Pattern Based Analytics

Quantum Leap Analyst is a Pattern Based Analytics platform that automatically identifies collections of patterns that enable you to:

  • understand what happened and why.
  • predict what might happen and why, and to be able to explore alternative actions in the context of future scenarios.

  • Pattern Based Analytics as implemented in Quantum Leap Analyst is:

  • Collectively exhaustive as Patterns in a Collection are guaranteed to cover the entire dataset.
  • Mutually exclusive as each data record from the dataset appears in only one Pattern in a Collection.

  • Patterns

    Patterns are something we all easily can relate to; we observe patterns in all aspects of our daily lives; they are a means to process things we see, hear or sense in a systematic fashion, a way to organize impressions into a regular or repetitive form, order or arrangement.

    Patterns are a fundamental way in which we organize our experiential knowledge as a basis for decision making.

    Patterns are the fundamental construct in Quantum Leap Analyst, whether they are user defined or discovered by Quantum Leap Analyst. A pattern will point to a well-defined data subset where the records all have some common traits. As an example, a group of records may be identified by the following pattern:

    Gender = Male AND Age = 40-50 AND Diagnosis = Chest Pain AND Treatment = PTCA.

    In Quantum Leap Analyst, patterns carry qualitative and quantitative information that will help you determine their relevance.


    Quantum Leap Analyst applies machine learning algorithms to discover target centric patterns in data. Unique to Quantum Leap Analyst, the algorithms also utilize a proprietary multi-dimensional extension of Shannon’s Information Theory, which helps determine the relevance of different attributes individually and collectively toward a specific attribute.