The Easy Way to
Your Data

Guiding you to build data science projects remarkably fast, collaboratively and without writing code.
More powerful than dashboards and more intuitive than notebooks.

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Inside Graphext.

The Graph
Compare
Trends
Details
Insights
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Connect Data.

Pull data directly from databases like PostgreSQL, MySQL, Google BigQuery and more. Integrate with Google Drive and Sheets.
Drag and drop files into your Graphext workspace to start working with datasets. We support a range of file types including CSV, JSON and SAV.
Use Tractor to create new datasets from information posted on popular platforms including Twitter and Google News.
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Build Projects.

Create and deploy powerful clustering and prediction models on your data using the guidance of our setup wizard.
Filter and sample your data directly from your Graphext workspace. Switch and control the variable types in your data.
Enrich your analysis with information from popular APIs or external sources with census, climate or socio-demographic data.
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Explore & Analyze.

Discover communities and their features using the visual representation of the Graph to explore your datasets.
Find temporal patterns in your data at a glance. Switch between chart types and detect anomalies and trends automatically.
Uncover the relevance of variables in explaining similarities and differences between segments of your data.
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Report Insights.

Capture your findings as you move through your analysis. Create reports to help tell the stories in your data.
Save and download charts, tables and insights as exportable image files.
Publish and present your Graphext project. Embed projects in any website to start sharing aspects of your analysis online.
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Resources

Good Risk vs Bad Risk: Deconstructing the Features of 1000 German Loans

Attempting to discover the most influential features of a loan application when considering risk, our team built a model using the features of a loan application to predict whether an applicant would have a good or bad risk rating.

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Jake's Project: Investigating the Data Behind a Good Day

Andy and María meet with Jake to talk about a dataset he's building about himself. From skating to people he sees to whether he flosses or not - Jake's data offers a unique and deeply personal insight into his life. But what makes the difference between good and bad days?

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Simple Solutions to Prevent Customer Churn

Our team analyzed 7043 current and former customers of a telecoms provider in order to better understand what types of people are most likely to cancel their contracts.

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How Data Can Help You Keep Your Workers

To showcase how a company could reduce employee turnover, our team clustered a dataset containing information about IBM employees to discover the reasons why employees left their jobs.

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A digest of our blog data analysis, product updates and company news
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