Big Data New Year’s Resolutions

January 6, 2017 John Pestana

By now I’m sure your inbox and LinkedIn feed have been flooded with thousands of blog post titles following the common turn of the year theme of “New Year’s Resolutions.”

Well, here’s another one for you.

You would think that by now the digital voice of Big Data would be a bit hoarse from all the incessant declarations of glad tidings of Big Data joy.

Not so. Big Data is crying out more than ever, and is alive and well. Like the rattle of an auctioneer, we never seem to stop hearing about Big Data.

Probably because Big Data is a big deal. With the decreasing cost of data storage, companies are amassing large amounts of data to analyze. There are so many insights to be garnered, decisions to be made and objectives to be achieved.

Big Data, combined with machine learning and automated validation, will be the determining factor in your company’s success.

If you’re an enterprise-level organization, chances are your company already has some form of Big Data measurement practices. So how can you sharpen the edge on the two-edged sword that is Big Data?

The Four V’s of Big Data

There are four V’s that outline the effective application of Big Data: volume, variety, velocity and veracity. Focusing in on improving your Big Data analytics in each of these areas will help you capitalize on those massive loads of data.


In order for machine learning to accurately detect trends in user behavior, you need a lot of data. Most companies in the US have around 100 terabytes of data stored. And it’s estimated that 2.3 trillion gigabytes of data are created each day. That’s good, because the more data you have to draw a sample from, the more credible your conclusions will be. Here are some suggestions:

  1. Increase your data storage capacity in your marketing tools.
  2. If your website or mobile traffic drastically exceeds your analytics tool’s data limit, consider upgrading the tool.
  3. Establish protocol for CRM accounts to make sure all fields are complete. This is especially valuable for discovering buyer personas.
  4. Take advantage of large amounts of data by analyzing both horizontally and vertically.
    1. Horizontally: How are other customers in this segment behaving?
    2. Vertically: What has been this specific customer’s pattern of behavior over time?


The more you know about your customers, the more you can respond to their needs. From social media to YouTube videos to CRM data to IoT devices, there are myriad sources of structured and unstructured data that you can tap into to expand your vision of your customers. Consider applying the following:

  1. Create an option for users to log in to your site or app with their Google, Facebook or other social media accounts.
  2. Explore additional sources of unstructured data, such as email, video, audio, website comments, images or other records relevant to your industry.
  3. Invest in data mining or text analytics to process your unstructured data.


Velocity refers to the speed of collection and accessibility of the data. Research shows that for a typical Fortune 1000 company a 10% increase in data accessibility will increase net income by $65 million. Consider the following:

  1. Implement a tag management system for asynchronous tag loading.
  2. Use a data visualization tool like Domo to obtain real-time insights from your data.
  3. If you have Adobe Analytics, take advantage of Analysis Workspace for rapid, experimental segmentation.


Even if you have a lot of data, if it’s not correct, it’s worthless and even misleading. Verifying that your data collection processes are working properly is essential to being confident in your data-driven decisions.

  1. Implement a data governance plan, including:
    1. Appointing a data steward.
    2. Scheduling regular meetings to discuss data governance and data quality.
    3. Documenting your data deployment practices
  1. Perform regular audits on your analytics implementation. To avoid lengthy, error-prone manual audits, use ObservePoint’s Data Quality Assurance™ platform for automated validation and monitoring of your analytics and marketing tags.

Leveraging your data to enhance the customer experience and refine your company’s operations is crucial in a customer-centric, digital age. In the end, the way you use Big Data will drastically affect your bottom line.


About the Author

John Pestana

Prior to ObservePoint John Pestana co-founded Omniture, a web analytics software company based in Orem, Utah. John helped grow Omniture from a startup business to a large company with over 1,200 employees throughout the world. Omniture went public in 2006 and then sold to software giant Adobe for $1.8 billion dollars in November of 2009.

LinkedIn More Content by John Pestana
Previous Article
What Is Tag Auditing?
What Is Tag Auditing?

Tag auditing is a step in the right direction towards tag governance, allowing you to verify your web tags ...

Next Article
Better Together: Adobe Analytics and ObservePoint
Better Together: Adobe Analytics and ObservePoint

Maximize the ROI on your Adobe Analytics implementation by performing regular audits using ObservePoint.

Get a Custom Pre-Recorded Audit