Monday, September 25, 2023

Five Compelling Reasons to Embrace Augmented Analytics

By Umme Sutarwala - May 26, 2022 3 Mins Read

Five Compelling Reasons to Embrace Augmented Analytics

Augmented analytics is one of the most recent breakthroughs in business intelligence technologies that assist the company. It’s a brand-new concept aimed at modernizing an organization’s analytical skills.

The newest method to consider data and analytics is indeed augmented analytics. Augmented analytics, in particular, allows for faster access to insights drawn from vast volumes of structured and unstructured data in order to provide machine learning-based recommendations. This intelligence aids in the discovery of hidden patterns and deviations in data, as well as the removal of human bias and the development of predictive skills that can assist an organization in deciding what to do next.

The basic notion of augmented intelligence is to supplement human information, automate repetitive operations, and empower enterprises; instead of replacing humans to make faster and wiser judgments. Let’s take a peek at some of the reasons why businesses should adopt augmented analytics.

Also Read: Seven Ways Enterprises Can Benefit from Augmented Analytics

More rapid decision-making

If consumers are not getting the expected results, augmented analytics will offer other datasets. All users can get reliable forecasts and projections based on past data with only one click.

Better data literacy

As enterprises continue to obtain vast amounts of data, it is critical that everyone, irrespective of analytical expertise, can benefit from it. By automatically surfacing and explaining findings in natural language, providing a suggestion, and allowing all users to take action confidently, democratizing Artificial Intelligence (AI) across the data value chain boosts data literacy. This helps to develop a data-driven culture that will benefit the company in the long run.

Can provide more value

Manually doing repeated activities is time-consuming when establishing higher-level business solutions rather than putting in the effort to combine analytics with human intelligence. It is preferable to create an automated system that can do activities such as data preparation, execution of Machine Learning (ML) and Deep Learning (DL) algorithms, finding of insights, and so on. This is beneficial to businesses at all levels.

Also Read: Reimagining BI and Analytics with Augmented Analytics

Data democratization across firms

Platforms for augmented analytics are not simply for analysts but all users. They are designed primarily for non-technical business users. This allows everyone to communicate with data. Data democratization necessitates a solid data strategy and culture, as well as the necessary infrastructure.

When choosing a deployment strategy, companies must consider factors like speed, future needs, budget, and the types of workload expected. Although it is crucial for firms to make this decision after establishing their data strategy, in theory, it requires a solid augmented analytics infrastructure to make it work. This allows everyone to benefit from superior AI-powered insights while keeping all intricacies hidden. In other words, this enables enterprises to democratize data across the board.

Enables consumers to make more informed, data-driven decisions

According to a RevealBI survey of software developers and IT professionals conducted in 2021, 41% of businesses have seen a surge in requests for data and analytics. Allowing people to make data-driven decisions is one of the main reasons.

When end users gain access to analytics, they might find answers to questions they didn’t realize they had and ask new ones. It also enables corporate business users to quickly identify the source of problems and implement data-driven solutions to issues quickly.

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Umme Sutarwala

Umme Sutarwala is a Global News Correspondent with OnDot Media. She is a media graduate with 2+ years of experience in content creation and management. Previously, she has worked with MNCs in the E-commerce and Finance domain

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