Headless BI: Metric Standardization in Action

Learn how numerous information instruments can entry a headless BI platform, eat the identical metrics, and obtain constant outcomes

Desk of contents:· What is headless BI?
· Setting up the headless BI platform
GoodData.CN CE
GoodData Foreign Data Wrapper
· Consuming a standardized revenue metric
SQL clients
Data science IDEs
BI platforms
React applications
Comparing the results
· Summary

GoodData.CN CE

$ docker-compose up -d
Person: demo@instance.com
Logical Knowledge Mannequin — GoodData.CN
Income metric—GoodData.CN
Order Quantity metric — GoodData.CN (picture by writer)
Income by Area — GoodData.CN

GoodData International Knowledge Wrapper

  • From console utilizing psql --host localhost --port 2543 --user gooddata gooddata123
  • From every other shopper utilizing JDBC string: jdbc:postgresql://localhost:2543/gooddata
Username: gooddata
Password: gooddata123
GoodData.CN server in PostgreSQL
Import semantic mannequin into the pseudo-table

SQL purchasers

Connection kind: PostgreSQL
Host: localhost
Port: 2543
Database: gooddata
Username: gooddata
password: gooddata123
Database connection — DBeaver
choose customers_region, income from demo.compute;
Income by Area — DBeaver

Knowledge science IDEs

$ jupyter pocket book
Income by Area — Jupyter

BI platforms

$ docker run -d -p 12345:3000 --name metabase metabase/metabase
$ docker community create community
$ docker community join community metabase
$ docker community join community gooddata-fdw-container-name
Host: host.docker.inner
Port: 2543
Database identify: gooddata
Username: gooddata
password: gooddata123
Database connection—Metadata
Income by Area — Metadata

React purposes

npx --ignore-existing @gooddata/create-gooddata-react-app --backend tiger my-app
cd my-app
yarn begin
Fixed.js config — React app
yarn refresh-ldm
house.js code for Income by Area desk—React app
Income by Area — React app

Evaluating the outcomes

Standardized Income metric throughout numerous information instruments

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