AI In Analytics: Today and Tomorrow!

Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.

Augmented Analytics with Auto Insights Support Business Users!

Augmented Analytics with ALL Gartner Classified Essential Components AND Auto Insights Too!

Gartner classifies essential augmented analytical components and technologies as follows:

  • Machine learning
  • Natural Language generation and natural language processing
  • Automation

‘Combine the three essential components specified by Gartner to create a comprehensive augmented analytics solution with refined auto insights and clear, concise results, the enterprise and its business users can perform complex data analytics and share analysis across the organization in a self-serve, mobile environment.’

While none of these is considered ‘new’ in the market today, the combination of essential components and the leveraging of new technologies and features is key to keeping augmented analytics fresh and usable for the average business user.

One such feature that users will look to for quick results and clear, concise decision support is the concept of auto insights.

Auto Insights Adds Clarity and Ease-of-Use to Augmented Analytics

Search Analytics is evolving at a rapid pace, and the concept of auto insights builds on the foundation of assisted predictive modeling and Clickless Analytics features, taking natural language processing (NLP) search analytics and predictive modeling to the next level.

Auto Insights frees business users and reduces the time and skills required to produce accurate, clear results, quickly and dependably, using machine learning that frees the business user to collect and analyze data with the guided assistance of a ‘smart’ solution.

Using this approach, business users will no longer have to select data columns or analysis techniques such as classification or clustering. Instead, the user will simply select the dataset to be analyzed. That’s it!. The system interprets the dataset, selects important columns of data, analyzes type and variety and other parameters and then uses intelligent machine learning to automatically apply the best algorithm and analytical technique and provide data insights.

Users can easily understand data and apply correlation, classification, regression, or forecasting, or other appropriate technique(s) based on the data the user wishes to analyze. Results are displayed using visualization types that provide the best fit for the data, and the interpretation is presented in simple natural language. This seamless, intuitive process enables business users to quickly and easily select and analyze data without guesswork or advanced skills.

By combining the three essential components specified by Gartner to create a comprehensive augmented analytics solution with refined insights and clear, concise results, the enterprise and its business users can perform complex data analytics and share analysis across the organization in a self-serve, mobile environment.

This approach provides support for sophisticated, advanced analytics and smart data visualization to automate the analysis process, so business users can simply point to a dataset and let the system do the rest.

‘The combination of essential components and the leveraging of new technologies and features is key to keeping augmented analytics fresh and usable for the average business user.’

Find out how Smarten Auto Insights can help your team and your organization. Leverage the essential components of Augmented Analytics, as defined by Gartner, and provide seamless, easy-to-use, sophisticated features and functionality to support your business users and transition your team members to Citizen Data Scientists.

Smarten Augmented Analytics Now Available on Mobile App!

Smarten is pleased to announce the launch of its Mobile Application for Smarten Augmented Analytics. This native app has a seamless user interface for a great user experience (UX). Smarten Mobile app is available for iOS and Android. Installation is easy.

Smarten Augmented Analytics Receives CERT-IN Certification for Its Products and Services!

Smarten announces the recent certification of its Smarten Augmented Analytics Software product by CERT-IN. CERT-IN, or the Indian Computer Emergency Response Team, is an India government-approved organization for upholding information technology (IT) security, and is a well-renowned application security standard, respected within the technology community. It was initiated in 2004 by the Department of Information Technology for implementing the provisions of the 2008 Information Technology Amendment Act. CERT-IN certification is provided by a CERT Empaneled Security Auditor following a detailed security audit to review all components of the organization network including websites, systems, applications, etc. After completion of the testing procedure, the certificate is provided to show that all requirements were met.

Smarten Announces Sentiment Analysis Capability Designed for Business Users!

Smarten is pleased to announce the addition of Sentiment Analysis features and functionality to its innovative, augmented analytics solution. Sentiment Analysis enables businesses with easy-to-use tools that provide insight into what customers, stakeholders and others are thinking, thereby allowing business teams to improve products and services.

The Important Components of Augmented Analytics!

AutoML, NLP and Clickless Analytics Come Together to Produce Auto Insights!

When it comes to the new world of analytics, the augmented analytics approach allows business users with no data science background to readily access and use analytics in an intuitive way. There are some important aspects of this approach, including auto machine learning, natural language processing (NLP) and intuitive search analytics.