Questions? We got you.

Data is complex but Graphext is here to make it easy. Take a look at our frequently asked questions.

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Anything you want to ask? Want to request a demo? You can contact us at hello@graphext.com or click on the button below.

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Do I need to be a data scientist to use Graphext?
You don’t have to have a technical background to use Graphext. Our product is designed to be used by everyone. We provide step by step guidance to help users create and explore their data, but we also offer an advanced “editor” so more experienced users can get more out of the product.
What technology do you use to visualize the Graph?
We use dimension reduction techniques to map out multi-variable data sets in two dimensions so users can visually identify patterns and outliers in their data.
Is Graphext a data visualization company?
We are a lot more than that. We pride ourselves in having cool visualizations, but in reality, we offer an end-to-end data analytics solution that covers data preparation, exploration, analytics, and reporting so we could help you in each step.
What is the advantage of data exploration before analysis?
When you work with a unfamiliar data set, you may need to establish and test many hypotheses in order to find insights from your data. Working under the wrong hypothesis could bias your analysis and produce inaccurate results. Our suggestion is to explore the data with Graphext in order to first confirm your hypothesis. That way you can develop more accurate analysis and save time.
What is data enrichment?
Within Graphext, we connect with a few external APIs and we are developing an increasing amount of API connections to improve data enrichment, so when you choose to enrich your data, we can retrieve additional information such as location, demographic, contact that will complement your existing data.
How does Graphext cluster data?
We cluster data based on their similarities. We use un-supervised learning so the clustering result is unbiased.
How accurate is your clustering?
The clustering result is subject to interpretation. We aim to help users to put their data in business context so they can easily explain their finding to their audience.
I have sensitive data. Can I install Graphext on premise?
Of course! In fact, our platform is built using Docker, and it is ready to be installed in laptops, local or cloud servers
Is Graphext only a social listening tool?
Although Social Listening is one of the most popular use cases of Graphext, we offer much more! Basically we can analyze any type of data. And many customers use us to do customer profiling, retention analysis, survey analysis, product recommendation, text analysis, etc.
How much data can you process?
Is there a size limit? - This question depends on the type of dataset we are working with. The upload limit to Graphext is 4GB. With complex datasets including texts, each project can process up to 300MB of data. If you are data set is larger than that, we may be able to analyse it on case by case basis. Send us an email and we will get back to you.
What languages can Graphext process?
In our text analysis, we are able to process all major European languages including English, German, French, Spanish, Italian. For the Spanish market we also integrated Catalan in our language processing capability.
How much does Graphext cost?
Our pricing is seat based. Request a demo and we will get back to you. However, you can give Graphext a try for free!
Do you offer a free trial?
Yes. We offer a limited version of Graphext which you can use completely for free. Sign up here.
Do you offer professional services?
Yes. We have a dedicated team of Data Scientists who provide advisory and consulting services to customers on project base.
I just asked for a demo. When will you get back to us?
Within 24 hours

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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