Data Management

Features
Manage complex and growing datasets with versioning, diff tools, and data flows (merging, stacking, recoding, transforming).

Difference Tools

Compare datasets or revisions to notice field and value modifications and/or calculation differences

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Staging Slots

Test edits in separate environment(s) before pushing live.

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Inspection

See everything by inspecting all data cells to find unique values and frequencies.

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Data Flows

Automate data processing by creating a visual workflow diagram with intuitive stages: Transform fields via recodes, re-basing, renaming, and rollups. Merge records with unions and joins.

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Dimensionality

Elegantly handle multi-dimensional data through features that allow unrolling loops and picks, etc., without the need to manually restructure datasets.

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Dependencies

Easily find dataset and field references to understand all side-effects and answer important questions such as: "Where is this field being used?"

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Automated Tests

Ensure data integrity with automated tests that run every time a new dataset revision is published. Prevent common and repeat mistakes.

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Analytics

Features
Utilize performant modern compute clusters while elegantly handling the nuances of market research data and requirements.

Custom Models

Custom modeling is accomplished through thoughful organization of standardized calculation stages. This is probably less effort than writing raw scripts (R, Python, SAS, SQL), and powerful, intuitive and performant.

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Parallelism

Iterative calculations such as price sensitivies and various forms of optimization may be accomplished by running multiple pipelines or dataflows in parallel for ultimate scalability.

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Extensibility

As calculations are performed by the compute servers, authors may tweak the inputs/outputs using Javascript. This offers extreme customization for both calculations and data visualization.

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Visualization

Features
Create clean, sharp, professional user interfaces using extensible open-source visualization libraries.

Native Charts

Our basic charting libraries support Office Open XML features wherever possible, offering export (to Excel®, PowerPoint®) as native editable data-behind charts.

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Third Party Integration

Our visualization platforms offer the integration of 3rd party Javascript data visualization libraries for maximum extensibility.

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Powerful Export

We have a thoughtfully archited export model which offers clean, precise, scalable export visualizations which integrate well with themes and brand templates. Editable charts are supported (see Native Charts).

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Data-driven text

Authors may create programmatic text and phrases, such as a footnote that includes calculated sample sizes, or an intelligent recommendation that is data-driven.

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Themes

Palettes are used for UI elements and visualizations. They contain both named swatches and arrays. Swatches have color and text information.

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Images (icons, logos)

Incorporate lists of images and link them to items such as brand lists, country lists, segment personas.

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Intuitive Layout

When designing pages and slides, we offer intuitive container widgets that simplify layout mechanics.

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