You Can’t Have Good Data Science Without Good Data
In this five-part series from Dstillery, their AI, Machine Learning and Data Science experts will help marketers and market researchers demystify these emerging trends and offer ideas for taking action.
In our previous chapters, we defined and demystified Artificial Intelligence and machine learning, as well as helped market researchers explore new ways to expand their understanding of consumer behavior. But insights are only impactful when the ingested data is of the utmost quality. AI cannot accurately answer questions based on inaccurate data. A key role of a data scientist is to select and compile the data inputs that best speak to the question at hand and, through the correct choice of algorithms, transform them into actionable insights that a brand can harness for a competitive edge.
A paramount rule underlying this process is that the quality of the output is determined first and foremost by the quality of the input. Good data is essential for actionable and accurate results, and in this chapter we will discuss some of the lessons we’ve learned when processing and analyzing data.