As a marketer, you probably already realize that to stay competitive, you can't ignore Big Data as a tool for insights and smart decision-making. The trickier issue, however, is how to avoid the big headaches of overly technical implementations.

Fortunately, business analytics and data-visualization software can help you avoid having to double as an engineer to extract value from data. That move toward democratizing data is pushing our field to new heights.

Think of any marketing goal and the key to success likely comes down to data. Whether you're looking to analyze survey responses, track social mentions or campaign revenue, assess buying behavior, or parse geographic variations in brand loyalty, you can't get very far without agile management of huge streams of complex, ever-changing, and often unstructured data from multiple sources.

Some companies have such unique analytics needs on an enterprise scale that they opt for a corps of data scientists, whose complex work to combine databases involves highly specialized engineering skills, break-the-bank salaries, long timelines, and huge capitalization costs.

Most marketing operations, however, can't do that... and frankly don't want to. They are better off using multiple existing data sources—like Google Analytics, account records, Salesforce data, etc.—in a more accessible "data-blending" approach that overlays this varied information into a single, visually coherent and flexible workspace where you can play with the data to reveal trends and insights.

Regardless of your specific approach to marketing analytics, you need to have the right mindset if you want to get the most value from the effort.

Here are a few things to keep in mind.

Reconsidering the Data Scientist

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ABOUT THE AUTHOR
image of Elissa Fink

Elissa Fink is chief marketing officer at Tableau Software.