It's In The Data, So It's True!

Big Data eCourse

Together with Laudius and another teacher I made a Big Data eCourse in Dutch about what Big Data is, how to analyze Big Data and Privacy & Ethics in Big Data research. With the code: GUISELAINE 10 percent discount (Affiliate).

Index

Proven, Because There Is Data

Everyone uses data to clarify or prove something. Often this is done by interpreting the data as it suits me. For example as a writer without taking into account a number of other factors that I do not mention or mention in the margins. Think about this!

Do The Figures Give The Right Picture? 

A good example of this is described by Renée Romkes in her July 2013 blog on the limitation of the collected data and the conclusions attached to it. She rightly points out that the figures on violence against women do not indicate the extent of the violence, but only the number of women who dared to report it.

Only The Number Of Women Who Dared To Report It

Yet I read this number everywhere as THE NUMBER indicating violence against women. 'Every 10 days a woman in The Netherlands dies as a result of abuse by an (ex) partner.' Source: https://www.oneworld.nl/lezen/seks-gender/feminisme/nederland-hat-een-femicide-problem/

Is The Collected Data Correct?

A good example of distorted images is the measurement of new visits in Google Analytics. According to the graph, a large part of the visitors to my website in the month of August 2013 were new visitors (read: Never visited my site before). It would be nice if this was true, but I know that some visitors to my website always disable their cookies. They are therefore always seen by Google as new visitors. So drawing the conclusion based on these figures that my website only attracts new visitors is not a correct conclusion. 

Bias Or Professional Deformation

In addition to collecting the wrong data and collecting data incorrectly, it can also go wrong when interpreting data. I only filter the data I need and I link this data based on conclusions. So there is always bias or professional deformation.

Statistics

Another example from Google Analytics. Based on statistics, it is possible to see on my website which places are clicked a lot. This is very interesting for web stores, for example bol.com. With these statistics I can see what visitors click on the most. By following this data over a longer period, I can make statements. For example, that the products in the top right corner are always clicked. But yes, nowadays many people use VPN or Cognito mode, which causes clouding of the data.

Big Data

A better measurement would be that like Amazon and also bol.com uses to classify the website according to my interests. Which products did I last buy or view that appear at the top. Very annoying if I've bought them before and don't want to buy the same dress again. But when it comes to books in the same genre, I may be tempted to make a purchase if I have money left over. Read bigger sales.

In Addition To Big Data

For webshops and other large customers, customer satisfaction and service is also important. This is measurable by placing a survey that the customer fills out at the end of a purchase or service, but this is a snapshot. This is only mass data and with large companies BIG Data, unless this is linked and aftercare takes place.

New Products & Big Data

But don't forget to hold an interview or focus group every now and then to learn more about my customers. Data alone will never answer the needs of my customers and therefore also my revenue growth, because they are only numbers to which I attach a statement or conclusion. With this I miss the individual explanation of the explanation behind the data.