Aldous Huxley once said that “facts do not cease to exist because they are ignored,” a quotation that can be illustrated by the data overload of today’s economy. Recent technology has made data exponentially more abundant than it has ever been. In 2010, Eric Schmidt, then CEO of Google, said “Every two days now we create as much information as we did from the dawn of civilization up until 2003.” And that pace is accelerating: Cisco predicts “the amount of data generated in 2019 will be effectively larger than almost the entire history of the internet.” While most companies know they should be capturing data, most don’t even know how to handle what they already have. A study from MIT Sloan found that while 65% of companies reported that they effectively captured data, only 46% knew how to properly deconstruct or analyze it.

Data is our most powerful tool, and the real winners will be the ones who know what to do with it. Today’s most desirable and high-growth companies have built their business models on data analytics.  An Uber job posting says that the company “has been hard at work building a global transportation fabric that spans the globe, and data science lies at the heart of it.” Buzzfeed has an entire data blog, where a post explains that  “[Buzzfeed] employees in every group and at every level are aware that data (and, more broadly, technology) are core to our success.”

Drew Conway's Data Science Venn Diagram
Drew Conway’s Data Science Venn Diagram

Here is an overview of how to extract value from raw data– a process that separates the men from the boys, as illustrated through the analytics of music.

  1. Understand the Question:  What blind spot am I looking to fill, and what decision am I looking to support with evidence? Am I an indie rocker with dwindling concert sales, or a rising country artist looking to maximize on limited resources?
  2. Access Data: Data are facts, figures, and stats. Music data company Next Big Sound tracks the internet presence of hundreds of thousands of artists, from the number of their Twitter followers to how many people stream their mixtape on Soundcloud to how many Pandora stations were created in their name.
  3. Reporting: Effective reporting converts raw data into trustworthy and useful information. Just because you know how many times a specific user streamed Sam Smith’s album doesn’t mean that you have to include that data. This relates back to the first step: understanding the question.
  4. Analytics: Turn the results from your reports into strategic action. The Latin music genre has a Facebook-heavy fan base, so you might advise a Latino musician to build up a Facebook presence. Meanwhile, Trap Queen artist Fetty Wap’s high concert attendance correlates to his vibrant Instagram account. Use data to help musicians make decisions: whether to release music on Soundcloud or Spotify first, how many music videos to shoot, which locations should be on their tour.

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Music is not the only industry that needs data analysis to make decisions. Data analysts are in high demand to help solve problems across healthcare, technology, finance and education industries (to name a few). In a Robert Half survey of 1,400 CIO’s, 53% of respondents whose companies are actively gathering data said they lacked sufficient staff to access and extract insights from it. If you are interested in exploring career opportunities for data analysts, check out this article on salaries for data-oriented roles. A wise man named Justin Bieber recently asked, “What do you mean?” To which Sherlock Holmes said: “Data, data, data! I cannot make bricks without clay!”