Turning Data Into Intelligence

The Guest

Aron Clymer is Founder & CEO of Data Clymer, a next gen data & analytics consulting firm that empowers every client’s success by unlocking the value of data. Aron established and built the Product Intelligence team at Salesforce. Subsequently, Aron headed up the Data team at PopSugar where he democratized data and supported analytics/data science across the company, and he’s here today to talk about turning data into intelligence. 

The Interview

Starting out in high-tech enterprise software, including a stint at the data team behind Salesforce, and ending up working with major league sports teams, the circuitous pathways that led Aron Clymer to his current position as founder of a data analytics consulting firm have been driven by curiosity.

“After my long and winding road in my data journey,” begins Aron. “I realized I had only been exposed to a handful of datasets, and I was curious to see what data other companies and organizations were dealing with, and how I might be able to use my experience to help.”

Aron is big on the concept of data heroes and finding ways to break data out of silos and unify teams across an organization through the proper tools and democratized analytics.

“There’s so many reasons why being a data hero can (and should) relate to staff at any level in a company, and it all starts with curiosity,” says Aron. “Because the ease of access and availability have massively improved in recent years, it’s never been easier to become a data hero. Before the push for the cloud, anyone with a question about their datasets really did need a professional or data engineer to help them find those answers, or even secure an understanding on where and how to look for those answers. Thankfully full-cloud, self-serve data intelligence is available, and if someone really understands the business and product, they can find insights fairly quickly. But it takes a lot of work to get to that point.”

The conversation then pivots to the basic definitions in data, specifically the differentiation between databases and data warehouses. 

“First of all, one thing to know is that most data pros don’t know the difference between databases and warehouses,” explains Aron.

“A data warehouse is meant to take all the data, scan it, and give an answer, meaning its function is specifically designed for analytics. The architecture of warehousing has been around for a long time; the reason the recent fascination and increased functionality behind data clouds are interesting is that the cloud makes logical sense because it's removed the centralization of data.”

When the question of “build or buy” was broached, Aron had some worthwhile reflections to share.

“There is always this thought with data, do we buy a bunch of applications to build the data warehouse, or do we go with the cloud. But really, thinking that a ‘single source of truth’ is the end goal, belies the reality most teams are facing. There will always be a multiplicity of apps and tools that comprise a businesses ability to get and use data. You need to be flexible and scale with the pace of your business.”

The interview goes on to explore how better data management can help all departments, but in particular sales and marketing.

“Getting a really rich picture of a company’s prospects is possible with better data management and access. For me, just like any problem, take the raw data, and let’s model it all into something that makes sense. An approach we’ve been using recently, a modeling approach where we take every single touchpoint across many different data sources, and put it into one single log with a timestamp, stitch it together, and now you have a full view of everything that’s ever happened. That data can then be transformed into something easy to use and understand, and so there are ways a non-technical marketer can ask questions that can really depict valuable insights.”

For stories about how Aron has helped major league baseball organizations break their siloization of data to secure homerun insights, how to measure the ROI of a data team, and how trust in data is the most important thing to secure and for advice on how to get your team aligned, listen to the rest of the show at the links provided above and below.  

The Links

Data Clymer
Aron on LinkedIn  

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