2024: Week 24 - Solution



Solution by Tom Prowse and you can download the workflow here. 



Step 1 - Weekly Salary

First we want to input the Tenures & Salaries table and then calculate a single row for each week when a salary will be paid. Currently, the salaries are at a yearly total so therefore we first need to calculate this on a weekly basis: 

Salary 
[Salary]/52

Now we have the weekly total, we can start to create a row for each of the different weeks. For this we can use the 'New Rows' step but first we need to create an end date for our range. 

For this we can make sure that the End date is a Date field, and then replace the last date '17/06/2024' with the end date in the requirements '12/06/2024'.

We can then create the new rows step where we create a row between the start and end date for each week: 



Step 2 - Output 1

We are now ready to output our first table. For this we need to create a total salary per week so we can create an aggregation step and group by Week then Sum the Salary field. 


Within the aggregation you can set the level that you want to aggregate the date by, in our case we want to select the Week Start level: 



We can then round the salary to 2 decimal places and rename the field to Salary Payments: 

Salary Payments 
ROUND([Salary],2)


Then our final table for the first output should look like this: 




Step 3 - Output 2

We can now return to the 'New Rows' step and create a new branch off of here using another aggregation step. This time we want to aggregate by the Year and sum the Salary. Again we want to select the level in the group by field: 


We can then round the salary and rename the Week field to Year.

Salary 
ROUND([Salary],2)



Next we can input and combine the Total Expenses table by using an inner join on the Year field from both tables: 



Finally we can calculate the % spent of manager salaries by dividing the salary by the expenses: 

% Spent on Manager Salaries
ROUND([Salary]/[Expenses]*100,1)

We can then remove any fields that we no longer need and are ready to output the table: 


You can view the outputs here.

After you finish the challenge make sure to fill in the participation tracker, then share your solution on Twitter using #PreppinData and tagging @Datajedininja, @JennyMartinDS14 & @TomProwse1

You can also post your solution on the Tableau Forum where we have a Preppin' Data community page. Post your solutions and ask questions if you need any help! 

Popular posts from this blog

2024: Week 1 - Prep Air's Flow Card

Image
Created by: Carl Allchin Welcome to a New Year of Preppin' Data challenges. For anyone new to the challenges then let us give you an overview how the weekly challenge works.  Each Wednesday the Preppin' crew (Jenny, myself or a guest contributor) drop a data set(s) that requires some reshaping and/or cleaning to get it ready for analysis.  You can use any tool or language you want to do the reshaping (we build the challenges in Tableau Prep but love seeing different tools being learnt / tried). Share your solution on LinkedIn, Twitter/X, GitHub or the Tableau Forums Fill out our tracker so you can monitor your progress and involvement The following Tuesday we will post a written solution in Tableau Prep (thanks Tom) and a video walkthrough too (thanks Jenny) As with each January for the last few years, we'll set a number of challenges aimed at beginners. This is a great way to learn a number of fundamental data preparation skills or a chance to learn a new tool — New Year...
Read more

2023: Week 1 The Data Source Bank

Image
 Created by: Carl Allchin Welcome to a New Year of Preppin' Data. These are weekly exercises to help you learn and develop data preparation skills. We publish the challenges on a Wednesday and share a solution the following Tuesday. You can take the challenges whenever you want and we love to see your solutions. With data preparation, there is never just one way to complete the tasks so sharing your solutions will help others learn too. Share on Twitter, LinkedIn, the Tableau Forums or wherever you want to too. Tag Jenny Martin, Tom Prowse or myself or just use the #PreppinData to share your solutions.  The challenges are designed for learning Tableau Prep but we have a broad community who complete the challenges in R, Python, SQL, DBT, EasyMorph and many other tools. We love seeing people learn new tools so feel free to use whatever tools you want to complete the challenges.  A New Year means we start afresh so January's challenges will be focused on beginners. We will u...
Read more

How to...Handle Free Text

Image
Free isn't always a good thing. In data, Free text is the example to state when proving that statements correct. However, lots of benefit can be gained from understanding data that has been entered in Free Text fields. What do we mean by Free Text? Free Text is the string based data that comes from allowing people to type answers in to systems and forms. The resulting data is normally stored within one column, with one answer per cell. As Free Text means the answer could be anything, this is what you get - absolutely anything. From expletives to slang, the words you will find in the data may be a challenge to interpret but the text is the closest way to collect the voice of your customer / employee. The Free Text field is likely to contain long, rambling sentences that can simply be analysed. If you count these fields, you are likely to have one of each entry each. Therefore, simply counting the entries will not provide anything meaningful to your analysis. The value is in ...
Read more