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Data Overview

Octigen's data integration system allows you to connect your own data sources to presentations, enabling dynamic, data-driven slides that update based on configurable parameters. It is intended as a simple integrated data warehouse & analytics tool. For more advanced purposes, contact us at for an integration with commercial data lakes & analytics, such as Snowflake, Microsoft Fabric, Databricks or Denodo, or even your company-internal data middlewares.

What is Data Integration?​

Data integration in Octigen means:

  • Your data files (Excel, CSV) stored and organized in collections
  • Parameter-based resolution - data files identified by values like dates, portfolio IDs, versions
  • Automatic population - charts and tables filled with your actual data
  • Validation before generation - ensure all required data exists before creating slides
  • Transformations - chain steps to filter, sort, combine, and reshape data before it reaches slides
  • Data Landing Zone - bulk-upload workbooks that auto-match to your collections
  • Coming soon - corporate data middlewares, SFTP, and third-party data vendor API integrations (please contact us on which ones are especially relevant to you)

Why Data Integration Matters​

Without Data Integration​

  • Manually copy-paste data into slides
  • Charts and tables filled with placeholder content
  • Risk of stale or incorrect data
  • Time-consuming updates for recurring reports

With Data Integration​

  • Data flows directly into slides
  • Charts populated from your actual data files
  • Parameter-based selection (e.g., "December 2024 report")
  • Single source of truth for quantitative content
  • Fast updates when new data is available

Core Concepts​

Data Collections​

A Data Collection is a logical grouping of related data files. Think of it as a folder with rules about what goes inside.

Examples:

  • "Monthly Sales Data" - CSV files with sales figures
  • "Portfolio Holdings" - Excel files with investment data
  • "Market Metrics" - Performance data by date

Each collection defines:

  • File type (CSV, Excel .xlsx and .xls)
  • Parameters that identify individual files (valuation_date, portfolio_id, etc.)
  • How parameters map to filenames or row values (prefix, suffix, sheet name, row filter)
  • Parsing options (sheet, rows/columns to skip, filename pattern for bulk upload)

Parameters​

Parameters are the identifying characteristics that distinguish one data file from another within a collection.

Common parameters:

  • valuation_date - The date the data represents
  • portfolio_id - Which portfolio or segment
  • department_id - E.g. to identify your internal department to load sales figures for.

Example: In a collection with parameters valuation_date (suffix) and portfolio_id (prefix), files are named like:

PORTA_2024-12-01.csv
PORTB_2024-12-01.csv
PORTA_2024-11-01.csv

Transformations​

A transformation is a saved recipe that starts from a collection (or another transformation) and applies ordered steps - select columns, filter rows, sort, union tables, computed columns, and more. The output is resolved with the same parameters as its sources, so workflows can link to a transformation instead of raw files when slides need prepared data.

See Transformations for step-by-step details.

Data Landing Zone​

The Data Landing Zone accepts multiple workbook uploads at once. Files are matched to collections by filename pattern (and sheet, when configured) and ingested automatically - useful for recurring report packages.

See Data Landing Zone.

Data-Connected Shapes​

Templates can include shapes (charts, tables, text fields) that are marked as data-connected. These shapes are linked to a data collection or transformation and are populated with resolved data during slide generation.

Shape types that support data connections:

  • Charts - Bar, line, pie charts populated from data
  • Tables - Data tables with rows and columns from your files
  • Text fields - Each data row becomes a paragraph; each cell becomes a text run within that paragraph

The Data Flow​

1. Upload and Organize​

Upload data files to collections individually, or drop a batch into the Data Landing Zone. The system validates filenames and patterns. Optionally define transformations to reshape data for specific slides.

2. Configure Connections​

When starting a presentation, configure which data to use by setting global parameters (e.g., valuation_date = "2024-12-01").

3. Validate Availability​

Before proceeding, validate that all required data exists. The system checks each data-connected shape and reports any missing data.

4. Generate with Data​

During slide population, charts and tables are filled with your validated data.

Integration Points​

Data integration works with:

FeatureHow Data is Used
TemplatesDefine data-connected shapes (charts, tables)
WorkflowsOptional pre-configuration of data collections
Slide DecksConfigure parameters and validate data before generation
Content AssistantAdd data objects as content pieces during build phase

Best Practices​

For Data Organization​

  • Use consistent naming conventions
  • One parameter per filename component
  • Keep collections focused (one data type per collection)
  • Use date formats that sort chronologically (YYYY-MM-DD or YYYYMMDD)

For Template Design​

  • Name data-connected shapes descriptively ("Revenue Chart", "Holdings Table")
  • Link shapes to appropriate collections
  • Include fallback content for shapes without data

For Presentation Creation​

  • Set all global parameters before validation
  • Review validation results carefully
  • Check that data is current before generating

Next Steps​