Data Science As Service

We use state of the art data science principles to derive insights and build innovative solutions. We use the following methodology (also described in the figure below) to derive insights from your data.

Either you have structured or unstructured data, we have the expertise to understand and consolidate your big data. Once we develop good understanding about your data, we design and implement Data Mining, Machine Learning and Natural Language Processing solutions to bring insights and build innovative services that reduce cost and improve efficiency in your business processes.

DataScienceModel-2

We enable companies to develop new solutions to gain competitive advantage. Either its data storage problem, development platforms or its integration, analytics and reporting tools, open source provide a multitude of solutions. It’s useful to have a guide like us to provide insights about the underlying open source projects that are driving today’s – and tomorrow’s – solutions.

Data Mining

We build predictive models to optimize your forecasts while increasing profitability. We validate your computational models while testing them against the ground truth. We apply state of the art algorithmic and statistical techniques to optimize your financial products and services. In this context we use Open Source technologies such as Hadoop/Hive and Apache Spark to return the maximum value of your investments.

Machine Learning

We devise algorithms that iteratively learn from data. This basic approach allows our Machine Learning solutions to find insights from various forms of structured and unstructured data without the need of modifying computer programs that actually look for hidden patterns in data. In this context, we use simple and extensible programming framework such as Apache Mahout for building scalable Machine Learning based solutions.

Natural Language Processing

We device algorithmic techniques that allow computational processing and understand of English language. Over the past 5 years we have build expertise to understand legal (natural) language primarily used for drafting licenses, terms of services, developer agreements, and privacy statements. Our solutions enable syntactic parsing and tagging of English language for the purpose of risk assessment and sentiment analysis. In this context we use various Open Source technologies such as Google TensorFlow.

Open Source As Service

Data driven companies are using Open Source solutions to derive their innovations. Either its data storage problem, development platforms or its integration, analytics and reporting tools, Open Source provide a multitude of solutions. Below are some popular Open Source solutions that help in creating data-driven innovations.

Data Storage and Processing

Data Integration and Anlytics

Development Platform

  • OpenStack (Build private and public clouds)
  • Cascading (Java programming for data analytics)
  • REEF (Microsoft's Hadoop based development platform)
  • Python and R (Programming for predictive analytics)
  • Apache Mahout (Programming for Machine Learning solutions)

Next Steps...

Reach out to us for more details.