Fahim@ualberta.net

Data’s Power and Danger

Data’s Power and Danger

Fahim Moledina optisyn data

Data analysis and the need to be data-driven is disrupting many roles and organizations. Companies are starting to demand more experience and skills in not just understanding data and the business but being able to clean, visualize, evaluate and deploy data for use is becoming common. Many entry-level data science jobs are asking for 3 – 5 years of experience when the role itself is so new that many companies are hiring there first data scientists. About 5 years ago I worked with two individuals who were recently hired as data scientist’s both were very bright had masters degrees and were very adept at analyzing and cleaning data but did not understand the business nor were they data scientists for years so they were in the process of upskilling while they worked. There were clearly high expectations of these individuals to analyze data and come to solutions that would help managers and executives (some type of secret sauce) but the data was not extensive and executives clearly wanted the data to say what they wanted and often pushed for this bias and one of the two individuals usually followed this bias while the other individual who was more experienced decided to leave the company. Data is powerful but often can be weaponized with bias and in this regards it is important to have structure and objectivity when making decisions and using analytics. The other danger now with data-centred roles is impostor syndrome as the demands of organizations are becoming quite vast and the skillsets often are more siloed. Data roles are starting to converge and individuals are upskilling as organizations big and small are looking for assistance in making data-driven decisions. This often means the same individuals are playing multiple roles often being data engineers, scientists, analysts, testing engineers and developers. With the demand for data-driven decisions organizations’ roles will adapt and change from the bottom all the way to the C-Suite with the rise of positions like the Chief Data Officer to often complement the CIO the question now is what roles will adapt and emerge.

 

Data now is very powerful and companies like Google use your data to customize your experience. Automation and intelligence are starting to become commonplace. I actually turned off my data and automation to google and all my social media for a week and was surprised at the convenience I lost. Customized news that was targeted at me was starting to fade out- the biggest issue was google maps two days in a row did not notify me automatically of an accident and I was late to work due to an accident usually google would have automatically detoured me. So the protection of your data and security often comes with tradeoffs and people need to evaluate how much data they are willing to release for convenience. Individuals really need to understand if they really own their data in many cases they give up or agree to something they never read by clicking a box. Now data holders are becoming savvy and storytelling with data is becoming more common coordinated efforts can lead to risks again of bias and misinformation that can influence people of all sorts of things. We now live in an age where bots can help support misinformation as seen when Bolivian President Evo Morales eventually resigned thousands claimed it was not a coup and the hashtag #bolivianohaygolpe had over 17,000 tweets the day after and 5,000 were created the day before and most likely all were bots. In this case, there was coordinated misinformation that many ended up believing. Targeted efforts become even more effective as organizations sell their data quite often. Many marketers will buy data and this is more common than people think. Often when you attend a conference or even a webinar they take your information down, have you asked where this goes? When I worked within a marketing team it was often discussed buying conference lists and contact information of individuals at conferences and this data is commonly sold to many different groups. Digital marketers now collect data that some may even consider intrusive- technology and automation are making data a very valuable commodity a CRM with no or little data has a very different value than a CRM with robust information. More qualified leads can be quickly generated with appropriate data as well as targeted marketing and personalization become a possibility with more data.

With the sale of data ethics in the use of analytics and new technology (AI etc.) is becoming more prevalent as seen with examples like Cambridge Analytica and in spreading what many would say is fake news. Political campaigns are now being driven by data and often this data is contorted and used to influence and convince undecided voters. The question now with all sorts of numbers and data out there what do we believe. Often people now will use the excuse that they are “just doing their job”. Ethics needs to be ingrained in how data is used and it was quite clear in “The Great Hack” the documentary on Netflix shows how data mining and algorithms are really affecting large world decisions. Some of the unethical ways data were used was targeted at impressionable voters. The question now is will data be weaponized to drive world issues and bias? Data is very powerful and what Cambridge Analytica did show is it is dangerous if there is bias and the data is weaponized.

I recently took on learning how to code and learn some programming language. It had been about 5 years or so since I typed a line of code or queried any data in that way. In writing what I have in this post and my previous post I believe upskilling and increasing my knowledge will take significant time as I believe this will truly be lifelong learning. Data is becoming an asset and an opportunity the question now in this journey is who will be left behind.

I’m a big fan currently of Avinash Kaushik his blog is great and he is in charge of a lot of Google’s digital marketing and some great blogs on data strategy at a high level. Check it out here. You can also follow my blog here as well and share it on social if you enjoyed this post.

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