Data Science and Analytics

Turn big data into intelligence and actionable insights

Data Science and Analytics 2017-12-05T20:27:22+00:00

Big Data isn’t a technology initiative to be left entirely to data scientists and IT departments. It’s a strategic business opportunity that requires technical savvy and organizational coordination. To succeed, companies need to embed Big Data and analytics deep into their organizations to ensure that information and insights are shared across business units and functions.

Big data unlocks hidden opportunities and insights. QuantFarm turn technology into business outcomes by delivering information management, business intelligence and analytic solutions under one umbrella.

We become a valuable asset bringing profound expertise in certain areas of data science, such as deep learning, text analytics, data mining, and pattern recognition.

QuantFarm’s Advanced Analytics practice provides three services to clients:

We develop advanced analytics strategies, helping clients derive competitive advantage from their data assets and analytic capabilities.

We deploy advanced analytics for decision support, helping clients improve operational effectiveness and efficiency through innovative uses of data and analytics.

We help clients build the advanced analytics organization and capabilities required to execute strategies and deploy decision support applications.

Companies looking at Big Data often seek the power of new external datasets. While these new datasets can be valuable and are often leveraged in Bain casework, we find that there is frequently a wealth of untapped opportunity for companies to more effectively use the data at their fingertips:

  • We begin by setting the strategic rationale for a company’s analytics journey.
  • Next, we identify the analytics use cases that present the highest value opportunities.
  • With the strategy clearly articulated, we bring analytical rigor through the expertise of our team, which can support a multitude of analyses, including: predictive modelling, customer segmentation, experimental design, pricing optimization and more.


  • Machine learning
  • Deep learning
  • Natural language processing
  • Computer vision
  • Predictive Modelling
  • Anomaly Detection