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Data Science and Advanced Analytics

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Healthcare
Sports
Telecommunication
Finance
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Retail
Internet of Things

What we do

  • Help businesses in Cross-Selling and Up-Selling using Association Analysis and recommender systems of transactional/customer data.
  • Business Problem solving using statistical techniques and machine learning.
  • Predictive modeling using regression and classification techniques.
  • Insights from unstructured text data through machine learning and natural language processing.
  • Drive Better Business Decisions by Using Advanced Forecasting Algorithms
  • HR analytics

Tools

R, Python, Hadoop, HiveQL, Sqoop, Spark, Pig, Oozie, Flume, MR, Tez, Hbase, NiFi, Cloudera, Hortonworks

Cognos (IBM), AWS, SPSS (IBM), Qlikview (Qlik), Power BI, Tableau, SQL & NOSQL DB.

Data Ingestion

A preliminary, yet important, step in an organization’s big data strategy is to lay-out a thorough plan for data consumption. We can assist you in doing so by:

Developing solutions that make previously recorded data existing in silos and legacy systems accessible to contemporary analytics platforms.

Identifying new sources of data and creating the necessary infrastructure to collect it based on your organization’s needs, the domain of operation, and expectations.

Implementing optimal strategies for data collection and storage as dictated by the complexity, volume, and accumulation rate of a particular data type.

Integrating/prepping multi-channel structured and unstructured data before analysis.