2020: Week 13


In the Chin & Beard Suds Co IT department we are always looking to support our colleagues in the best way possible. As always, we are looking to improve our service and want to understand how the support department is currently performing. We have collected support ticket information from part of this year and want to answer some questions. A new line of data is created every time the status changes. This creates a sequential Status No, giving us a history of the progress each ticket has made.

Inputs

One file, with the following sheets:

 1. Ticket Information
Ticket Info for Jan, Feb, March

2. Department SLA Agreements (in days)
SLA Agreements

Requirements

  • Input Data - This was updated on 26th Jan (1PM GMT), to remove some duplicate Ticket IDs
  • Clean Ticket ID/Names
  • What is the current ticket status? Are they still open, how long have they been open, and how many business days has that been? 
    • Business days are Monday-Friday, don’t worry about bank holidays! Some of our workers work on the weekends, if a case is closed on the weekend then we roll this back to the Friday. If a case is logged on a weekend, we roll these to the Monday. 
    • Business days are also calculated down to the minute level. Eg, if a case was logged on 1st Jan 2020 00:00:00 then closed on 2nd Jan 2020 12:00:00 then this would be 1.5 days. 
  • Answer the following questions:
    • How many cases are in each status?
    • How many closed tickets have missed their SLA? How many are on track to meet their SLA?
    • What departments have the best SLA achieved %?
      • Closed cases only
      • Higher the percentage, the more cases have been closed under the SLA limit set
      • Rank from highest % to lowest % 

Output

There should be three outputs:

1, How many cases are in each status?

  • 2 Fields
    • Current Status
    • Ticket Count
  • 5 Rows (6 including header)
2, How many closed tickets have missed their SLA? How many are on track to meet their SLA?

  • 2 Fields
    • Metric
    • Total
  • 2 Rows (3 including header)
3, What departments have the best SLA achieved %? (Closed cases only)

  • 3 Fields
    • Department Rank
    • Department
    • Achieved %
  • 5 Rows (6 including header)
Don't forget to fill out the participation tracker and share your solutions using the #PreppinData on Twitter and using our community forum on the Tableau Forums where you can upload your solution for others to learn from! 

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 use dif
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