When we started this blog some three years ago, data science was widely seen as a mere buzzword. The interest in the concept seems to be here to stay – and grow steadily. Google Trends shows how the interest in the search term Data Science has developed in the last three years:
Data Science is here to stay
We think that Data Science is more than just a fancy term for statistics and agree with the popular blog KDnuggets: Data science is about creating value through data and supporting digital transformation of other processes in a company such as marketing, customer service, production etc. We believe that the positive impact of advanced analytical methods is something that can be generated across industries and is not limited to the corporate sector. Earlier this year, we discussed the adoption of advanced analytics by nonprofits. Given the already existing relevance of data science, we asked ourselves what 2020 might bring - and found some interesting hypothesis on the web.
Take everyone onto the Data Science Journey
According to towardsdatascience, some 100 papers on Machine Learning were published in 2019 on a single day. This reflects that Data Science as a whole is here to stay. Hand in hand with increasing presence comes certain differentiation. The mentioned blog sees a trend towards specialization among different roles in data science. On the one hand, there are experts on bringing models into production and providing the necessary infrastructure. On the other hand, there are people involved in investigative work and decision support.
The footprint of Data Science is getting larger as models are becoming an indispensable part of business operations. This implies the ongoing challenge to further increase model performance, the possible need for model retraining or rebuilding as well as continuous levels of support for model stakeholders.
We mentioned before that Data Science is essentially about turning data into value for the respective organization. This value creation is, according to towardsdatascience, not only dependent on the “physical technology” consisting of algorithms and data flows. The “social technology”, i.e. effective lines of related communication and decision-making or executive awareness (or even better, a basic understanding provided by interesting in-house-trainings in Data Science) are at least as important.
People and Tools are needed
Data Science is done by Data Scientists. According to a study by IBM, the demand for Data Scientists will grow by some 28% until 2020 (compared to 2017). Some might go as far as to call Data Scientists the “sexiest job of the 21st century” – like Harvard Business Review did back in 2012. Regardless of any labels, it can be expected that the perceived shortage of expert staff will remain in 2020 both across industries and on a global level. The good news is that further developed self-service tools will gradually improve the ease of data preparation, exploration, visualization and modelling.
Natural Language Processing
Most people think of structured information in rows and columns when they hear the term “data”. In fact, an unbelievable large amount of unstructured data, i.e. texts, speech, sounds and videos are produced every single day. This also applies to different forms of personalized data and general customer communication. A powerful approach to make most of unstructured data is so called Natural Language Processing. It is essentially about classifying texts in categories, sentiments, similarities etc. What happens under the hood is that characters are translated into numbers and further processed by models such as Neural Networks. Breakthroughs in Machine Learning and emerging libraries like Tensorflow have drastically increased the possibility to apply NLP models to unstructured data.
Data Privacy and Security as relevant constraint
There is no data science without data. The “raw material” for analysis and models is often personal data, be it from customers or donors. Particularly in a European context, the public has become more aware and careful regarding the ownership of personal data. The ongoing challenge for any kind of organization involved in data science is to keep highest data security and protection standards, aligned with best practices and being transparent upon customer request. If organizations stick to that, there is no need to become paranoid about data protection at the same time.
What is it that fundraising nonprofits can do or learn about Data Science in 2020?
We think that a classic quote by Mark Twain gives valuable hints into this direction:
The secret of getting ahead is getting started. The secret of getting started is breaking your complex overwhelming tasks into small, managable tasks and starting on the first one.
No matter how far away you see yourself away from applied and sophistiacated Data Science, it definitely will pay off to be even more data driven in 2020 and beyond. As we outlined earlier this year, there still seems to be a competitive edge in the industry for "analytcial NPOs" (see our blog post for facts and figures in this regard if you are interested. Do not hesitate to ask experts or organizations you trust for guidance - also joint systems will be happy to help throughout 2020. :-)
We wish you merry Christmas holidays and a good start into a happy, healthy and successful 2020.
David Weber and Johannes Spiess
4/7/2020 11:56:17 pm
Very good read! Some interesting times ahead.
4/8/2020 11:34:42 pm
Thank you very much, Fabian! Looking forward to keep in touch regarding data science and other interesting topics.
1/8/2023 03:45:50 pm
I have been absent for some time, but now I remember why I used to love this site. Thank you, I will try and check back more often. How frequently you update your web site?
1/9/2023 10:41:51 pm
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2/21/2023 12:10:39 am
Such a Informative post. The Concept has been explained very well, Looking forward for such informative posts. Thanks for sharing this post
2/21/2023 09:38:05 pm
Thanks for sharing such a amazing post with us. Data Science is very interesting subject , The way you present this article is very informative , and Data Science take care by supporting and implementing such a impactful decisions that are made by non - data scientists . We have to create awareness. It can also help to introduce decision makers to the organizations.
2/23/2023 10:38:38 pm
Thanks for sharing such informative blog with visuals it help me to understand the concept very easily
Great post! It's amazing to see how rapidly the field of data science is evolving and how new technologies are being developed to handle the ever-increasing amount of data.
5/27/2023 07:53:50 pm
This technology blog is an excellent resource for anyone looking to stay up to date on the latest tech news. I will be using this blog for my own clients. talk Ten 4 Technology Group for technology information.
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