Data Science & Analytics


Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. Data analytics is essential for creating actionable intelligence and is the main force driving informed business decisions. However, only the interdisciplinary field of data science will reveal ‘whys’ and ‘hows’ hidden in various reports, spreadsheets, numbers, and graphs.

Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social science. The field encompasses the larger areas of data analytics, machine learning, and managing big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation.


Super Coding


What is happening currently, based on incoming data. Typically, a real-time dashboard and/or email reports.
Best User Interface


A look at past performance to determine what happened and why. The result of the analysis is often an analytical dashboard.
Unique Design


An analysis of likely scenarios of what might happen. The deliverables are usually a predictive forecast.
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This type of analysis reveals what actions should be taken. This is the most valuable kind of analysis and usually results in rules and recommendations for next steps.