# Missing or Inefficient Use of Materialized Views

Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/missing-or-inefficient-use-of-materialized-views

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

# Missing or Inefficient Use of Materialized Views

## Explanation

Inefficiency arises when MVs are either underused or misused.

- When high-cost, repetitive queries are not backed by MVs, workloads consume unnecessary compute resources.

- When MVs exist but are rarely queried, their background refresh and storage costs accumulate without offsetting savings.

Proper evaluation of workload patterns and strategic use of MVs is critical to achieve a net cost benefit.

## Relevant Billing Model

## Detection

- Analyze query history to identify expensive, frequently executed queries that could benefit from materialization.

- Review existing MVs for read activity to detect underutilized or idle materialized views.

- Compare MV refresh costs and storage footprint against active query savings to assess net cost effectiveness.

- Validate whether candidate workloads involve relatively stable datasets appropriate for materialization.

## Remediation

- Create materialized views for high-cost, repetitive queries where refresh costs are low relative to compute savings.

- Decommission materialized views that incur maintenance and storage costs without sufficient query usage.

- Implement periodic reviews of MV usage and refresh behavior as data volumes and access patterns evolve.

- Engage data engineering teams to tune MV designs for optimal cost-benefit balance (e.g., selective columns, filtered subsets).

## Relevant Documentation

[Submit Feedback](https://hub.pointfive.co/inefficiencies/missing-or-inefficient-use-of-materialized-views)

## At a glance

Reference

CER-0026

Cloud provider

Snowflake

Service

Snowflake Materialized Views

Category

[Other](https://www.pointfive.co/efficiency-hub/service-category/other)

Inefficiency type

Inefficient Resource Usage

## Contributed by

- Simar Arora 

### Simar Arora

Value Engineer - FinOps @ Snowflake

[LinkedIn](https://www.linkedin.com/in/simarpreet-arora/)

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Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.