We get asked this question all the time — “What is Data Operations?”

DataOps is extremely powerful concept used by classic enterprise data teams that’s just making its way into Revenue Operations function today.

It’s the missing link to giving RevOps complete control over their data without having to do deal with all the traditional “sales alignment” fun– rep adoption, training, carrot/stick incentives, data cleansing, ETL, pivot tables, dataloader, etc.


And it’s an amplifier that bridges the gap across all your existing sales tool investments and opens the door to a whole new class of automation (data entry, next best action, etc).


It makes things like this possible…


Ultimate Sales Automation
…freeing up 20hrs+ of your reps’ time while creating perfect digital journeys for your customers


Who does data operations?

Traditionally, it was the job of a “Data Engineer” to build data pipelines between various applications and data warehouses, transforming data along the way to make things usable/reportable by downstream systems.

But with the proliferation of no-code tools across the stack (Fivetran, Census, Synari, DBT, Truly), the technical barriers to doing Data Engineering have come down a lot.  RevOps teams can now move/transform data with just basic tools like SQL/Regex.

This means that RevOps teams are best positioned to own data operations inside the revenue org, since they are closest to understanding the processes that generate data and the practical applications for operationalizing it.  And thanks to Truly.co, that’s exactly what’s happening today.


Why is this only just becoming a thing?

The idea behind data ops isn’t new.  Enterprises have been using data operations to power Process Mining and Robotic Process Automation projects for almost a decade (Google the history of UIPath and Celonis)

But these concepts couldn’t be applied to the sales simply because they rely so heavily on data completeness, data accuracy and the interconnectedness of apps.

Here are just a few changes in the sales ecosystem that have made it possible to bridge this gap.

  1. Remote Selling: COVID-19 dramatically accelerated the transition to remote selling and the digitization of all sales activity.
  2. Transcription: over half of the sales job involves speech.  Only in the past couple years has transcription reached a tipping point in accuracy and cost.
  3. AI/ML Technology: AI/ML/NLP techniques have only just matured to the point where we can reliably create structured data from text and understand it well enough to operationalize it.
  4. Interconnectedness of Apps: the rise of cloud IT and the Salesforce ecosystem, allowing us to unify engagement data into single sources of truth.

Interested In Learning More?

If your company is continuing to invest in Revenue ops, we should talk.  Contact us to speak to one of our product consultants today!