In this role of an analyst, one of the primary tasks is to create in-house capability by designing and implementing new functionality for business intelligence or data analytics. Often companies need to evaluate existing tools and develop new capabilities that will leverage what the company already has but in a more effective and efficient way. This allows for businesses to reduce the time spent on analytics initiatives and focus more time on business strategy and operations.
Domino is a powerful platform built on the open source platform to fill in the gaps and automate modern applied scientific research flows. SAS Talent Discovery by Nick Elprin (Founder, Domino Data Lab) leveraging scala code with an established product called domino compatible language called Domino Language, allows data scientists to create custom driven processes (also called function compositions) that can be executed in a self-contained environment. By leveraging scala code and the stable and popular domino platform, data scientists can build more in-house applications, perform more efficient and reliable analysis and also reduce the time spent on tedious analytics initiatives.
So how does it work? Domino Language allows users to use a language model to develop programs for domain specific purposes. For example, rather than writing programs in R or SAS for trend analysis, data scientists can utilize scala to create programs that can perform the analysis in a manner that is more efficient, error free and easy to maintain. The language allows for greater comparability, e.g. rather than having to write code for every function, a programmer can write a function once and reuse that code throughout the application. The language also allows for easier version control and versioning as well as support for multiple versions of the program.