Data is the new Bacon
Dutch Version published as LinkedIn Article and on my website DataBrouwers.
It is well known that you can no longer ignore data these days. When I ask Google what exactly it is, I see the following:
According to Google, it is therefore one of the following:
- Oil🛢
- Gold 🥇
- Currency 💸
- Bacon 🥓
- Future 🔮
And if I had to pick one, it might as well be bacon!
Conclusion: we have to do something with this.
The first thought that often comes to people is: ‘I (also) have to do something with Data Science!’ This makes sense, because Data Science has exploded in popularity over the past ten years:
Unfortunately this is not the case with the popularity of bacon, still going strong:
Data Science it is!
But Data Science is, you would not expect it, a science. So first check for yourself if you are ready. Were you ready for uni when you were four, or did your parents think it would be wiser to start with primary education first? With the exception of exceptions, it is often pleasant to roll into secondary school afterwards and then, if you still feel like and have a talent for science: the university.
This is also the case with the steps you have to take to get value from your data. If you want to start immediately with the highest attainable goal, you will have a hard time.
OK, so first to the ‘primary school’: Reporting?
After all, how are you going to predict if you don’t even know what actually happened? The first step is therefore always to have your reporting in order:
- Which KPIs are important?
- How have the values changed over time?
- Do I measure the things I would like to know or are these insights unknown?
- Which months is bacon popular as a search term?
- In which country was bacon most popular in 2019?
We have seen in recent years that the peak of popularity of bacon falls in December. It also appears that last year not the United States but New Zealand came out on top. Why this is so, however, falls in the following phase:
High School: Analysis?
Once you have laid the foundation, it is time for the next step: diagnosing your report:
- Why did this KPI go up or down?
- Do I see the effect of my Sales campaign in a specific region?
- Is there actually a significant seasonal effect?
According to an online test for seasonality there is ‘very strong evidence’ to reject the null hypothesis, which is to say, there is likely to be a seasonal effect.
- Can abnormal peaks be explained by actor Kevin Bacon?
Some deviating peaks, such as in September 2012 or March 2014, can be partly explained by the higher popularity of actor Kevin Bacon. Perhaps this is worth figuring out and this could also be determined with statistics. There is no need for fancy Data Science.
Finding anomalies (Anomaly Detection) and explaining them are typical topics that you can apply at a later stage to determine in real time whether peculiarities occur:
University: Data Science!
If you have your reporting and analyses in order, you can take steps in the world of Data Science. That this is not so simple is shown by the ‘Image Recognition’ of Data Science giant Google when it tries to guess my feature image:
In addition, it is important that once you are involved in Data Science, you do not abandon your previous steps, reporting and analysis. After all, how do you succeed in calculus if you let go of the basic principles of arithmetics and mathematics. In addition to being a good basis for further research, good reliable reports and analyzes remain vital to keep an eye on the fortunes of your company.
We will talk about how you can reduce manual input or automate decisions with Data Science later, because bacon is here to stay.
But are you not sure exactly which school or class you are in, do you need homework guidance or are you orienting yourself at the different universities that exist? Feel free to leave a message in the comments, send me a DM or add me on LinkedIn.
Most of all, do not forget:
Data is the new bacon — Google’s Algorithm
Bacon is good for me — King Curtis
