What is a Citizen Data Scientist
There is a lot of buzz about a new emerging role in the Industry called Citizen Data Scientist, popularized by Gartner a couple of years back. What is it? Does it make even sense to follow the heard and start looking for one? or if anyone is interested then what is the path to becoming a Citizen Data Scientist.
Little background
The vast majority of organizations are going through a process called “datafication” where they are essentially fixing their data governance and data pipeline to get some business value out of it. When I say business value, it simply means to reduce costs and increase revenue. In a process of doing so, they will need a large army of tech-savvy data professionals, who are in scarcity. The primary reason being that real data professionals ( Math/Stats ) have always seen technology as something to make their life easy rather than an essential thing to achieve their objective. That has created a massive skill gap between what industry needs and what we have in our resume.
Massive Skill Gap
I am not going to talk about a skill gap that we don’t have enough Java/Python developers or enough data scientists. The question is beyond that, the skill gap we are talking about is the lack of tech-savvy data professionals or data-savvy Tech professionals. Tech-savvy does not mean who likes to chitchat on Instagram or have celebrity status in LinkedIn where everything whatever he/she says sounds amazing.
We are talking about experienced Statistical modeling professionals with good understanding of software development or experienced software developers with deep understanding of statistical analysis. Unfortunately, this skill gap can’t be just filled with a single shot of Udemy, LinkedIn, Youtube videos or doing Kaggle challenges, this skill requires some experienced wisdom which only comes with experience in doing dirty data jobs.
Now the question is what to do next? Should we sit idle? Of course, not there is a middle way. Citizen Data science approach might have the answer.
Addressing the Gap
Citizen Data Science is a role that brings about Data-driven business culture in the organization. This role is not a replacement for Data Scientist, rather augment the capability of a Data Scientist by supporting the overall Data ecosystem for the organization.
Citizen Data Science won’t replace anyone, but rather it will support the modern fast-moving data pipelines. I would call it a brand new role, which wears multiple hats and comes to rescue when needed to Data Professionals ( Data Scientists, Data Engineer, Data Analytics ).
A data scientist is a person that uses an overall diagnostic analysis and the capability to predict future moves or perspectives. The main aim being the field of analytics and statistics. The citizen data scientist is also a savvy data user, who might not be able to build a model, but should be able to understand nuances of data engineering and should be able to help data professionals needed.
The Citizen role could be picked up by anyone, including a new joiner or existing manager who happen to love the subject and is ready to pull up his/her sleeves and get their hands dirty with data.
We got a Data Problem
People won’t have gone crazy about data if, Facebook and Google didn’t surpass the market cap of many countries combined. Take an example if I add-up market cap of all Banks in Canada they can hardly reach to Facebook market cap, I don’t want to even start talking about Google, you might have to add up all oil companies and banks together.
What these companies have? nothing but Data. That started the gold rush to encash the data on which a vast majority of organizations are sitting for centuries if not decades.
Technological Advancement
“Hey I build an ANN model in 10 minutes”, does this sound familiar? this highlights a few things
- The algorithms which were only on theory papers and now can easily be used in a programmer-friendly library, which makes it easy to adopt for virtually any developer.
- This raises the level of competition and expectation from your models.
What organizations need to do
Does that mean you start teaching python to everyone? You might be surprised that a lot of people correlate Python with Data Science, which is absolutely misleading.
In my opinion, businesses should start investing in their workforce to be data-aware even if it’s your receptionist. Because customer-facing employees deal with your customers, users on a daily basis and teaching them the value of data would go a long way, especially when you are interested in some of the behavioral data, circumstantial data, etc.
A simple example could be, monitoring the wait time in a Bank tellers queue and the probability of selling a new product to the customer when they didn’t come to buy a product would be very crucial and improve bottom line for the bank.
This comes down to the fact that we need to brings data-driven culture, rather than a tool-driven culture that has been predominant for decades when it comes to workforce training. Remember, tools will come and go, but underlying concepts remain the same. For example, you don’t need to teach BI tools to everyone, they can do pretty neat stuff in Microsoft Excel itself, of course, once they graduate from this you can introduce them to more advanced tools.
Definition from the Experts
According to Gartner,
Citizen data science bridges the distance among mainstream self-service records discovery through commercial enterprise users and the advanced analytics techniques of information scientists.
Gartner’s definition puts the term into an important context. In nutshell, it demands an organizational change in terms of how we train our employees and how to define the strategy to service our customers.
How to Become a Citizen Data Scientist
This goes back to the fact that whatever job you are doing in an organization, you need to be aware of what data points you are generating or its passing through you and how you could utilize it to either increase your productivity or reduce cost.
Example: Citizen Data Scientist in a Software development team would analyze the number of defects against the LOC in git commit, and possibly try to find correlation and pain points which could improve the quality of the code.
In general, anyone interested to be Citizen Data Scientist should have the capability to perform the following
- Generate habitual reports
- Create and customize information visualizations
- Analyze information to make business decisions
- Have some knowledge of statistics
- No Python needed ( unless you are aiding someone with data cleaning activity )
Citizen data scientists can complement the efforts of information scientists and analysts and fill in the gaps that occur when enterprise humans should rely upon technical experts to get answers approximately their facts.
Looking for more information please check: https://www.becloudready.com/datascience_training/citizen-data-scientist-course/
