Forget about Data Scientists… Start thinking about Citizen Data Science
Just as you finally managed to wrap your head around Big Data, data science is already a profession at risk of marginalization. Citizen data scientists are set to replace them, and disrupt data analytics as we know it.
Description
Citizen Data Science is all about increasing the accessibility of data analytics to non-data scientists.
Think of it as the WordPress of Big Data.
WordPress allowed anyone to create a website within a few clicks without needing a degree in web development. Citizen Data Science attempts to do the same for data analytics. The goal is to create a platform upon which anyone can extract insights from massive amounts of data.
This technology is motivated by the high failure rate in Big Data projects. 66% of companies claim to obtain little to no benefits from data analytics initiatives. This is not surprising given the high startup cost of an analytics department and the inefficiencies involved in the jobs of data scientists who spend 60% of their time doing janitorial tasks like cleaning and organizing their data.
The development of increasingly elaborate self-service data-preparation tools aims to simplify the tasks of the Data Scientist to the point where any business analysts would be able to become a Citizen Data Scientist.
Application
Citizen data science allows for the decentralization of data based decision making.
The promise is to solve one of the main challenges large organizations have been facing when investing in data analytics: the disconnect between business experts and data experts. Relevant insights are found at the intersection of statistical modeling and contextual application. A Data Scientist is essentially useless without the appropriate business context.
With Citizen Data Science, businesses would be able to empower data driven decision making across their organization by giving business experts an easy to use analytics tool.
According to Gartner, 10% of organizations have adopted some form of self-service data preparation tool, which is estimated to grow to 30% of organizations by 2020. The bulk of new adoption will be from large organizations in mature economies.
Challenges
- Vendors must find the right balance between being simple enough to be teachable and versatile enough to drive meaningful results.
- Citizen Data Science is not an easy solution to implement as it requires a fundamental cultural shift to data driven decision making across an entire organization.
- Decentralizing the access to organizational data increases the risks associated with data compliance, security and privacy.
Current Players
The market for Citizen Data Science tools is highly fragmented. In the last 12 months, many big tech and startups have developed self-service data-preparation tools, but a clear leader has yet to emerge. Notable examples include: Alteryx, Cloudera, Platfora, Looker, SAP Lumira, IBM Watson, and Microsoft Power BI.
This post is a humble attempt to demystify the current state of emerging technologies that show potential to disrupt the marketplace within the next few years. If you found it interesting let me know!
Sources
http://www.computerworld.com/article/3051605/big-data/the-rise-of-the-citizen-data-scientist.html
https://www.gartner.com/doc/reprints?id=1-2YQ7FQZ&ct=160216&st=sb
http://www.computerworld.com/article/3047642/big-data/hottest-job-data-scientists-say-theyre-still-mostly-digital-janitors.html
http://www.cio.com/article/3003538/big-data/study-reveals-that-most-companies-are-failing-at-big-data.html
http://www.gartner.com/newsroom/id/2950317
https://www.crowdflower.com/
