Measuring a Snowflake Modernization: Five Outcomes to Track
Almost every data modernization business case promises the same things: lower cost, faster delivery, one version of the truth, room to grow. A year later, few teams can show those results with numbers. The reason is usually simple. Nobody recorded the "before."
Here are five outcomes worth measuring on a move to Snowflake, what to baseline for each, and what we measured at Petmate.
The five outcomes
Outcome | What to measure | Baseline before migrating |
Legacy cost retired | License, capacity or consumption units on the platforms being replaced | Last 3 to 6 months of invoices and usage reports |
Delivery speed | Elapsed time per migration phase; share of development work that is automated or repeatable | Estimate for the same scope delivered by hand |
Consolidation | Source tables and systems brought into one governed layer | Count of systems and copies people pull reports from today |
Business reach | Functions and users working from the new layer | Who relies on which legacy reports today |
Speed to insight | Query and report run times; report turnaround; analyst hours on manual prep | Timings of the 10 to 20 most-used reports and extracts |
Why Snowflake makes these easier to prove
On many legacy stacks, the "after" numbers are as hard to collect as the "before." Snowflake records much of the evidence for you:
Compute cost by warehouse. The WAREHOUSE_METERING_HISTORY view returns hourly credit usage for each warehouse for the last 365 days. Give transformation, BI and data-science workloads their own warehouses, and cost per workload follows.
Performance per query. QUERY_HISTORY records elapsed and execution time for each query. Use it to compare report run times against your legacy baseline.
Guardrails on spend. Resource monitors track warehouse credit usage and can send alerts or suspend warehouses at the thresholds you set.
That turns "the new platform is faster and cheaper" into a query anyone can rerun.
Three habits that keep the numbers honest
Measure the scope you actually moved. The percent automation figure covers applicable migration and integration activities, not the whole project. Precise claims hold up. Inflated ones get challenged.
Count cost in both places. Legacy savings mean little if new spend rises faster. Track retired license and consumption costs next to Snowflake credits.
Re-measure after each phase. Modernization is a program, not a single cutover. Each phase should move at least one of the five numbers.
Building the business case for your own move to Snowflake? Talk to Pingahla about setting the baseline and measuring what changes.
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