Augmented Analytics: How AI is Changing BI for Complex Data

Now more than ever, businesses in the digital age are amassing vast amounts of information. This vast amount of data is incredibly valuable for companies to make informed decisions, but it can also be challenging to manage and analyze. This is where Business Intelligence (BI) tools come in - they provide businesses with powerful insights into their data, helping them make smarter decisions. 

However, as data becomes more complex, traditional BI tools are struggling to keep up. Augmented Analytics is a ready solution to all our modern Business Intelligence dashboard problems. 

What is Augmented Analytics?

Augmented Analytics is a new generation of Business Intelligence tools that leverages artificial intelligence (AI) and machine learning to enhance the process of data discovery, analysis, and insights generation. Unlike traditional Business Intelligence software, Augmented Analytics tools can analyze complex data from multiple sources in real-time, providing businesses with actionable insights faster than ever before. 

These tools use AI algorithms to uncover hidden patterns, trends, and insights, providing users with data-driven recommendations that are intuitive and easy to understand.

Benefits of Augmented Analytics for Business Intelligence

Improved data discovery and analysis

One of the main benefits of Augmented Analytics is its ability to automate the data discovery process. Augmented Analytics tools can analyze large datasets quickly and efficiently, identifying relationships and patterns that would be hard for humans to uncover. This automation enables businesses to get answers to their most pressing questions promptly and efficiently.

For example, a retail company used an Augmented Analytics tool to analyze its sales data across multiple channels. This augmented business analytics software quickly identified that certain products sold better in specific regions, allowing the company to optimize its inventory management and increase sales.

1.More accurate insights and predictions

Another benefit of Augmented Analytics is its ability to provide more accurate insights and predictions. Traditional Business Intelligence tools rely on human analysis, which can be influenced by personal bias and error. Augmented Analytics tools, on the other hand, use AI algorithms to analyze data objectively, eliminating the possibility of human error.

For example, a healthcare organization used an Augmented Analytics tool to analyze patient data and identify the factors that were causing the most readmissions. The Business Intelligence dashboard with augmented analytics identified that patients who were discharged on a Friday had a higher likelihood of being readmitted. This insight enabled the organization to adjust its discharge practices, reducing readmission rates significantly.

2.Increased speed and efficiency

Augmented Analytics tools can analyze large datasets in real-time, providing users with insights faster than ever before. This increased speed and efficiency can save businesses significant time and resources, allowing them to make more informed decisions quicker.

For example, a manufacturing company used an Augmented Analytics tool to monitor their production processes in real-time. The tool alerted the team to a problem in one of their assembly lines, enabling them to fix the issue before it caused any significant downtime or quality issues.

3.Reduction in human errors and bias

Augmented Analytics tools can eliminate human errors and biases that can occur when analyzing data manually. These Business Intelligence tools use algorithms to analyze data objectively, providing unbiased insights that businesses can trust.

For example, a financial services company used an Augmented Analytics tool to analyze customer data and identify trends in their spending habits. The tool identified a group of customers who were using their credit cards for fraudulent purposes, enabling the company to take action before any significant losses occurred.

Key Features of Augmented Analytics Tools

1.Natural language processing

Many Augmented Analytics tools use natural language processing (NLP) to make it easier for users to interact with their data. This technology enables users to ask questions in plain English and receive data-driven answers quickly and efficiently.

2.Autmated data preparation and cleaning

Augmented Analytics tools can automate the process of data preparation and cleaning, reducing the time and effort required to analyze data. This automation can also eliminate the risk of human errors during the data cleaning process, ensuring that the insights generated are accurate and trustworthy.

3.Smart data visualization

Augmented Analytics tools provide users with smart data visualization capabilities, making it easier to identify trends and patterns in complex data. These visualizations can be customized to meet the user’s specific needs, providing a more intuitive and interactive experience.

4.Predictive modeling and forecasting

Many Augmented Analytics tools provide businesses with predictive modeling and forecasting capabilities. These tools use AI algorithms to analyze historical data and predict future outcomes. This information can help enterprises to make more informed decisions and plan for the future.

Future of Augmented Analytics in Business Intelligence

The adoption of Augmented Analytics is expected to overgrow in the coming years as businesses seek to extract insights from their data more efficiently and accurately. As the technology continues to evolve, we can expect to see more advanced features and capabilities, such as advanced natural language processing, real-time predictive modeling, and automated decision-making.

However, there are also potential challenges and limitations that businesses need to be aware of when adopting Augmented Analytics. These include concerns around data privacy and security, the need for skilled data analysts to interpret the insights generated, and the potential for AI bias.

Conclusion

In conclusion, Augmented Analytics is transforming the world of Business Intelligence tools by providing businesses with faster, more accurate insights into their data. The technology is allowing companies to analyze complex data in real-time, generating insights that were previously impossible to uncover. As businesses continue to create more data, the need for advanced BI tools like Augmented Analytics will only continue to grow. 

Want to level up your Business Intelligence? Try Grow's Business Intelligence dashboard today and experience the power of Augmented Analytics for yourself. 

With advanced features like automated data preparation, smart data visualization, and predictive modeling, Grow's Business Intelligence tools can help you unlock insights from even the most complex data. Sign up now for a free trial and see how BI tools can transform your business on Grow data dashboard Trustradius.

Article source: https://article-realm.com/article/Finance/38155-Augmented-Analytics-How-AI-is-Changing-BI-for-Complex-Data.html