But it also needs to show that you can collect data, clean it, and report your findings in a clear, visual manner. Yes, your portfolio needs to show that you can carry out different types of data analysis. This makes sense when you think about it-after all, our insights are only as good as the quality of our data. In fact, about 80% of all data analytics tasks involve preparing data for analysis. As any experienced data analyst will tell you, the insights we see as consumers are the result of a great deal of work. What should you include in your data analytics portfolio?ĭata analytics is all about finding insights that inform decision-making. Exploratory data analysis project ideas.What should you include in your data analytics portfolio?.We’ll then share nine project ideas that will help you build your portfolio from scratch, focusing on three key areas: Data scraping, exploratory analysis, and data visualization. In this post, we’ll highlight the key elements that your data analytics portfolio should demonstrate. And the good news? Data is everywhere-you just need to know where to find it and what to do with it. The most important thing is to demonstrate your skills, ideally using a dataset that interests you. You might also think that your data projects need to be especially complex or showy, but that’s not the case.
Finding projects for your data analytics portfolio can be tricky, especially when you’re new to the field.
