Analytics projects universally run into challenges where the data we have is not exactly the data we want. In some cases, those limitations are obvious and easy to work around. Most of the time though, it is difficult to both find and navigate the “bad” elements of the data. Learning how to balance the business problem you are trying to solve with the available data is a key skill as a data practitioner. We will discuss how to find and recognize where your data has flaws as well as how to assess how those flaws will impact your preferred analytics solution. Thinking about how the data came to exist and how it got to you is one of the key tools we will discuss for working through these challenges. Finally, we will address the how and why for automation of data processes, as it is key to developing reliable solutions.
Register here