Augmented Analytics: what it is
According to Gartner’s definition, Augmented Analytics (or Augmented Analytics) is “the use of enabling technologies such as machine learning (ML) and artificial intelligence (AI) to support data preparation, generation and interpretation of detailed information, to improve the way people explore and analyze data through business intelligence platforms”.
In short, Augmented Analysis helps human beings to interact with data: it automates the most technical processes to simplify access to information, allowing even non-IT figures to perform deep analysis and discover new connections in a simple and “natural”.
Traditional Analysis vs Augmented Analysis
Augmented Analysis, therefore, changes the way analytics platforms interact with data and extract information. Self-learning (ML) and Natural Language Processing (NLP) systems move the analysis process from a horizontal plane (kpi identification, data preparation, dashboard construction, interpretation, action) to a circular plane, in which analysis procedures are enriched and automated to find new relationships, provide business insights and at the same time generate new knowledge to be put back into circulation to improve the analysis process itself.
Advanced Analytics already introduced the concept of advanced analysis based on ML and AI technologies to obtain predictive and prescriptive analysis, thanks to Augmented Analytics platforms the whole process becomes easier to govern: Key management figures can explore and analyze data in complete autonomy through elementary and intuitive interrogation commands (e.g. via a voice command), being guided by prediction suggestions that open unexplored visions.
The information obtained is shown in the most suitable format for use, enriched and integrated by different sources, offering endless possibilities for analysis, establishing new connections, suggesting unreleased correlations and revealing otherwise unknown insights.
Augmented Analytics tools
Companies that want to introduce the use of Augmented Analytics need tools and enabling platforms:
- A Cloud platform that allows the management of Big Data in a short time and with immediate results.
- Democratization of the data as a basis for making important decisions.
- Integration with analytics tools that allow data manipulation and the use of artificial intelligence (such as Microsoft Azure Synapse).
- Enhanced analytics platforms manageable even without the ability to write code, via simple and natural query commands, to allow managers to focus exclusively on the best decisions for their business (like Microsoft ,Qlik and Dataiku)
Benefits of Augmented Analytics with Blue BI
Blue BI solutions allow companies to introduce Augmented Analysis as a tool to obtain valuable and new information, useful to make the best decisions and gain a competitive advantage against their competitors.
The Augmented Analysis:
- It allows an agile and fast management of the data (and the mole will be always greater), automating the processes of preparation of the data thanks to the Machine Learning.
- Speed up and refine the complex analysis process, reducing dependence on data scientists.
- It allows to obtain immediate insights, often unpublished depth , allowing a better understanding of the present and future context.
All this translates into the ability for companies to react promptly to changes, but also in a reduction in costs and zero waste, for example, having a greater understanding of the preferences of their customers to offer customized products.