Advanced Predictive Analytics

We integrate with smart automated machine learning platforms such as and for automatic feature engineering, machine learning and interpretability.

Or use R and Python directly on all data sets and implement custom Artificial Intelligence algorithms.



What do you want to do?  Forecast sales numbers?  Identify customer segments exhbiting similar behaviors? Sentiment analysis towards a product or company?  Identify relationships between actions and results?

Read below on how Machine Learning algorithms can help you.



Identify the relationship between one metric and its contributing factors and then use the model to estimate the metric given a new set of factors.

The most common use of regression analysis in business is to predict events that have yet to occur. Demand analysis, for example, predicts how many units a customer will purchase.   Some other examples include estimate SKU pricing, production efficiency, hiring, and similar types of models.



Given a set of properties about the topic of interest, group similar topics using those characteristics and identify other possible topics with the same factors.

The most common use here is the identification of possible customers churning, creation of targeted marketing campaigns or sentiment analysis.

ANALYSIS. Seamless vector pattern with word cloud.


Sometimes data is not neatly laid out in columns and clearly identified as to its meaning and instead be just a blob of words and phrases collected via surveys, commentaries, social media, and documents.

Text analysis allows for the classification of those words into discrete categories.

Useful for sentiment analysis of products, services or companies, automation of documents or text based data.



Using time series regression, you use historical data based on time to forecast its future growth.

This is a widely used approach to predict sales, energy consumption, demand planning and many other time based data.



You can integrate ClicData with many of the most popular Machine Learning/AI platforms available today.  Here are some of our customers' favorites.


Open Source Machine Learning

H2O is an open source, distributed in-memory machine learning platform.

H2O supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more.

H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models.


Automated Machine Learning provides an automated machine learning platform to generate and deploy highly accurate predictive models. Make your business data-driven by adding predictive intelligence to all your operations.

  • Increase productivity of your data science projects
  • Cut the time spent in implementation
  • Access detailed explanations of your models’ decisions on the platform itself
  • No prior technical knowledge or infrastructure is needed
  • Build standalone models using only your enterprise data


Get your hands in the code and connect Python to ClicData directly via our Dedicated option using SQL Server ODBC and save months of work in building connectors and data cleansing operations.

Using ClicData and pandas, an open source BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language, you can get your machine learning project off to a great start without spending a fortune.

White Papers

Download these free reports written by data experts to understand the role of Artificial Intelligence and Machine Learning in BI applications and their impact on the future of your business.

Machine Learning fo Business Intelligence

What's the future of BI? Machine learning has a great role to play in the interpretation of data and sure will improve business intelligence.

Future of BI: Artificial Intelligence

Despite the advances, BI remains relatively difficult to use. Artificial Intelligence can change and open up the world of BI and Data Analysis to everyone.

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