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Self-service Analytics has been around since the early days of computer technology. It began as a way to automate internal data analysis and reporting by allowing business users to access and analyze data without relying on IT professionals. Over the years, this technology has become increasingly powerful, allowing businesses to quickly analyze large amounts of structured and unstructured data in order to make informed decisions about their companyu2019s future.
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Integrating Self Service Analytic Tools in Your Workflow & Processes
Why do organizations need self-service analytics? We live in a self-service world that enables consumers to get things done on their own: from pumping gas (with the exception of a couple states), to shopping online, to ordering food delivery. The goal is to carry out tasks entirely independently (with the help of some computers), whenever and wherever you’d like. QUICK TITry right clicking on a photo and using "Replace Image" to build your own flash cards..
Who uses self-service analytics? Traditionally, self-service analytics is designed for business users who want to get answers when they need them and without relying on IT. Because you don’t need specialized knowledge or complex training to operate a self-service analytics platform, employees across your organization can reap the benefits—e.g., human resources, marketing, customer success, R&D, finance, or sales— of having access to the same data as those in advanced IT sectors.
Self-service analytics use cases Self-service analytics is being used across myriad industries and departments within organizations. Once the teams gained access to AI-powered, self-service intelligence, they were able to automate previously manual processes of analyzing data across brands. This enabled dramatically faster data modeling, leading to more timely insights shared across the organization.
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