Set of operations aimed at creating interfaces and mechanisms for the flow and access of information. It takes dedicated specialists – data engineers – to maintain data so that it remains available and usable by others.
A non-linear, iterative process that teams use to understand users, challenge assumptions, redefine problems and create innovative solutions to prototype and test.
Moving your work to the cloud, including migrating apps, data, software programs or the entire IT infrastructure in line with your business objectives. Objective is to have the ability to quickly adopt new technology while also responding to new competitive threats and immediate market needs.
Data Science explores and tests new methods to use and interpret data, while Data Analytics focuses on analyzing datasets and finding insights and solutions to problems.
Continued process of transforming Legacy Systems in order to reduce IT environment complexity and costs, increase data consistency, enable collaboration across platforms and improve process flexibility.
Strategy of analyzing and improving your business processes. Automation is the use of technology to execute recurring tasks or processes in a business where manual effort can be replaced so as to minimize costs, increase efficiency, and streamline processes.
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