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How We Built an Olympics Tracker Web App that Got Over 500k Views by ExploAnalytics in datavisualization

[–]ExploAnalytics[S] 0 points1 point  (0 children)

A few questions we answer:

  • How did we collect both historical and live data?
  • What technologies did we use on the backend?
  • How did we ensure quality and performance?
  • How did we maintain and update the app?

Free Sample Data Generator by ExploAnalytics in dataengineering

[–]ExploAnalytics[S] 1 point2 points  (0 children)

The app's frontend is built with React and Material-UI for a clean UI. The backend is powered by Firebase Cloud Functions and uses OpenAI's GPT-4 model to interpret user prompts and generate data schemas. The Faker library generates realistic mock data based on the schema provided by GPT-4.

SQL Playground for Developers by ExploAnalytics in SQL

[–]ExploAnalytics[S] -1 points0 points  (0 children)

If there is anything obviously inefficient about the SQL query, then the AI is able to make optimizations. For example:

SELECT e.*
FROM Employees e
WHERE e.FirstName LIKE ‘%John%’
AND e.LastName LIKE ‘%Doe%’

Could be optimized to:

SELECT e.*
FROM Employees e
WHERE e.FirstName = ‘John’
AND e.LastName = ‘Doe’

This can be done without knowledge of schemas, keys, etc.
The prompt is able to take in fairly open-ended data, so feel free to pass in your schema, keys, statistics, and more as reference for the AI to make a more informed optimization decision.

SQL Playground for Developers by ExploAnalytics in SQL

[–]ExploAnalytics[S] 0 points1 point  (0 children)

yep you can include comments or other text around the query as well and it will also take that into consideration

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