The Automated Data Analyst

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FOR WHO?

A solution for everyone
executives, researchers, data scientists

ADAN combines years of commercial and scientific expertise to provide a solution that resonates with everyone.

Senior data scientists: Drastically reduce the time analyzing data.

Junior data scientists: Acquire the skills of a seasoned veteran.

Executives: No need for a data scientist. ADAN can do the job for you.

Researchers: You no longer need to look far for a statistician to analyze your data.


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WHY ADAN

Data is today's oil.
ADAN extracts the value from it.

ADAN uses the latest advances in machine learning and statistics in order to automatically extract the most interesting patterns in your data and present them in an interpretable form.

An interpretable model: A clear equation explaining the data.

A predictive model: An ultra powerful black-box model for making predictions.

A clear presentation: Understand the key drivers in your data, in the simplest possible way.

3 EASY STEPS

We create value from your data through our experience-based,
3 step process.
LOAD DATA

Load the data, no matter how small or big. ADAN is optimized for machines of all sizes from small machines to large clusters.

ANALYZE

ADAN runs a set of sophisticated algorithms on a highly scalable system to extract value from your data.

DELIVER

The solution is explained in various degrees of complexity, from a simple explanation for non-techies to a fully detailed explanation for data scientists.




Cost-efficient

The most cost-effective option for data analysis.

Time-efficient

The fastest way to results.

Growth

ADAN scales easily to big data.

Expert

ADAN is based on advanced commercial and academic expertise.

USE CASES

  • Explain your data with simple equations such as: \(sales = \frac{2}{5}\ price^2+0.45log(\sqrt{discount^2+stock})\)
  • Filter out the best features from huge datasets in a short time, and combine features to create new ones: From simple interactions such as \(sales*stock\) to features of arbitrary complexity such as \(\frac{sales\exp(stock)}{2\sin(discount)}\)
  • Automatically try and tune a huge range of machine learning models in order to provide the one with the best predictive capabilities.
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client

Explanatory
equation modelling

client

Feature
selection and creation

client

Predictive
modelling