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DATA SCIENCE 2018-02-14T08:04:31+00:00

Adopt data-driven machine learning to improve future outcomes

By doing data science not statistical modelling

  1. GrayMatter practices an exploratory approach to discover relationships between variables.
    This is opposed to statistical modelling wherein an assumed hypothesis is confirmed or rejected based on statistical significance of the assumed relationships. What this means is that we let the data free to provide all possible patterns instead of trying to force fit the data into one of the assumed hypotheses

  2. Validation of patterns with the help of domain experts to confirm meaningful relationships
    What this means is that all the possible relationships are validated with the help of GrayMatter’s domain experts, that ensures that the model is relevant

Data Science as a Service
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Data Science Services

Data Science Consulting


Scope identification, feasibility assessment, choice of tools and algorithms

Data Science Services

Data Preparation

Enriching the data set by missing value replacement, outlier analysis, categorical variable definition

Data Science Solutions

Model generation

Generating the model, testing and refining on basis of validity of output

Data Science Consulting Companies

Performance Tuning

Enhancing model and scripts on ongoing basis, over and above model self-learning

Data Analytics Consulting


Migration of algorithms, models from one platform to the other, e.g., SAS to R

Data Science Service Providers


Training of business users as well as technical teams on SAS, Python and R

Expertise across Technology Stacks

GrayMatter has a dedicated Center of Excellence for Data Science (CoE-DS) with expert Data Scientists. GrayMatter’s Data Scientists have skills in a variety of Data Science as a Service related technologies & tools including SAP PA, MS Cortana, R, SAS, Python, SPSS, Weka, MATLAB and others