Augmented business intelligence (ABI) is the combination of augmented analytics and business intelligence. Augmented analytics is the use of enabling technologies such as machine learning and artificial intelligence to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and business intelligence (BI) platforms. BI refers to the procedural and technical infrastructure that collects, stores, and analyzes data produced by a company. Augmented analytics is the use of ML and NLP to enhance data analytics, data sharing, and BI.
Augmented analytics deftly manages to blend artificial intelligence elements with traditional BI. BI involved analyzing isolated databases to create basic reports. With graphical user interfaces and self-service business intelligence (SSBI) tools, business users get the information they need to make better decisions, with greater ease, and without having to rely a lot on data analysts and information technology professionals. SSBI solutions offer significant upgrades to the traditional model of data analytics. As the future generation of BI, augmented analytics improves the self-serve model in several distinct ways.
Big data: It refers to a large number of both structured and unstructured data. It is large data and has a complexity that none of the traditional data management tools can store or process efficiently.
Artificial intelligence and machine learning: Both make it easier for business users to prepare, analyze and get insights from their data. It also helps data scientists by automating many of the tasks involved in developing, managing, and deploying artificial intelligence and machine learning models. Using AI-driven techniques, AA can accomplish specific tasks by analyzing huge amounts of data.
Natural language processing: This technology allows ABI systems the ability to interpret and manipulate natural languages as humans do. One of the natural language processing applications in business is the development of improved chatbots.
Augmented Analytics (AA) uses artificial intelligence algorithms to automate data preparation for analysis by labelling and structuring business intelligence. It performs unbiased data analysis for objective BI inputs and identifies the root cause of problems with ease.
Unlike traditional business intelligence and SSBI which requires extensive amounts of time to work properly, augmented business intelligence can deliver insights in minutes. Business users at every level can use augmented BI to capitalize on time-sensitive opportunities.
While business intelligence technology requires Information Technology teams to do the heavy lifting, AA software frees up data scientists and data analysts to spend time on more important work. With this increased data democratization, AA solutions are predicted to lift the organizational adoption of business intelligence from 30% to 50%.
AA also helps make the technology accessible to more business users. Augmented business intelligence can speed up business decisions making and data-driven decisions. And enhance overall business performance. Instead of having people pouring over data, cleaning the data, and getting it into tables for reporting, augmented business intelligence uses artificial intelligence and ML to automate the entire process.
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