Analyze Data with Data Studio in Autonomous AI Database

Use Data Analysis in Data Studio to analyze tables and Analytic Views in Oracle Autonomous AI Database. The Data Analysis tool lets you create Analytic Views with multidimensional metadata, create analyses and reports from those Analytic Views, inspect tables, generate SQL reports, and visualize query results through tabular, pivot, chart, and related analysis views.

This topic provides an entry point for understanding when and how to use Data Analysis in Data Studio with Autonomous AI Database. For detailed overview of Data Analysis, related views and tables, and workflows, see the Data Studio Documentation.

When to use Data Analysis

Use Data Analysis when you want a guided, visual way to inspect, model, query, and report on data stored in Autonomous AI Database.

For example, use it to:

• Create Analytic Views on top of fact tables and related dimension tables so users can analyze data through hierarchies, measures, calculated measures, and drill-down navigation.

• Create analyses and reports that collect multiple reports on a single page and provide a visual representation of performance through charts and graphs.

• Analyze tables directly and generate SQL reports from database tables.

• Inspect and validate Analytic Views by analyzing, editing, compiling, viewing DDL, deleting, exporting, or checking data quality for errors.

• Use natural language prompts to generate SQL queries on Analytic Views or tables, instead of manually writing the full SQL query.

• Use AI Explain to translate SQL queries into natural language explanations for SQL-based reports on queries.

• Use vector search to search for text in source data by semantic similarity when the required vector prerequisites are available.

• Analyze Autonomous AI Database data from spreadsheets with Oracle AI Database for Excel or the Oracle AI Database add-on for Google Sheets, when those add-ins are installed and the required roles are granted.

Use SQL Worksheet, Oracle Analytics Cloud, Microsoft Power BI, Tableau, or other BI tools when you need a custom SQL-only workflow, enterprise dashboard, or external BI consumption instead of the built-in Data Studio analysis workflow. See Analyze Data with Autonomous AI Database for details.

How Data Analysis works with Autonomous AI Database

Data Analysis runs from Database Actions for Autonomous AI Database. Database Actions is bundled with each Autonomous AI Database instance and provides development tools, data tools, administration, monitoring, and download features. The Data Studio feature area includes tools such as Data Load, Catalog, Data Insights, Data Transforms, and Data Analysis. See Connect with Built-In Oracle Database Actions for more details.

The Data Analysis home page contains three main areas:

Area	Use it to
Analyses	View, edit, rename, or delete analyses. An analysis can contain multiple reports created from Analytic Views.
Analytic Views	Create, analyze, validate, export, edit, compile, show DDL, or delete Analytic Views.
Tables	Analyze tables and generate SQL reports from table data.

For non-ADMIN users, Data Studio tools, including Data Analysis, require the DWROLE database role. If the Data Analysis card is not visible, the database user may be missing this role.

Before you begin

Before using Data Analysis, verify the following:

• You can access Database Actions for your Autonomous AI Database. Database Actions access is schema-based, and the ADMIN user can enable access for other database users.

  Your database user has the required role. Data Studio tools, including Data Analysis, require DWROLE for non-ADMIN users.

• To use Natural Language Query or other AI-assisted features, configure an AI profile in Data Studio Settings. Data Studio Settings lets you select an AI profile that controls how natural language prompts are translated into SQL statements. See Data Studio Settings for details.

• To use Natural Language Query, you need access to a supported AI service account and access to the DBMS_CLOUD_AI package. See Run Natural Language Query in the Data Analysis Tool for details.

• To use Vector Search in Data Analysis, verify the database, ORDS, source data, AI profile, credential, and package prerequisites described in Vector Search in the Data Analysis Tool.

• To use spreadsheet add-ins, review the add-in requirements. Oracle AI Database for Excel requires the ADPUSER role for the download card, and the Google Sheets add-on requires Web Access and roles including CONNECT, DWROLE, RESOURCE, and ADPUSER. See Oracle AI Database for Excel for more details.

Open Data Analysis

To open Data Analysis:

1. Open Database Actions for your Autonomous AI Database.
2. Select the Data Studio tab.
3. Select Data Analysis.
4. Use the Data Analysis home page to work with Analyses, Analytic Views, or Tables.
5. Select an existing object, or use Create to create an analysis or Analytic View.

What you can do in Data Analysis

• Create and manage analytic views:
  • Create Analytic Views over fact tables, generate hierarchies and measures, add hierarchy sources, manage measures, and define calculated measures.
  • Analyze, check data quality, export, edit, compile, show DDL, or delete Analytic Views from the Data Analysis home page.
  • Enable options such as Autonomous Aggregate Cache, Analytic View Transparency Views, and Analytic View Base Table Query Transformation when creating an Analytic View.

  See The Data Analysis Tool for more details.

• Create analyses: Build analyses that contain one or more reports from different Analytic Views and save the analysis for later review. See The Data Analysis Tool for more details.

• Create reports: Drag and drop hierarchy levels and measures into rows, columns, and value areas so Data Analysis can generate the underlying query and display the results. See Creating Reports for more details.

• Format numeric output: Format numeric columns as number, currency, or percentage, and configure options such as precision, thousands separators, abbreviation, and aggregation. See Format Numeric Columns in the Data Analysis Tool.

• Create calculated measures: Use calculation templates for common business intelligence calculations, including cumulative aggregates, prior and future period, period to date, parallel period, moving aggregates, share, and rank. See Using Calculation Templates.

• Generate SQL from natural language: Use Natural Language Query to generate SQL on Analytic Views or tables and view the result in query, chart, tabular, or pivot modes. See Run Natural Language Query in the Data Analysis Tool.

• Explain SQL in natural language: Use AI Explain to generate a natural-language explanation for a SQL query in a SQL-based report. See Generate Natural Language explanation from SQL Query using AI Explain for more details.

• Run vector search: Use Oracle AI Vector Search capabilities in Data Analysis to find data similar to search text in a selected source column. See Vector Search in the Data Analysis Tool.

• Use spreadsheet analysis tools: Use Oracle AI Database for Excel or Oracle AI Database add-on for Google Sheets to query Autonomous AI Database tables or Analytic Views from spreadsheets. See Access the Spreadsheet Add-in by OCI IAM Domains.