What kind of a data scientist are you? Take the free Data Skills Scoring System Survey atÂ http://pxl.me/awrds3
Companies rely on experts who can make sense of their data. Often referred to as data scientists, these people bring their specific skills to bear in helping extract insight from the data. These skills include such things as Hacking, Math & Statistics and Substantive Expertise. In anÂ interesting study published by O’Reilly,Â Harlan D. Harris,Â Sean Patrick MurphyÂ andÂ Marck VaismanÂ surveyed several hundred practitioners, asking them about their proficiency in 22 different data skills. They found that data skills fell into five broad areas: Business, ML / Big Data, Math / OR, Programming and Statistics.
Complementary Data Skills Required
There are three major tasks involved in analytics projects. First, you need to ask the right questions, requiring deep knowledge of your domain of interest, whether that be for-profit business, non-profits or healthcare organizations. When you know your domain area well, you are better equipped to know what questions to ask to get the most value from your data. Second, you need access to the data to help you answer those questions. These data might be housed in multiple data sources, requiring a data worker with programming skills to access and intelligently integrate data silos. Finally, you need somebody to make sense of the data to answer the questions proposed earlier. This step requires data workers who are more statistically-minded and can apply the right analytics to the data. Answering these questions could beÂ more exploratory or intentional in nature, requiring different types of statistical and mathematical approaches.
Getting value from data is no simple task, often requiring data experts with complementary skills. After all, I know of nobody who possesses all the data skills to successfully tackle data problems. No wonder why data science has been referred to as aÂ team sport.
Data Skills Scoring System (DS3)
We atÂ AnalyticsWeekÂ have developed the Data Skills Scoring System (DS3), a free web-based self-assessment survey that measures proficiency across five broad data science skills: business, technology, math and modeling, programming and statistics. Our hope is that the DS3 canÂ optimize the value of data by improving how data professionals work together. If you are a data professional, the DS3Â can helpÂ you:
- identify yourÂ analytics strengths
- understand where to improve yourÂ analyticsÂ skill set
- identify team members who complement your skills
- capitalize onÂ job postings that match your skill set
While the publicly available DS3 is best suited for individual data professionals, we are customizing the DS3 for enterprises to help them optimize the value of their data science teams. By integrating DS3 scores with other data sources, enterprises will be able to improve how they acquire, retain and manage data professionals.
Find out your data skills score by taking the free Data Skills Scoring System Survey:
We are also conducting research using the DS3 that will advance our understanding of the emerging field of data science.Â Some questions we would like to answer are:
- Do certain data skills cluster together?
- Are some data skills more important than others in determining project success?
- Are data science teams with comprehensive data skills more satisfied with their work than data science teams where some skills are lacking?
Respondents will receive a freeÂ executive summary ofÂ our findings.