Big Data

In this Digital Age with daily 500 million tweets, 3.6 billion Instagram posts, 4.3 billion Facebook messages, 205 billion emails and 6 billion Google searches, it has become incredibly difficult to stay on top of all this data with traditional analysis tools, let alone rely on human labour.

There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.

Eric Schmidt, of Google, said in 2010

Speedminer Big Data introduces Machine Learning that handles huge data volumes and is capable of learning from customer’s historical data and merge it with information from social media, publication or web sites to find the patterns, trends and associations. This is done so that it can construct the Predictive Model that can predict future business trends to help our customers to look into the future of their business.

Accurate prediction prepares you for the uncertainty of tomorrow.  If you know a customer is dropping out tomorrow, can you do something today that may turn the situation around? The answer is probably yes if you know the right thing to do.  This is exactly what Speedminer Big Data is designed to provide – the information for you to do the right thing.

It is not enough to do your best; you must know what to do, and then do your best.

W. Edwards Deming

Since ancient days, everyone is dreaming to be able to predict the future.  Wizards with the crystal ball seemingly able to foretell the future, but in this modern age of technology, can you still trust such magical power without facts?


Speedminer Big Data connects to various data sources to extract relevant data, process it to create predictive model to assist you to look into the future, with a proven scientific way

Text Analytics:

Speedminer Text Analytics supports the following features and more:


Speedminer comes with internal big data engine, but it is also capable to integrate to external Open Source to enrich the modeling capability:

  • Spark
  • Python
  • R
  • Hadoop

Speedminer Big Data comes with supervised and unsupervised learning to handle structured, semi-structured and unstructured data.


Predictive Modelling:

Speedminer supports various predictive modelling algorithms and visualization including

  • Linear Regression, General Regression
  • Logistic Regression
  • Neural Network
  • Decision Tree
  • SVM
  • KNN
  • K-Mean
  • Random Forest
  • Graph Theory