Finding Meaning Behind the Numbers

We help people develop data skills, understand where measures come from, identify relationships between records, and write well-supported findings based on the available information.

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Where Siftanox Took Shape

Siftanox began with the intention of explaining Data Analysis Basics without overwhelming learners with complex terminology. The team combined experience in tables, databases, record review, and reporting to create sequenced courses for independent study.

  • Kellie Erickson

    Kellie Erickson

    Research Data Analyst

    Kellie works with learning

    studies, categories, and

    comparisons between groups.

    She develops structured analytical

    questions and identifies the data

    needed to examine them.

  • Walton Stuart

    Walton Stuart

    Dataset Structure Analyst

    Walton works with table

    structures, value types, and the

    logical organization of information.

    He prepares examples that explain

    relationships between rows,

    columns, and categories.

  • Annette Meza

    Annette Meza

    Survey Data Analyst

    Annette reviews responses,

    categories, scales, and record

    coverage within survey datasets.

    She demonstrates how to group

    findings and describe differences

    between participants.

Step Inside the Course Structure

Explore the Siftanox course collection covering tables, measures, record quality, and foundational work with connected datasets. Each course examines a separate part of the analytical process and builds on earlier subjects through new examples and assignments. Course pages describe the module content, learning objectives, and included final tasks. Choose a direction that matches your current knowledge and the subjects you would like to study.

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    Data Logic

    Each topic shows

    how tables, measures,

    categories, and findings

    connect within one

    analytical process.

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    Working Examples

    Learning scenarios help

    participants apply new

    knowledge when

    reviewing records,

    comparing groups, and

    preparing summaries.

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    Flexible Pace

    Learners can organize

    their own study

    schedule, revisit

    selected modules, and

    spend more time on

    challenging subjects.

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    Clear Explanations

    The materials describe

    terms, calculations,

    and methods without

    adding unnecessary

    complexity.

  • Darryl Sellers

    Darryl Sellers

    Darryl worked with recurring internal reports but often

    spent considerable time reviewing category labels, repeated

    records, and inconsistent date formats. He found the

    separated dataset-review stages and concise checklists

    particularly useful.

    “I started documenting every table change, and I could finally explain where each summary measure came from.”

  • Margret Powell

    Margret Powell

    Margret wanted to write analytical summaries without

    broad wording or assumptions that were not supported

    by the table. The format helped her connect each

    observation to a defined measure, period, category,

    and limitation note.

    “My reviews now show not only the result, but

    also the conditions under which it was calculated.”

30-Day Money-Back Guarantee

Try the course risk-free. If you're not satisfied for any reason, get a full refund. No questions asked. Refund requests may be submitted within 30 days in accordance with our Refund Policy.

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Begin with a Small Data Practice

Begin exploring the Siftanox approach with a free learning material focused on Data Analysis Basics. It covers table structure, value types, record checks, and the writing of concise observations. The material includes a focused task that applies the explanations to a learning dataset. It offers a helpful introduction to the format and subject matter before selecting a complete course.