As Big Data continues to grow across a wide variety of industries, Data Science has evolved as a key interpretive instrument to learn, discover and innovate. Data Science uses associative thinking and mathematical and scientific methods including algorithms to explore Big Data to create meaningful results that exhibit predictable and reproducible behaviors.
The data revolution has created a new opportunity to draw upon statistics and Machine Learning in clever new ways that allow for better answers. Framing questions statistically allows organizations to extract strategic knowledge that can enhance performance for industries, educational institutions, social media venues, government and commerce.
Data Science requires effective collaboration between several key professional communities as follows:
1. Database Management for the organization of data and resources
2. Statistics and Machine Learning to convert data into meaningful information
3. Distributed and Parallel Systems to provide the necessary infrastructure for data analysis
In addition, a communications component is required to interpret the data and present it in a meaningful way.
The potential applications for Data Science continue to emerge exponentially. Some current day examples of Data Science employment include:
LinkedIn- to generate ideas for products, features, and value-added services
Intuit- to develop insights for small-businesses and consumers for social design and marketing.
General Electric- to optimize service contracts and maintenance schedules for industrial products
Google- to refine core search results and promotional ad algorithms
Zynga- to optimize the game experience for revenue and promote long-term customer engagement
Netflix- to improve the company’s movie recommendation system
Kaplan- to uncover effective learning strategies
And the list goes on.
Contact Us today to discuss how we can use data science to help your business discover important insights and seek strategic answers that will give you a competitive advantage!