Examining trends and future predictions for augmented analytics in BI.

Tell us if you have heard this before: data is the lifeblood of every organization, and the ability to analyze, manipulate and draw insights from relevant data keeps them in the competition. Among new developments in Business Intelligence (BI), augmented analytics is emerging as a transformative force to revolutionize how enterprises analyze and perceive data. As trends in BI continue to evolve, we will look at key trends and predictions that will shape the future of augmented analytics. 

The Power of Augmented Analytics

In its simplest form, augmented analytics can be explained as analytics that combines the power of AI (artificial intelligence) and ML (machine learning) to automate the preparation and analysis of data, identify trends and visualize this data. It differs from traditional analytics in that it does not require significant technical experience working with data - the ideal choice for enterprises that want to introduce self-service analytics. 

Augmented analytics offers enhanced data management and revolutionizes how organizations leverage data and influence strategy, decision-making and operations for the better.

In a nutshell, augmented analytics…

• Improves decision-making by making it possible for many users to access, process and interpret data. 
• Increases efficiency by automating tasks and removing the potential for human error. 
• Draws deeper insights by enabling users to examine data from numerous data sources, large data sets and different perspectives. 
• Provides a better understanding of customer behavior by presenting a 360-degree view of customer data and identifying patterns and trends. 
• Enhances the ability to predict outcomes and decide on a strategy. Predictive analytics uses AI and ML to process historical data to forecast outcomes, while prescriptive analytics provides recommendations on the best course of action.

Must Read: Learn more about Augmented Analytics and its impact here

Trends & Predictions for Augmented Analytics

There is no debate that augmented analytics has emerged among the top BI trends in 2024. Its potential in the realm of business intelligence is undeniable. However, as we look to the future, let’s examine the key trends and predictions that are set to shape the trajectory of augmented analytics. 

Democratization Of Data 

Democratization of data refers to empowering employees or business users across the board to analyze data without extensive technical expertise and with minimal effort. Augmented analytics automates and simplifies complex analytical processes, enabling users to query data by asking questions, assisted by Natural Language Processing (NLP) and guided by ML. Answers can also be automatically presented in visual formats like graphs or maps. 

Integration With Business Intelligence Platforms

Leading BI vendors have acknowledged that augmented analytics is the future and are increasingly integrating it into their existing platforms - if they haven’t already. Vendors offering augmented analytics are already seeing market traction from early adopters, which is unlikely to slow down. This BI integration enables business users to leverage advanced analytics tools while working in a familiar system. It enables seamless transitions from data visualization to predictive analytics and enhances decision-making, allowing organizations to expand their perspectives in new and exciting ways.

Enhanced Data Preparation & Data Quality Management

Data preparation can be time-consuming. Augmented analytics can change that by employing AI and ML algorithms to identify anomalies, predict outcomes and recommend corrections. These algorithms also refine their accuracy to provide accurate insights and enable real-time decision-making. The automation of monotonous tasks and the ability to adapt to new data inputs help save time and effort. 

Integration Of Advanced Natural Language Processing 

Natural Language Processing simplifies data analytics by allowing users to interact with data systems using a common language, thus making data exploration user-friendly. It is, therefore, one of the cornerstones of augmented analytics. It allows business users to run data queries without training in data science and transforms complex insights into understandable and actionable formats. Its integration into augmented analytics is vital, and as the technology evolves, it will become more sophisticated, further simplifying data processing and preparation. 

Real-Time & Streaming Analytics

Real-time data processing and analysis are essential for organizations to stay competitive. As such, real-time and streaming analytics in business intelligence are increasingly necessary. Real-time analytics refers to the immediate analysis of data and presentation of results while streaming refers to continuously generated and delivered data. Augmented analytics incorporates real-time and streaming analytical capabilities to allow enterprises to monitor events as they happen and act appropriately. They empower businesses to detect anomalies, identify opportunities, and mitigate risks more effectively, thus improving operational agility.

Ethical & Responsible AI

As AI-powered technology becomes more sophisticated and widespread, it is critical that its deployment is guided by transparency and accountability. Ethical AI practices prove essential in augmented analytics - which relies heavily on AI and ML- as well, as organizations require tools that are free of biases and meet regulatory compliances. Responsible AI practices build trust. They include clear documentation of AI models, continuous monitoring, and repetitive testing. Ethical and responsible AI practices in BI must be at the forefront as the technology develops and expands. 

Enhanced Collaboration & Data Literacy

The growing adoption of augmented analytics corresponds with the need to enhance data literacy and collaboration in business intelligence. While augmented analytics simplifies drawing insights from complex data for business users with little technical expertise, improving data literacy - the ability to read, write, and communicate data in context - has become critical to fostering a data-driven culture and enhancing collaboration. Augmented analytics tools allow users to share insights, annotate reports, and collaborate on projects. Promoting data literacy helps employees augment AI capabilities with creativity and critical thinking, enabling enterprises to maximize the value of data and drive innovation.

Customization & Personalization

Customization in BI is not a new concept, and the customization and personalization trends in BI extend to augmented analytics as well. As technology becomes more sophisticated, business users will be able to tailor the analytics process to their specific needs and preferences, enhancing productivity to a much larger extent. Personalization in BI offers users a sense of satisfaction and comfort. Augmented analytics includes customized data visualization, user-specific anomaly detection, personalized recommendations, and adaptive learning algorithms to adapt behavior. 

Cloud Adoption & Scalability

With most enterprises working on cloud-based systems, it is no surprise that cloud adoption for BI, significantly augmented analytics solutions, is accelerating. Scalability in BI is a prime requirement for organizations and is one of the driving forces behind cloud adoption, flexibility, and cost efficiency. Cloud adoption and scalability in business intelligence solutions facilitate collaboration and provide access to the latest analytical tools and features. As more organizations migrate to the cloud, the availability and sophistication of augmented analytics tools will continue to grow.

The Role of Automation

The role of automation in business intelligence advancements continues to evolve. Where augmented analytics is concerned, it is one of its key features. It refers to using ML to build and refine predictive models that automate routine tasks across the data analytics lifecycle - from data ingestion and preparation to model building and deployment - reducing the manual effort required.  Automation in BI has significantly helped accelerate decision-making and improve operations. With the evolution of automated business intelligence, augmented analytics tools will become more sophisticated, further simplifying the data analytics process. 

Step Into a New Era with Augmatica

Let’s look at how Augmented analytics is changing business intelligence, and why choosing an augmented BI platform will significantly impact organizations moving forward. Augmatica from AirQuery is designed to seamlessly integrate AI, ML, and human expertise. It empowers enterprises by solving business-specific problems accurately and efficiently. By adopting AI to augment BI processes, Augmatica creates customized BI solutions that meet specific goals and propel organizations forward. 

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The Future Of BI

The future of augmented analytics is bright, with transformative trends and innovations set to redefine how organizations leverage data. The promise of scalable BI solutions, automation, BI customization, user-friendly interfaces, and data democratization, among others, is and will continue to render it invaluable to enterprise growth. As organizations embrace augmented analytics, they will unlock new opportunities for growth, efficiency, and innovation.

Step into this new era of business intelligence with us. Explore Augmatica and its features and applications, and experience its transformative power firsthand with a demo.