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Role of Augmented Analytics in Increasing the Efficiency of an Enterprise
Augmented analytics has become a revelation in the field of data analytics. It has allowed businesses to close the gap with their data. The augmented analytics process uses machine learning techniques and natural language processing to automate data analysis. The augmented analytics technique also allows non-technical users to automate most of their data analytics as this technology combines artificial intelligence with business intelligence.
Augmented analytics handles all the repetitive processes, allowing technical analysts and data scientists to focus on other complex queries. Non-technical users can interact with augmented analytics solutions by asking questions directly like Google and Siri. The users get instant answers, which helps them to reduce reporting time and accelerate strategy and performance.
Here are a few ways in which augmented analytics help users working in different processes in an enterprise:
Data Scientists: Augmented analytics solutions help the data scientists by doing all the repetitive works itself. This allows the data scientists to focus on complex processes, in turn helping their organization to have the edge over their competitions.
Marketing Executives: Marketing managers need instant access to data and the ability to automate the analysis process to help the organization capitalize on marketing opportunities and understand customer behavior. Augmented analytics process helps the marketing executives to isolate the marketing channels which are bringing customers and business.
Brand and category Managers: Augmented analytics technique helps the brand and category managers in looking for deeper insights into the proceedings such as the correlation between the buying frequency and the churn risk. The augmented analytics process provides a report of the findings in the natural language of the user.
Consumer Insights Researchers: Augmented analytics process helps a consumer Insights researcher to integrate internal data with syndicated data. The easy access and automated analysis process help them to track a company’s performance.
Digital Marketers: Digital marketers have an abundance of data, and they can leverage augmented analytics to make great use of their data. Augmented analytics process can help digital marketers to create an end-to-end view of website visitors by syncing their digital traffic with advertising data.