The complexity, dynamism and ever-increasing volume of data accumulated every day by companies represent a challenge for those who have to make quick and real-time decisions based on their data.
Traditional Business Intelligence (BI) solutions for Data Analytics are no longer sufficient to accurately process such amounts of complex data, due to the difficulties associated with the long times of data preparation, their extraction, management, and understanding .
Being able to identify, process and understand data and take the most appropriate decisions and actions is an increasingly difficult task to perform manually; with the consequence that important decisions may not be entirely data driven and rely too much on instinct.
The need to keep up with fast-growing data is increasingly pressing, and this is where solutions like Augmented Analytics come into play.
Today, identifying, managing and understanding data is made faster and easier by the use of automation, algorithms and natural language features that improve the analysis steps.
What is Augmented Analytics?
Augmented Analytics is the use of technologies such as Artificial Intelligence (AI), Machine Learning, and Natural Language Processing (NLP) to transform the way data analytics can be built, used and shared. Augmented Analytics tools can transform the process of preparing, discovering and explaining data and open up new ways of exploring and interpreting data.
The use of Augmented Analytics, a term coined in 2017 by the research firm Gartner, as part of the data analysis process – preparing and collecting data, generating and explaining insights – not only helps to explore, analyze , understand and better act on data, but also to transform and automate the use of data for all types of users. Augmented Analytics makes data, insights, predictions and possible actions to be taken accessible and comprehensible to more people, even non-technical people, at all company levels.
The Augmented Analytics approach is designed around the automation of analytics processes that were previously typically found in specialized data science and machine learning (DSML) products. These were generally IT-driven and aimed at specialists, which made BI tools largely inaccessible to the broader corporate population.
In recent years, the proliferation of visualization-based data detection tools has seen artificial intelligence and machine learning capabilities increasingly incorporated directly into analytics and BI platforms to specifically assist the business user , and not just data experts. This made it possible to bring together data, analysis and DSML, where they were once considered and managed separately.
Conversational Analytics: explore your data by talking with a Virtual Advisor
Advances in artificial intelligence and natural language processing systems have simplified the way data is accessed. As part of today’s business intelligence applications, the user interface allows users at all levels of the business to explore and interact with data by querying in natural language using voice or text. This allows you to obtain immediate and intuitive answers and to access data at any place and time from the device you prefer, without having to manually search for them in reports and dashboards, without having to produce custom reports, and without the need for technical knowledge of the BI tools.
Responsa Virtual Advisor for Conversational BI
Responsa’s ChatBot for Conversational BI allows you to access data quickly and easily, to receive personalized reports and alerts, to be guided in the exploration of data, all through a dialogue in natural language. The system leverages context within the conversation to understand the intent of the user’s query and encourage dialogue, creating a natural conversational experience. Charting, analysis and calculations are generated automatically, where previously they would have required lengthy manual procedures.
The benefits of automated insights, through machine learning and natural language for query and exploration, not only make it easier for users or customers to analyze and act on data, but provide a competitive advantage for businesses. that they are thus able to make informed decisions with greater speed. According to research firm Forrester, the timely adoption of BI solutions integrated with Augmented Analytics technologies will be a key factor in determining the difference between industry leaders and companies that risk falling behind. BI and Augmented Analytics tools are an integral part of companies’ digital transformation strategy, and an essential part of their future.
Read the complete Whitepaper on Augmented Analytics and Conversational BI!