Accelerating Time to Value, Connecting Dots in the Data, Empowering Everyone

Python is a powerful, flexible, open source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. Its simple syntax is very accessible to programming novices, and will look familiar to anyone with experience in Matlab, C/C++, Java, or Visual Basic. Python has a unique combination of being both a capable general-purpose programming language as well as being easy to use for analytical and quantitative computing.

For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. It has been used to improve Space Shuttle mission design, process images from the Hubble Space Telescope, and was instrumental in orchestrating the physics experiments which led to the discovery of the Higgs Boson (the so-called "God particle").

At the same time, Python has been used to build massively scalable web applications like YouTube, and has powered much of Google's internal infrastructure. Companies like Disney, Sony Dreamworks, and Lucasfilm ILM rely heavily on Python to coordinate massive clusters of computer graphics servers to produce the imagery for blockbuster movies. According to the TIOBE index, Python is one of the most popular programming languages in the world, ranking higher than Perl, Ruby, and JavaScript by a wide margin.

At Continuum, we are developing the next generation of tools to make Python as powerful and successful for big data and business data analytics as it has been for science, engineering, and scalable computing. We are focused on providing end-user domain experts with the most expressive, easy-to-use tools for data structuring, manipulation, query, analysis, and visualization.

Every sector of business is being transformed by the modern deluge of data. This spells doom for some, and creates massive opportunity for others. Those who thrive in this environment will do so only by quickly converting data into meaningful business insights and competitive advantage. Business analysts and data scientists need to wield agile tools, instead of being enslaved by legacy information architectures.

Python is easy for analysts to learn and use, but powerful enough to tackle even the most difficult problems in virtually any domain. It integrates well with existing IT infrastructure, and is very platform independent. Among modern languages, its agility and the productivity of Python-based solutions is legendary. Companies of all sizes and in all areas — from the biggest investment banks to the smallest social/mobile web app startups — are using Python to run their business and manage their data.

Who's Using Python?