Determine the grain of the model
  3. Design your Dimension tables
  4. Design the Fact tables

So if you're asked "how do you design your data model", do these steps resonate with you, and why?

Do you consciously sit down, and work through each of these steps in order?  I suspect that many self-service BI analysts skip the first step entirely as they are implicitly familiar with their business process.  (As a consultant, I ask a lot of questions in this area to try and understand this before building anything.)

Do you design the reports on paper, then work backwards to the data you'll need, go find it and reshape it?  Or do you go the other way, trying to collect and reshape the data, then build reports once you think you have what you need?

Do you explicitly define the model grain?  And if you do, what does that mean to you?  Is it restricted to "I want transactions at an monthly/daily/hourly basis"? Or do you do deeper like "I want transactions at a daily basis and want to break them down by customer, region and product"?

Why the question?

There's actually two reasons why I'm asking this question:

Reason 1 is that I'd I think healthy discussion makes all of us better.  I'd like to hear your thoughts on this as I'm probably going to learn something that I haven't discovered in my own learning journey.

Reason 2 is that my whole business is around teaching people how to do these things, and I'm always looking to make things clearer.  The more opinions I hear (even if they contrast with each other), the more I can help people understand his topic.

So sound off, please!  We'd all love to hear how you approach the task of building a data model.

Become a Data Master with Power Query

Ken is really excited to be teaching his popular Master Your Data with Power Query class for the first time in New York City! Join us this spring for a small group hands-on workshop and learn how to become a Data Master with Power Query.

Learn to become a Data Master with Power Query

Join Ken Puls for a live hands-on session in New York, NY on April 17, 2019.

What's so great about Power Query?

If there is one thing you need to learn in Excel today, Power Query is it. With Power Query, you can clean, reshape, and combine your data with ease. No more tedious cutting and pasting between multiple files. No more manually removing garbage rows or adding new columns. And no more repeating the same time-consuming steps whenever you need to refresh the data.

Instead, once you have your data the way you want it, all you have to do is click refresh and it will be ready to be loaded into the next day's/week's/month's/quarter's report. You can even schedule these refreshes to happen automatically!

What will be covered in the workshop?

The day will begin with a quick overview of Excel tables, PivotTables, and what makes "good" data. Next, Ken will show you how to import data from a wide variety of files, including Excel workbooks, CSV and TXT files, databases, and even entire folders. You'll be able to clean, transform, and refresh your data in Power Query with just a few clicks.

Ken will also show you how to append (or stack) data from multiple tables and 7 ways to merge (or join) tables without any VLOOKUPs. You'll be able to pivot data like this:

Pivoting Data with Power Query

and unpivot data like this:

Unpivoting Data with Power Query

But wait, there's more!

Ken will teach you some more advanced techniques using conditional logic. He will also give an overview of best practices for structuring your queries and query folding. Additionally, you'll receive a copy of the course slides to refer back to. Many of these slides contain handy recipes that will lead you step-by-step through the data transformation techniques.

Not only that, you will be able to directly ask a leading Power Query expert to help you with challenges you are currently facing with your own data. That kind of in-person access is invaluable!

How can Power Query help me?

A data wrangler spends the majority of their time just gathering, cleaning, and preparing the data before it can be even used in a report, chart, or other data model. Instead, become a Data Master with Power Query and get hours of your time back. For example, Ken was able to help a workshop attendee automate a workflow in 30 seconds, saving them 6 hours per week!

Power Query is the data preparation tool of the future, not only for Excel but also for Power BI Desktop, Microsoft Flow, and more. Thus, everything you learn in this course is transferable to other technologies - giving you more bang for your buck.

How do I make the case to my boss for sending me to the course?

As Ken mentioned in a previous blog post, the cost of the course can look like a lot up front. This is especially true if you must also pay for travel, hotel, etc. But divide the $499 USD registration fee + any expenses by your hourly rate. You'll see a return on investment pretty quickly with the time you save using Power Query.

However, the real value of the training comes in when you look at what you can do for your company with that extra time. You can now focus on analyzing the data instead of preparing it. See, Power Query turns your data into information. It allows you to identify new opportunities, make better decisions, and add real value to your organization.

Where do I go to become a Data Master with Power Query?

Ken will be leading this full-day workshop on Wednesday, April 17, 2019 at the NYC Seminar and Conference Center in New York City. But this is a small group session so there are only a limited number of spots available. Register today to secure your chance to receive personal guidance from a world-class Power Query expert. Go to the Excelguru website to view the full course description and register online.

Solving Business Problems – Power Query Does That

This week's blog post on solving business problems with Power Query is a guest post by Alex Jankowski

Does your business or work group have manual tasks that are repeated regularly, such as data re-entry, copy/paste functions, sending the same old email, cross-referencing lists, etc.? We can automate these kinds of activities with a wide variety of tools, such as Excel (including VBA, Power Query and Power Pivot), Access, SharePoint and MS Power BI, as well as with other, more sophisticated software packages.

