Invest in the Discovery Phase of Analytics

October 4, 2016 Jack Vawdrey

Man hiking with mountains in the background

a man in hiking gear looking out over some mountainsIn order to foster the innovative use of Big Data, data architects need to discover new ways to gather, organize and structure their data.

They need discovery analytics.

Discovery Analytics and Business Intelligence

Discovery analytics is a division of digital analytics that uses machine learning and visual analytics to evaluate data not associated with predefined metrics. Discovery tools reorganize data and identify patterns and trends within Big Data, thus providing additional, actionable insight for an organization.

These tools can perform these functions without the structural constraints associated with data warehousing and traditional business intelligence analytics.

In business intelligence analytics, collected data is mapped back to predefined metrics that are based on pre-established business objectives—this type of analytics fosters retrospective verification of performance.

While traditional business intelligence analytics are valuable and influence decision-making, the concrete data structures do not present an opportunity to quickly analyze datasets in new and innovative ways.

The Value of Discovery Analytics

An article from Teradata Magazine effectively describes the value that discovery analytics can provide to your organization:

“Discovery approaches the data in an iterative process of ‘explore, discover, verify and operationalize.’ This method uncovers new insights and then builds and operationalizes new analytic models that provide value back to the business.”

Scott Cannon from Axis41, a full-service digital marketing agency, recently commented on the importance of discovery analytics to cultivate an analytics foundation and avoid the common pitfall of starting over:

“We’ve noticed a trend in companies re-implementing their analytics solution because they don’t trust the data. This lack of trust is the result of incomplete planning. Reliable data can only be cultivated once a foundation is built on research into current technologies, code version, and compatibility of third-party platforms.”

In the upcoming Analytics Summit, to be hosted by ObservePoint on November 17, 2016, Danielle Ackles and Scott Cannon of Axis41 will be presenting “Why You Need to Invest in the Discovery Phase of Analytics,” a discussion on the value that discovery analytics can provide to your organization.

To hear more about the impact of discovery analytics, along with actionable best practices from experienced thought leaders, reserve your seat at the 2016 Analytics Summit.

About the Author

Jack Vawdrey

A former student and present enthusiast of the humanities, Jack Vawdrey uses his love of language to explore the role of marketing and analytics technology in business. Jack joined the ObservePoint marketing team in August 2016 and serves as Managing Editor. Adamant about automation, Jack writes to educate the analytics and marketing community about the role of tag auditing and data governance in the enterprise.

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