BI-Metric Tools

Authors: Akshaya Jayakumar & Srutimala Deka & Sanskriti Tripathi


In this blog we will first take a look at what the metrics layer is and where it fits into our data stack. Then we will have a brief look at all the available metrics tools and move on to two specific tools - Metriql and Transform.


The comparison chart between the two will aid in selecting the best tool for any particular use case.


What is the Metrics Layer

Metrics are an essential part of analytics. These are the numbers that indicate the overall performance of a business or an organization.


In the traditional (and widely used) scenario, any tool which makes use of metrics, say a visualization tool or a CRM software, would have its own metrics definition. These are not portable to other tools which might use the same set of metrics in a different way.


So there comes a point when the metrics or KPIs have evolved over time. The numerous tools using that metrics would either fail to remain updated or it may not be consistent across all the consumption tools. This can heavily affect large businesses when decisions are made swiftly after one look at the numbers.



That’s where the metrics layer comes in!


It is a single layer which sits between the consumption layer and the data source. This layer is nothing more than a metrics store where metrics are defined, managed and cataloged by a selective group of data experts.



A data driven organization would employ their data engineers, analysts and business experts to collaboratively define the metrics they are most interested in.


When is it time to adopt a metrics layer?


In case the following conditions are met, one may consider introducing a metrics layer in their data stack.

  • The collection of consumption tools is getting larger and mismanaged

  • There are key metrics which are reused in most of the downstream tools

  • Large organizations having a mature data team.

Introduction to some BI-Metrics tools currently in the spotlight

LookML: LookML is a tool from Looker which allows analysts to collaborate, test and document data. It is an enterprise product. LookML’s primary advantage lies in providing a framework for converting every metric request into a query to extract that metric from the database, consistently and accurately.


Airbnb Minerva: Airbnb has come up with its own metric tool that addresses their internal metrics inconsistency problem. It is custom-made for querying customer data uniformly with a user interface and metrics store.


Transform: Transform is a brand new metric tool that provides not only a metric layer but also a UI and APIs for consumption tools to use those metrics. It has an open-source component (MetricFlow) and a 14-day trial to explore the UI and some APIs.


Metriql: Metriql is a metrics store built on top of DBT. This allows users to build, test and document data by leveraging DBT’s features. Metriql is open-source and allows integration with many consumption tools.


Comparison Between Metriql and Transform

Criteria

Description

Metriql

Transform

Comments

Product Offerings

End to End suite

Components for every facet of the tool

No

Yes

Transform has 3 components - the core metric layer, the UI/catalog, APIs for downstream tools

Product Offerings

Querying method

Metrics retrieval approach

Uses subset of ANSI SQL,

Trino's query interface


Uses its own MQL Server and UI for querying; CLI querying is also possible in local system

Product Offerings

Saas offering

Software packages that are available to the end users on the cloud

No

No

Both Metriql and MetricFlow component require on-prem installation

Requirements to use the tool

Memory Requirement

System memory requirements for local installation

64-bit processor,

4GB for Windows 10 and above


2GB - 4 GB

for local installations and Windows 8 and above


Requirements to use the tool

Data Source/ Warehouse Supported

Snowflake

Yes

Yes

Requirements to use the tool

Data Source/ Warehouse Supported

Redshift

Yes

Yes

Requirements to use the tool

Data Source/ Warehouse Supported

Big Query

Yes

Yes

Requirements to use the tool

Data Source/ Warehouse Supported

Postgres

Yes

No

Requirements to use the tool

Data Source/ Warehouse Supported

Presto

Yes

No

Pricing

Offering type

Licensed or Open Source

Open Source

The Metric Layer is Open Source ;

Catalog and API are not.


1.Metriql uses DBT, whose CLI is open source and free to use but DBT Cloud is licensed.

Pricing

License

Apache 2.0

AGPL

Pricing

Licensed Cost/Pricing model

Cost and credits required to use the tool

Metriql is free of cost and incurs cost of DBT DBT CLI is free DBT cloud has 14 days free trial period

Transform UI and APIs comes with 14 day trial with limited functionality

DBT:

Subscription based on pack of users

1.Developer users - > $1000/user/month

2.Operator users $500/10-user/month


Pricing

GUI

Yes; it has dashboard for integrations

Yes; It is the catalog component

Pricing

CLI

Trino's CLI

Local CLI


Criteria

Description

Metriql

Transform

Comments

Downstream Integration

BI Tools


Mode Analytics, Tableau, Thoughtspot, Google Data Studio, Looker and many more

Mode Analytics, Tableau, Python

Downstream Integration

Third Party Tools

Google Sheets, Jetbrains DataGrip, Dbeaver

Google Sheets, Slack, Excel

Compute

In reference to processing power, memory and other resources required for the computation

DBT - Data Warehouse

Source Data Warehouse compute

Metrics Storage

Storing metrics definitions or intermediate tables used for computation

Source Data Warehouse

Source Data Warehouse

Quality Assurance

Automated Testing

Leveraging automation tools to maintain, execute tests, and analyze data

Yes

No

DBT creates automated test cases like not null, unique, etc.

Quality Assurance

Data Model Validation

Yes

Yes

Validation of transform model after configuring yaml file (from CLI)

Data Governance

Data Lineage

Tracking the source and flow of data from sources to consumption

Yes

Yes

Transform UI allows annotation and tracking of metrics when changes are made. Metriql makes use of dbt Cloud to understand the data flow

Data Governance

Documentation

Descriptive information about the data

Yes

Yes

In DTB Great documentation is created for each model with DAG

Data Security

Same as the connected Warehouse security + DTB

Same as the connected Warehouse security


Conclusion
  • Metriql and Transform are two tools with quite similar methods of defining metrics, namely, yaml files.

  • Querying metrics require no new language to be picked up by the user. This is true for both Metriql and Transform.

  • For a team of technical and non technical professionals, Transform’s interface acts as an easy-to-use platform for collaboration.

  • To leverage advantages of DBT, Metriql would be the tool to adopt.


Useful Links
  • Useful blog about the metrics layer : here

  • Find official documentation for Metriql : here

  • Find official documentation for Transform : here

  • Transcripted Podcast with Transform’s CEO : here

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