Guest blog post by Daniel Calvo-Marin
All the people interested in data is always looking or researching for new data to integrate either in their business, academic research, software solution, etc.
There are lots of data sets meaningful for ones and not important for others, but there is one kind of data that every person who is passionate about data will find interesting, personal data.
We’re leaving logs of everything we do even without knowing it. Here is a list of data sets that we’re generating and we can study to know a little more of how we behave:
- Fitness data: if you’re a user of apps like Endomondo, Nike +, Adidas MyCoach,MapMyRun or you wear things like a Jawbone, Misfit, Fitbit or Garmin and a lot more, you have data to study. Steep counter, distance, speed, pace, carbs lost and heart rate are some of the dimensions that you can analyze to get a deep understanding of your exercise and improve on it. In some way you can become your own coach by establishing realistic goals, scheduling exercise sessions in a more efficient way and planning rest days when you need them.
- Personal Schedule: maybe this tool doesn’t sounds as awesome as fit bands or greatest gadgets but it has data that could help you a lot. If you are a person that is a high user of agendas and schedules you can analyze it to even predict your future. Yes I know, it sounds crazy, you are the owner of your future. But how many times you get late to an appointment? If you analyze your schedule maybe you can define a “late index” for every entry in your agenda. Or what about reminders to get in touch with people you care about based on your last dates with them. What about academics, maybe you can adjust a model that can set up the right timing for start studying for the exam based on your last scores and time of studying, so the next time you schedule an exam it automatically will also schedule your study sessions.
- Chats history: depending on the chat service you use, you can export your chat history. First of all, it's fun! Definitely you’re going to find things that you don’t remember and will give you a laugh. After that, you can analyze your data to know how is going your relation with others. Topics, number of messages, number of images and emoticons are some indicators to analyze. Other thing you can do is measure the level of importance you are giving to a person. Are you being absorbed by your job?, this is something that you can get to know through your chat history. What if you could apply sentimental analysis to your conversations? Are they nice conversations or there is someone you should avoid to prevent getting angry or upset. Go ahead and give a try to “Chat analytics”.
- Personal mail: in most of the cases this is a less intense communication channel than chat but it will also let you know better how you behave. Analyze your vacation bookings, orders history in different online stores, blogs, forums, advertising and way more. You have a lot of information here! First of all maybe you can create your own spam detector, those used by the mail services are very good, but for a practice it is a good exercise for analytics. We all are receiving messages that are not considered as important, so go ahead and make your own spam detector. After that you can analyze your preferences in products or vacation places to improve your next choice. You don’t have enough time to read emails that maybe you would like to analyze. For example, make a discount searcher that can find in all your mails promotions that interest you.
This isn’t an exhaustive list. From now on stay with your eyes open so you can discover new sources of personal data that you can analyze to improve your life. I think most of this type of analytics could help a lot in become a more efficient person in all of your activities, but I want to give you an advise, despite all of this information, live every day as you want, don’t feel restricted by your agenda, chat history analytics or vacation planing algorithm, you’re free to choose what you prefer in every moment of your life, this is just a help guide, not the final guide!
Originally posted here.