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Data is the new oil, and unlike oil, we are never going to run out of data. With more and more data being produced each minute, businesses have massive, complex datasets that are difficult to deal with. Digging deeper into the data to uncover valuable insights is vital for businesses to thrive.
While most businesses use BI and analytics solutions to derive visualizations from data, these tools often fail to give out the right insights. Preparing and analyzing the data to share findings remains a largely manual, lengthy, and tedious process, and business people struggle to find out which insights to act on. This is because most BI and analytics platforms fail to put the insights into context and uncover hidden patterns and trends in the data.
Introducing Augmented Analytics — the Next Frontier in Data Analytics
Augmented analytics is the latest evolution in data analytics that integrates AI and natural language processing elements into BI and analytics and changes the user experience across the entire process. It makes the process of preparing data, discovering insights, understanding correlations in the data, and sharing the insights with everyone in the organization more powerful and streamlined. Using machine learning and natural language generation, it automatically analyzes the data and converts the result of the analysis into data-oriented and detailed language-based insights.
Derive Insights on the “What” and “Why” of Business Data
Business intelligence has evolved from traditional BI that required manual interpretation and technical expertise to analyze data into a truly self-service automated approach to generate in-depth analysis from complex datasets. Modern self-service BI tools powered by augmented analytics have user-friendly interfaces that enable business users without technical and analytical skills to derive valuable insights from data in real-time. These tools can easily handle large sets of data from multiple sources in a faster and efficient manner.
With augmented analytics tools, organizations can easily uncover hidden trends in their data at the speed of sight and make improved business decisions. The insights derived from augmented analytics tools tell you not just “what happened” but also give an in-depth analysis of “why it happened.” It has the ability to reveal crucial insights, recommendations, and relationships between data points in real-time and present it to the user in the form of reports in conversational language.
Augmented analytics tools also enable users to query the data to get insights. Business users can simply ask the system questions such as, “How was the company’s sales performance in the last year?” or “What was our revenue change over the past two years?” Apart from deriving insights, the system can also give detailed explanations and recommendations around the insights, helping the users with a clear understanding of the “what” and “why” of their data.
It improves productivity, decision-making, and collaboration between users and promotes Data Literacy and data democracy across the organization. With augmented analytics, businesses can have:
- Better and quicker results
- In-depth analyses of hidden trends and patterns in data
- Actionable insights and automated recommendations
- Faster and improved decision-making
What Does the Future Look Like?
Augmented analytics is slowly becoming a must-have tool for businesses. It is going to change how people explore and analyze data. Augmented analytics will simplify and accelerate the preparation, cleansing, and standardization of data, thereby allowing businesses to focus all their efforts and energy on the all-important analysis.
Moving into the future, BI and analytics will become an immersive environment with integrations that allow users to interact with their data with more than just mouse clicks and keystrokes. Augmented analytics will enable new insights and data to be accessible via a wider array of devices and interfaces such as mobile phones, chatbots, or voice-enabled virtual assistants. It will aid decision-making by notifying the users of key insights or alerts that require their attention in real-time. This way, businesses can get instant updates on their data and stay up-to-date about the changes happening in real-time.