LEVERAGE AUGMENTED ANALYTICS FOR ULTIMATE BUSINESS TRANSFORMATION

Our new modern era is facing the everyday challenges of dealing with enormous amounts of data, and businesses are having a hard time interpreting data through the pile of haystacks. However, modern technological solutions may be well-equipped to solve data complexity into meaningful insights with expert help. But as our world is advancing towards more AI-driven technologies, the complications of even performing the complicated task are a no-brainer.?

?With the help of a class of analytics powered by AI and ML technologies, the power to operate within a complex data structure has become possible through augmented analytics. Augmented analysis is a class of analytics powered by AI and ML technologies that contribute to expanding human’s ability to interact with data. It helps in bringing insights, recommendations and provides guidance to the users. There are three significant ways how augmented analytics is a faster, more accurate, and more efficient class of analytics than any other. Let’s see how;

• Increase speed to insight; augmented analytics can effectively look for extraneous details and maintain a high accuracy level to help users make well-informed decisions based on thorough analysis.?
• Provides a complete picture; within augmented analytics, the task automation feature allows users to save time and energy from performing algorithmic tasks like data preparation, data discovery, statistical analysis, etc.??
• Automatic task efficiency; augmented analytics gets powered by AI and ML technologies that can accelerate the search for insights and suggest valuable opportunities for analysis on its own.

Here are five main features that AI-driven Augmented analytics grants its users:

1. AUTOMATIC DATA IDENTIFICATION; AI-driven BI platforms can automatically identify certain attributes of enterprise data and look into minute details such as geographic information, postal code, personal information, etc. Furthermore, the system has the capability to read tables of data in the form of PDFs and documents to remove and convert special formatting for further analysis automatically.?
2. STATISTICAL TECHNIQUES; Augmented analytics powered by AI and ML technologies has a unique ability to select the best forecasting, clustering automatically, and other strenuous statistical algorithms predicated on which gives the most certainty. It automatically runs through the data to find and offer valuable insights that the user might not have seen. The user doesn’t require any expertise in writing codes and calculations to use augmented analytics solutions.?
3. SMART DATA PREPARATION: During data preparation, statistical algorithms work to assist users in preparing data faster to minimize manual cleanup. Within augmented analytics, the system automatically groups words by pronunciation or familiar characters to reduce the need to spend much time searching for fields and values.?
4. RECOMMENDATIONS; the most prominent feature of augmented analytics is its ability to make AI-driven recommendations, from data preparation to discovery, analysis, and sharing insights to the end-users. Businesses will benefit from the system that provides suggestions on exploring analytical content based on the role and helps the new users to onboard faster to get the most relevant data asset.?
5. NATURAL LANGUAGE INTERACTIONS; One of the advanced features of augmented analytics is its ability to interact with its users in their natural language and allow the users to get insights into their data query without needing to know any technical language or coding. Additionally, it benefits the users in not requiring expert help to interpret data visualizations into data stories.?

The role of augmented analytics in driving business transformation?

Data as a critical fuel for businesses, can create new revenue streams and enhance the quality of providing better customer experiences. The ones that are more capable and efficient at analyzing their business data will have far more impact than their competitors. For such reasons, more and more enterprises choose to opt for AI-driven augmented analytics to successfully analyze their complex data to turn them into data-driven insights.?

?Forrester, a well-established research and advisory company, has found out that companies that use data-driven insights grow eight times faster than those led by intuition.?On average, the growth of insights-driven businesses is likely to be 30%, i.e., $1.8 trillion earning more than their less advanced competitors by 2021. That is why to drive business transformation; businesses need to be well-equipped with data insights to stay resilient in the face of challenges.?

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