Turn Info to Insights: Step 3. Build Your Technical Skills
In Step 2, we explored vital non-technical skills for a successful People Analytics career. We learned to consume and translate people data insights, but now, it’s time to get our hands dirty and build our data doer skills. A data doer actively transforms raw people information into actionable insights. That might include gathering, analyzing, managing, interpreting, sharing insights, and many other activities.
There are many ways a data doer might spend their time getting insights and a vast array of technical skills used along the way. We won’t be able to dive deep into the nuts and bolts of every possible technical skill. However, it is the goal of part 3 to point you toward some key areas where you can build your data doer skills to get a strong foundation on which your People Analytics career can be built. This section of the guide seeks to summarize and simplify the sometimes overwhelming amount of skills needed into categories for skill growth so you can more easily navigate this exciting world. Some things should be done in order, for example, learn basic statistics before going on to advanced statistics. Others can be tackled in any order, for example, it’s never a bad time to learn about security and data privacy! This is not a textbook and will not attempt to teach analytics techniques, it also will often need to over-simplify concepts for this same reason – but don’t worry, there are several fabulous resources already out there for that. This guide is intended to help you decide which skills you may want to explore, uncover the ones you already have strengths in, and identify those you may want to develop further. Its goal is to provide you with topics to consider as part of your continuous development and career learning journey. If you are itching to get into more detailed technical how-to materials, you can find additional recommended resources at heatherwhiteman.com/pa-career-guide. But don’t feel limited to those resources, if you can use a search engine, you can find lots of material on all the topics we cover in this guide.
For the sake of simplicity, I’ll break down the vast array of People Analytics technical skills into the following five categories and you will find various sub-categories within each. You can think of these as key People Analytics data doer skills.
1) analytics,
2) data visualization,
3) data management,
4) research methods, and
5) tools & technology.
* Disclaimer.
If you know me, you know I love skill, knowledge, and capability taxonomies. So, I couldn’t put this page out into the world without a disclaimer. Here it is. Disclaimer: The above categorization is not illustrative of the analytics, research, or information management fields (which are integral parts of one another), and it’s not even my personal stance on how a People Analytics skills taxonomy should be laid out. The categories were chosen purely based on the amount of content within each sub-category available in this guide. Its only purpose is to break up an otherwise unwieldy chapter into more manageably sized sections for the reader.