With last year’s numbers simmering throughout the industry, it’s obvious that data science had yet another big year. With solid growth across all markets and the internet of everything nearing realization, there seems to be no signs of an abatement. It is now truer than ever that the rise of data is both permanent and exponential.
Last year saw incremental adoption of data driven decision making across the entire C-suite. Marketing departments begrudgingly welcomed the Chief Marketing Technologist into the fold, as digital attribution and cross device analytics became necessary tools in the battle for digital consumer attention. We saw people analytics reach critical mass amongst first movers, with HR departments at companies like Google, LinkedIn and Walmart making use of predictive people analytics to better attract, select and retain the right candidates. Finally, we saw the birth of the Chief Analytics Officer, effectively ending intra-company confusion about who has ultimate responsibility for analytics within the organization.
Despite these moves toward analytics maturity, companies face significant remaining challenges in the data and analytics space. The primary challenge remains education and training to fill the skills gap. The war for data science talent is hard won, and companies continue to struggle to assemble teams that can move their organization to the top of the analytics value chain.
As companies sprint to formulate both buy and build strategies for data expertise, we are in turn seeing the data science training sector scramble to offer solutions that can meet the unique demands of business.
Here are our 5 predictions for Data Science training in 2015
1. Whilst the university sector will continue to provide the necessary grounding skills in statistics and computer science, the final steps toward full data science expertise will continue to come from MOOCs, self study and hard won industry experience working with 3 Vs datasets
2. There will be continued innovation in delivery methods and learning styles. We will see more interactive browser based trainers like DataCamp and frequent use of competitions like Kaggle to focus learning around an end goal
3. Increased knowledge meritocracy. Companies will care less about your grades and more about the actual data science projects that you’ve worked on
4. Increased offerings of 1-3 month intensive face-to-face trainings like the DataSeer Data Science Bootcamp.
5. A rise in the quality of Data Science courses on Udemy, as courses iteratively improve in response to student ratings. We also predict that we will start to see data science courses tailored to specific industry verticals on Udemy and other MOOC platforms.