Does Your Data Spark Joy?

April 10, 2020

“This sparks joy. This does not spark joy.” We’ve all seen that meme from ‘Tidying Up with Marie Kondo’ Netflix Original Series. In recent years, the titular Japanese cleaning consultant has risen in popularity as a home cleaning guru for teenagers and adults alike. But, while the popular KonMari method has become synonymous with home organisation, it seems it can also be applied to data management.

KonMari Method

Now, in case you’ve been living under an internet rock, the Japanese method described in Marie Kondo’s first book The Life-changing Magic of Tidying Up describes how to declutter objects using 6 guidelines:

  1. Commit Yourself to Tidying Up
  2. Imagine Your Ideal Life
  3. Finish letting go first
  4. Tidy by Category, not location
  5. Follow the right order
  6. Ask Yourself if It Sparks Joy

Data Decluttering?

In general, everything in our lives need decluttering at some point and our data is no exception. In fact, as we have mentioned before, poor data management or neglecting data can often lead to contamination which would, in turn, result in poor analytics and bad decision-making. To prevent this, companies often employ people to manually clean and maintain data.

Unfortunately, data maintenance is much more difficult than it may seem at first glance. After all, data is ever-changing and each individual record needs to be constantly updated. This means that anyone manually maintaining this set of data will be glued to their screens for long periods of time. Obviously, spending 24/7 on maintaining data is not advised and is definitely a business faux pas. So, how should you clean your data.

The real answer is: there is no hard and fast rules. Data cleaning is a mundane but necessary task. Time spent on it can be greatly reduced with modern cloud-based apps that promote automation but it can never be completely written off since issues pertaining to human error still exists within every dataset. As such, the goal is to make data cleaning as little of a hassle as possible. This is where philosophies like the KonMarie method come in.

Does this Data Spark Joy?

Now, looking at the 6 steps, it is easy to see how some of them can help with deciding which records are unnecessary and which require trimming.

The first step, Commit Yourself to Tidying Up obviously means that you need to find time and motivation to clean your data. If you start tidying only one part of your data due to a lack of commitment, there is a high chance you might further degrade the quality of data.

Secondly, Marie Kondo used the term ”Imagine Your Ideal Life” as a way to tell her clients to create a clear goal. This can easily be applied to data cleaning since before starting the process, you have to be aware of what your end goal is. This will help reduce time spent on the process since you will already have an understanding of which records need to be trimmed or moved.

Finish Letting Go First. Throwing away certain items is a huge part of the decluttering process. Similar to house organisation, when cleaning your data, you will find yourself deleting contaminated or out-of-date records. By deleting them first, you ensure that you are working with a healthy dataset.

Tidy by Category, not location is probably the most technical part of the KonMari philosophy since it actually details where clients should start the decluttering process. In her show, Marie Kondo often does this plopping her client’s belongings in front of them and asking them to choose a category of items they want to start thinning out. While data does not take on a physical form, it can also be cleaned out in a similar fashion. This means that you should think of a category of records you want to start cleaning first. By doing this, you ensure that you are editting your data in clusters, making it easier to track which records have been cleaned and which need cleaning.

Finally, we have the ever-memeable “Ask Yourself if it Sparks Joy”. Does the final appearance of your data spark joy? Are you happy with the way that your database looks? Do you think you can effectively derive important business information from it? If the answer to these are yeses, you have done your job successfully!

But, remember try not to be a perfectionist about your data. Afterall, it is almost impossible to completely scrub your data without wasting an exuberant amount of time. The best way to spot data errors is to make sure that your data is constantly used in daily operations and viewed by members of your organization. This is why it is imperative that your organization has a user-friendly application that makes all data accessible for all users.

So, start using VAL’s FREE plan to maintain and store your data. If you think you want to learn more, have a coffee with ThinkVAL to learn more about how you can improve your business with the power of data.

Source Agilence (2019. 28 February) Tidying Up Your Data With The Marie Kondo Method
RingLead (2019. 12 September) Does My Data Spark Joy? 5 Tips to Marie Kondo Your Database

About VAL

VAL, also known as the Value Aggregation Layer, is an all-in-one data collaborative data operations solution that lets you operationalize your day-to-day work and discover actionable insights from your data.

About the author

Nicole is a freelance designer and writer that has written articles for different sectors.