A few weeks ago I helped to organise a Data Plus Women London meetup. It was a great opportunity to get involved and get to know many interesting people from the community.
- Two Interesting topics were presented by speakers from The Information Lab and Interworks EU
- The event turnaround was great, and it was nice to see so many women in one place passionate about Data and Tableau
- Technical issues were not a problem but an opportunity to leave a formal meeting room and get more comfy
- Wine, snacks, pizza and an informal setup seemed to smooth all organisational hiccups and helped to alleviate the socialising part
Emily is kicking off the evening
The evening started with Mavis Liu from Interworks EU who took control of her own online data with Monzo API.
At first, Mavis reminded us that every day we create 2,500,000,000,000,000,000 (2.5 quintillions) bytes of data, which means that there is so much data available for our analysis that not many of us use. She also discussed the aspect of accessing our own data through various Web Data Connectors, which later on sparked a lively discussion about data security and privacy.
Mavis provided a great introduction to APIs and then shared her analysis and visualisation of her own spend data from the Monzo API, a powerful digital banking platform that gives users more control of their spend. We were also lucky that Mavis kindly agreed to demo her API work for everyone interested in the details at the end of the event.
Interesting fact: 90% of the world’s data has been created in the last 2 years alone!
The second speaker was Naledi Hollbruegge, who is a consulting analyst at The Information Lab with a master’s degree in social and cultural psychology which helps her to effectively communicate data and analysis to other people.
Naledi talked about two cognitive biases that every analyst should know about. First Naledi explained that cognitive bias refers to the tendency to draw an incorrect conclusion in certain circumstances, and then talked about two biases that are the most relevant to analysts.
The availability heuristic is a mental shortcut people use to solve a problem. We assume that the examples which come to mind easily are also the most important or prevalent things. This can lead us to overestimate the probability and likelihood of these events.
Confirmation bias refers to our tendency to search and favour information that confirms our beliefs while ignoring or devaluing information that contradicts it. This might lead to creating a skewed analysis.
In many cases simply being aware of a bias means that we can better reflect on a situation, be informed on how others might interpret our analysis.
Interesting fact: you are more likely to evaluate the information in this presentation as trustworthy because it includes pictures of brains.
The next Data + Women London event is already confirmed and will take place on the 22nd of June, with a deep dive into predictive analytics with Benedetta Tagliaferri. Register for the event here. Get in touch, tweet to @datawomenldn