With the amount of data being tracked in the World growing at an exponential rate, the ability to track, store, and process this data has also increasingly become a tough problem. Businesses, especially, are able to track more data than ever before, but are consistently running into the problem of how to harness the true power of having such mass amounts of data. Actionable insights that lead to profitable business outcomes are waiting to be uncovered, but how do we tap into the rich resource of the buzzword "Big Data"?

This walkthrough won't cover the business problem above. Finding actionable insights involves having domain knowledge of your area and the ability to extract mass amounts of data, by maybe writing some SQL-type code to perform basic exploratory data analysis. While data models like Random Forest or Linear Regression can help tell you which variables are more important than others and how statistically significant they are, models are sometimes there to just help validate your findings. Exploratory data analysis is powerful and can tell a story all on its own.

Once you've got your Key Performance Indicators (KPI) from your exploratory data analysis and modeling, you'll want to track how they're doing, right? In its simplest example form of tracking, if you launch a campaign online to drive more visitors to your website, you'll want to see if the number of visitors to your website is going up or down. What better way to do that than to have an automated dashboard? It sounds quite simple, but a lot of backend work needs to be completed. Being able to architect a database, write code to extract data and manipulate it into a final form, and then create powerful visualizations is no easy task, but that's what this guide will show you how to do.

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