DISCLAIMER: absolutely subjective point of view, for the official definition check out vocabularies or Wikipedia. And come on, you wouldn’t read an entire article just to get the definition.
Well, we analyse data every day, every hour, every minute. Our brain, using our 5 senses, reads the input, processes it and makes some conclusions. For example, you sleep, the alarm starts to ring, using ears our brain receives the data that something is happening outside and this something is not normal, so you wake up and check if there is any “danger” and if you don’t have any important appointment you pospone the alarm :D.
I see data analysis as 4-step process:
- Define the problem
- Collect the data
- Process the data
- Make conclusions
For example, a lot of people ask me: “How can I become Data Analyst? Can you please help?”. So here we have a problem. We are at step 1. A person wants to become a Data Analyst and doesn’t know how.
Step 2 is to collect data. A person starts to search for requirements to be able to do data analysis on professional level, all “whats”, “whens” and “whys”. The person can use Google to collect those data points, ask others, more experienced professionals in the field, check educational programs or maybe ask a career coach if such a person is present in their company.
Once the data is collected we go to the step 3, we start to process those data and combine with our reality, experiment with different variables and contexts that apply to this exact person’s situation. For example, you work in a company and want to change your specialty. You googled a lot, you checked different educational paths, you talked with your career coach, you have the data and you understand that to become a data analyst you have to learn new skills. Now you have to combine this data with the data that you have. If you work for a company it means that you stay in the office for at least 8 hours a day, you spend 30 minutes to get to the office (doesn’t apply for year 2020 XD), you also already know some tools that are used in data analysis, but you don’t have internet connection in your home and it is difficult for you to study alone etc etc.
You process this information and get to the conclusion that the best for you will be to find a presencial course that is taught for groups in your city.
Now you have a new problem – how to find a presencial Data Analytics course. And the process of data analysis repeats again and again.
Actually the initial problem arose from the data analysis cycle as well: a person realized that it would be awesome to become a data analyst (problem, step 1), checked their knowledge (collected the data, or in this case absence of such, step 2), realized that the person doesn’t have the right knowledge at the moment (processed the data, step 3) and made the conclusion that first the person has to fill that information gap (step 4). The new problem – “How to become a Data Analyst”. All this happens in just seconds, but this is how it works on a larger scale. Exactly the same way. You have a problem, you collect the data, you process it and make conclusions based on that data.
Selection of the data, various biases, uncertainties, paradoxes etc. are specifics that go hand in hand with this process, but it is not a topic of today’s article. And the more data we have, the more diverse data we have, the more tools we know, the more domain knowledge – the better and more rational decisions we can make. The world of data is incredibly complex and simple at the same time, as the world in general is.
Analyze your data wisely and have a great day! Cheers!