DataFinOps: More on the menu than data cost governance

BrainBlog for Unravel Data by Jason English

Part 3 in the Demystifying Data Observability Series, by Intellyx for Unravel Data

IT and data executives find themselves in a quandary about deciding how to wrangle an exponentially increasing volume of data to support their business requirements – without breaking an increasingly finite IT budget.

Like an overeager diner at a buffet who’s already loaded their plate with the cheap carbs of potatoes and noodles before they reach the protein-packed entrees, they need to survey all of the data options on the menu before formulating their plans for this trip.

In our previous chapters of this series, we discussed why DataOps needs its own kind of observability, and then how DataOps is a natural evolution of DevOps practices. Now there’s a whole new set of options in the data observability menu to help DataOps teams track the intersection of value and cost.

From ROI to FinOps

Executives can never seem to get their fill of ROI insights from IT projects, so they can measure bottom-line results or increase top-line revenue associated with each budget line item. After all, predictions about ROI can shape the perception of a company for its investors and customers.

Unfortunately, ROI metrics are often discussed at the start of a major technology product or services contract – and then forgotten as soon as the next initiative gets underway.

The discipline of FinOps burst onto the scene over the last few years, as a strategy to address the see-saw problem of balancing the CFO’s budget constraints with the CIO’s technology delivery requirements to best meet the current and future needs of customers and employees.

FinOps focuses on improving technology spending decisions of an enterprise using measurements that go beyond ROI, to assess the value of business outcomes generated through technology investments.

SOME CONSIDERATIONS FREQUENTLY SEEN ON THE FINOPS MENU INCLUDE:

  • Based on customer demand or volatility in our consumption patterns, should we buy capacity on-demand or reserve more cloud capacity?
  • Which FinOps tools should we buy, and what functionality should we build ourselves, to deliver this important new capability?
  • Which cloud cost models are preferred for capital expenditures (capex) projects and operational expenditures (opex)?
  • What is the potential risk and cost of known and unknown usage spikes, and how much should we reasonably invest in analysts and tools for preventative purposes?

As a discipline, FinOps has come a long way, building communities of interest among expert practitioners, product, business, and finance teams as well as solution providers through its own FinOps Foundation and instructional courses on the topic.

Read the entire BrainBlog here.

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Principal Analyst & CMO, Intellyx. Twitter: @bluefug