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Kyubit Business Intelligence · MySQL

Turn MySQL application data into business intelligence

Give sales and operations teams a clearer view of the data behind your applications, with self-service reports and interactive dashboards.

Connect Kyubit natively to MySQL and organize transactional data into a semantic model. Define the business meaning once, then let users explore sales, products, customers and time through their browsers.

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Kyubit dashboard showing sales trends, KPIs and product performance
Kyubit interface example using sample data.

Answer the questions behind the orders

Which products drive sales?

Model sales amounts and quantities at the order-line level, then group them by product and category. Use the same definitions in detailed analysis and the management dashboard.

Where is demand changing?

Compare periods using a configured time dimension, then inspect regions or customer groups. Separate a change in sales volume from changes in the mix of products sold.

What needs operational attention?

Use available status, location and date fields to build views of orders or fulfillment. Define the status rules in the model's source preparation so everyone reads the same business meaning.

These are example reporting scenarios. The measures available in your model depend on the MySQL records and business rules you supply.

Turn transactional MySQL tables into reusable metrics

Application tables are designed to record activity. A reporting model needs a clear grain: for example, one row per order line. Start there, then link product and customer descriptions through the appropriate keys.

  • Choose numeric measures such as line amount, quantity and cost.
  • Map dimensions such as category, customer group and sales territory.
  • Use a suitable date column for a time dimension and hierarchy.
  • Retain transaction references as details when they are needed for investigation.

Check totals at the correct level. Joining order headers to line items can repeat shipping charges or other header totals. Validate those relationships before publishing a revenue or margin measure.

Kyubit visual relationship between a customer key and a fact-table foreign key
Kyubit interface example using sample data.

See the visual model designer guide for the modeling workflow.

Connect MySQL with the reporting workload in mind

Create a native MySQL data source using the endpoint, database and credentials appropriate to your environment. Confirm access to the required tables and inspect representative values before processing.

Use a purposeful reporting dataset

Start with a manageable date range and the fields the first report needs. Where application logic requires preparation, use appropriate reporting views or source queries and validate the results rather than reproducing assumptions in every chart.

Keep data formats consistent

Check date values, numeric precision and category labels in the selected source columns. Agree how returns, cancelled orders, taxes and currencies should appear in analytics. The model should reflect those choices explicitly.

Let the first answer lead to the next question

Kyubit grid analysis comparing sales, costs and customer-related dimensions
Kyubit interface example using sample data.

A dashboard can show the monthly result. The analysis grid lets a user investigate it. Add a category, filter a territory, or drill down through the model's hierarchy without preparing another SQL statement.

Save a useful view as a report. Build charts and KPI cards from the same model so management summaries and detailed analysis share the same metric definitions.

With an appropriate time dimension, use relative periods and comparisons to review changing performance. Explore self-service analytics or see the dashboard features.

Refresh for new orders and changing order status

Order data often changes after it first arrives. New transactions and updates to existing transactions need different consideration in your refresh design.

A practical starting point for an order-reporting model.
Source behavior Processing consideration
New orders are appended Evaluate incremental processing for new records.
Recent orders are corrected or refunded Use an appropriate partial refresh window for changed data.
Older history is restated Plan a full rebuild or another supported refresh covering that history.

Kyubit provides full, partial and incremental processing with scheduling. Validate the configured behavior against actual MySQL changes; an append-only update does not automatically capture every edit or deletion.

Kyubit trend chart comparing the selected sales period with a previous period
Kyubit interface example using sample data.

Publish MySQL reporting on your own infrastructure

Deploy Kyubit on Windows/IIS and provide the required Microsoft SQL Server internal databases. MySQL remains your source database and can stay on its existing host when the Kyubit server can reach it.

Browser access for the team

Configure application permissions for the models, reports and dashboards people need. Business users work in Kyubit rather than connecting a SQL editor to your application database.

A repeatable reporting routine

Schedule processing before the reporting deadline, then set up report delivery. Review recipients and execution settings when reports are distributed outside the application.

For MariaDB deployments, use the dedicated MariaDB BI page to plan and test that source connection.

Frequently asked questions about MySQL BI

Can Kyubit connect directly to MySQL?

Yes. Kyubit includes native MySQL connectivity. Configure and test the connection, then build a semantic model from the required relational data.

Can I create an e-commerce dashboard from MySQL?

Yes, when the required order, product, customer and date data is available. Define measures and relationships for your schema; Kyubit does not automatically infer every application's revenue or order-status rules.

Do business users need to know SQL?

No SQL is required for routine visual analysis of a prepared semantic model. Someone with knowledge of the source data should configure and validate that model.

How do I include refunds and corrected orders?

Choose processing that refreshes the affected data, such as an appropriate partial window or full rebuild. Do not rely solely on importing new rows when previously imported records can change.

Does Kyubit run on the MySQL server?

Kyubit runs on Windows/IIS with Microsoft SQL Server for internal databases. It can connect to a separate MySQL server; the source does not have to share the application host.

Try Kyubit with your MySQL data

Take a representative set of MySQL orders, define the metrics your team uses, and turn them into a report and dashboard.

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