Power BI Analysis Of Quickbooks Data

Rob Collie shows how to use QQube to help with Quickbooks data analysis:

Our financials are the logical first place to start.  And our financials are in the hands of our accounting firm.  Specifically, they are stored in Quickbooks.

This, of course, poses a problem.  Because like ALL accounting and ERP systems, Quickbooks is primarily focused on being a great accounting system.  A system that collects, stores, organizes, and routes data.  Quickbooks is NOT an analytics tool.

And being an analytics (or BI or reporting, whatever you call it) tool is a full-time job.  ANY system whose job it is to collect/organize/route data will NEVER be sufficient for reporting and analysis.  NEVER.  I’m not kidding.  We should never expect different, and that’s not a “knock” on these vendors.  It’s just too many missions for any one company to execute.

This is a nice walkthrough of how you can apply visualization and analytics concepts, especially in a small business scenario.

Visualizing SQL Saturday Data

Tamera Clark analyzes SQL Saturday Nashville data:

Select the funnel from the visualizations (1), select track in the field list (2) and drag track to the values box (3). (Image 5 below) Now we need to customize this visualization.  Select the paint brush to edit. (Image 6 below) I recommend giving each of the tracks a different color. Since Tracks are determined by the organizer the data maybe similar so you might want to use the same colors for more than one data point. You should also update the title Count of Tracks by Track sounds silly. Now we have a lovely display of session distribution by track.

She came up with a nice-looking set of information describing sessions and presenters for SQL Saturday Nashville 2016.  I love seeing this kind of thing and hope it becomes mainstream among SQL Saturday organizers (maybe to the point where some of this is built into the SQL Saturday website).

Fractals In SSMS

Slava Murygin gives us a script to generate fractals:

That is most difficult operation. At first, SSMS can’t show more than 5000 separate objects at the same time. In order to show more we have to construct “MULTIPOLYGON” or “GEOMETRYCOLLECTION”. That only the way to fit more objects into SSMS screen. However it is still limited.
In order to combine triangles in a single object we divide them in buckets (Line 106).
In this example I just making number of buckets approximately equal to a number of objects within each bucket. Making lower number of buckets will increase processing speed, but produce less colors. All objects in one collection will have the same color.
Also, I wrapped the last query in extra CTE to have more flexibility on results formation.

This is a fun post showing some of the power and limitations of geometry types in SQL Server and their display in SSMS.

Making Charts Work

Meagan Longoria shows us a non-working chart and how to make it work:

First, I added some explanatory text for context to help communicate my message. If you don’t know about the Citizen Work Sessions, this chart might be confusing. The note about the shift in spending to public safety came from the FY 2016 – 2021 Citywide Business Plan. I thought it was important context to note as city council members and government officials have hard decisions to make when it comes to the budget.

This is a fantastic post for people without much background in visualization (like me) who are winging it (like me) and probably creating ugly charts (…like me).  And it’s all in Excel, meaning you don’t need to learn new tools to make charts convey useful information.

Fitbit BI

Reza Rad has a three-part series on applying BI tools (specifically, Power BI) to Fitbit.

Part 1:

So for this post we are going to build that dashboard (not all of that obviously, because we don’t have the data required for all of that), but most part of it with Power BI. You will see how easy and powerful is Power BI in this kind of scenarios, and you will see how you can be the BI Developer of Fitbit in a few steps of building this demo.

Part 2:

Unfortunately Power Query or let’s say Power BI doesn’t have a loop structure, and that is because of the functional structure of this language. However there are data structures such as Table and List that can be easily used with each singleton function to work exactly as a loop structure does. Here in this post I will get you through the process of looping into files in a directory and processing them all, and finally combining them into a large big table. You will also learn some Power Query M functions through this process.

Part 3:

Fitbit calculates based on my current weight and age (I assume) how much calories I have to spend each day. I don’t know that calculation, So I create a static measure with the value of 2989 for the amount of calories I have to spend each day. I also create StepsCap measure with 12000 value showing that I have to walk 12000 steps a day, and another one for FloorCap with the value of 10. I created a Calories HighEnd measure with 5000 calories as value (I will die if I burn more than that!). You can create all these measures easily in Data tab.

This is a nice combination of work and play, building an interesting system with a data set interesting to the author and freely available.

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