Solving Business Problems You Didn't Even Know Existed

I have found the following to be common themes that can inhibit identifying and solving business problems:

  1. Organizations are illiterate about their data.
  2. Organizations are allergic to cost.
  3. Many managers lack technical imagination. They can’t even conceive of the problems that the organization’s data could solve, let alone conceptualize potential solutions.
  4. Organizations think that only financial data is worthwhile.
  5. Organizations roll out massive ‘suites’ without a concept about how to get their money’s worth from the licenses. My guess is that on average less than 25% of the capabilities of MS Excel are utilized due to lack of training/imagination, which is not a good ROI.
  6. Organizations think that the IT group has a handle on this, whereas IT thinks that data belongs to the business or prevents anyone from accessing important data (IT acting as a “department of productivity prevention”).

And I’m not even talking about the mission critical data that resides in big ERP systems (including HR, Corporate Finance, Time Records, and Project Financials) or “Big Data” that everyone is looking over their shoulders at.

What about:

  • Detailing a list of technical drawings on a project?
  • Tracking hours spent on a project activity, or the employee vacation schedule against entitlements?
  • Creating a dataset of employee skills and performance reviews?
  • Linking that scheduling software package to a list of real deliverables?

The Basic Win - Owning Your Data

Every business has what can be termed ‘islands of data’ which are often generated and managed manually.

Islands of Data

There are 'islands of data' that exist in every organization

Let’s say that your business splurges to automate and standardize some elements of the work process to be more effective. What are the benefits? Well, there will be a reduction in repetitive costs that offset the application implementation costs. People can then graduate from data makers to data owners (where they spend more time analyzing report data rather than creating the report itself), and begin solving business problems by making smarter, data-driven decisions based on questions like, "Is that it? Was it worth it? Where’s the big payback?"

The BIG payback is in linking the ‘islands of data’ with each other to gain unexpected insights. Don’t believe me? Let's take a look at a simple real-life example.

The Unexpected Win

A few years back, I was working in an engineering firm with a very large project. The Operations Manager (thankfully, a guy with great data imagination) wanted to a way to track piping isometric drawings as they were reviewed by various project leads. The drawings would get lost in the review process, like when the head of electrical left them on his chair when he went away for a month in the summer. So we came up with a solution to identify every isometric in the review process, who had approved it, when it was approved, and where it was going next. We met the application goal and stopped losing the isometrics in the review process.

Sample Isometric Drawing

Sample Isometric Pipe Drawing (from http://www.svlele.com/drawings.htm)

Was that the BIG win? Nope. The big win was when we started matching the list of drawings that had completed the review cycle with the list of drawings issued for manufacturing in the document control system (which would have been a great opportunity for Power Query – I wish we had it then). Guess what? We found a small count of approved drawings which had not been issued to manufacturing.

The Real Cost of Not Doing the Data Work

You're thinking, "So what?" Well, each isometric drawing represents a section of pipe that is fabricated by the manufacturer with flanges, valves, fittings, etc. The fabricated pipe is then sent to the construction site holding yard to wait its turn to be assembled in the pipe rack by the construction team. The impact of the drawing not being issued to the manufacturer is that the pipe section is not on site when it’s time to construct, and nobody recognizes it is missing because the drawing was never issued.

What’s the cost of that?

  • extra cost: Rush to find and issue the missing isometric drawing
  • Extra cost: Construction team has to re-sequence its work to allow for the missing pipe section
  • Extra Cost: Rush fabrication by the pipe manufacturer, possibly resequencing their production schedule and possibly charging overtime rates
  • EXTRA Cost: Rush shipping charges to get the late pipe section to the construction site
  • EXTRA COST: Possible overall delay in the construction schedule
  • BIG EXTRA COST + LAWSUIT: Possible overall delay in the refinery startup schedule

That extra cost could be thousands of times more than the cost of doing the data work, and possibly end up eating all of the project’s margin and more. (If you’re going to be allergic to cost, this is the one to be allergic to). Creating the application for isometric tracking was a win, but matching it to the document control system drawing list was the BIG win and nobody expected it!

Delivering the BIG wins

Let's take a look at some ways at solving business problems in Power Query using the data you already have. What if you:

  • Need to find files, audit folder contents, or document a folder structure on the server? Power Query does that.
  • Need to develop an email filing system for your project? Power Query can list the emails, their contents, and attachments.
  • Need to open server files from an Excel list without navigating through the File Explorer? Power Query can help with that. (Eliminating the practice of people navigating from "My Computer" into the bowels of the server structure for each individual file is one of my personal lifetime goals.)
  • Need to create a templated report about projects, employees, or hours from an ERP system extract? Power Query does that.
  • Need to pull data from SQL for templated operations reports? Power Query does that.
  • Need to read multiple CSV or Excel files into a single data set? Power Query does that (check out some of Ken's other blog posts, like this one on Combining Excel Files).
  • Need to report on the status of drawings in your document control system? Power Query does that.

Once the 'islands of data' are being processed, Power Query does an awesome job of combining the data sets together, especially if all the column names are different and the data formats need to be aligned.

What data problems do you need to solve? How are you currently solving business problems, and are there opportunities for BIG wins in your business? Give us some feedback in the comments!