The Benefits of Low-Code, No-Code in Augmented Analytics!

What Are the Advantages of Low-Code, No-Code Platform in Augmented Analytics Solutions?

According to some estimates, the rise of low-code, no-code and AI in analytics has increased access to augmented analytics to end-users by 36% to 56%. In fact, Gartner predicts that 75% of new global software solutions will incorporate a low-code approach.

In the analytics software market, the primary driver of this growth is the advent of solutions that can be quickly modified and upgraded to address new requirements and user needs. The creation of no-code and low-code apps allows for simple foundations and construction to analyze data without customization or programming or data science skills supports both developers, data scientists and power users of analytics by providing tools to simply and easily create complex components.

‘When considering an augmented analytics solution, prospective users should carefully review the foundation and technology of the analytical software. The incorporation of new technologies and capabilities will drive current and future user adoption and the successful implementation of analytics within the business user community.’

The organization can leverage and change data workflows, reports, dashboards and predictive models without extensive coding or time investment. While Low-Code development enables organizations to build apps with minimal coding, No-Code utilizes a suite of tools, scripts and components to allow swift construction of apps with very limited coding or user interface (UI) based configurations. Both of these approaches enable a development environment that is agile, and can quickly respond to the changing needs of users, customers and the organization.

With this approach, users enjoy access to data, models, charts, gauges, tables, and grids that satisfy their current needs, and these can be easily modified as the organization grows and changes, and the user requirements evolve.

The Low-Code, No-Code Approach to Augmented Analytics

There are numerous benefits and advantages to incorporating low-code, no-code into an analytical environment, and these benefits provide support for developers, data scientists and for power business users.

  • Supports Complex Data Extraction, Transformation and Loading (ETL) and Data Preparation Workflows Throughout the Data Pipeline
  • Enables Complex Data Transformation and Data Cleansing Functions
  • Offers Rapid Predictive Modeling Hypothesis and Prototyping
  • Allows Quick, Easy Construction of Custom Expressions
  • Enables User Adoption of Self-Serve Analytics and the Citizen Data Scientist Culture
  • Requires No Professional Programming or Scripting Experience – Power Users Can Perform Complex Tasks Without Assistance
  • Supports Data Democratization and Data Literacy
  • Allows for Rapid Development of Various Analytics Components e.g., Datasets, Dashboards, Rports and Models
  • Ensures Agility and Speed of Upgrades
  • Provides a Cost-Effective Solution with Personalization for Organizations
  • Offers Flexible Integration and Data Management
  • Reduces Cost
  • Improves Collaboration and Productivity
  • Improves Return on investment (ROI) and Total Cost of Ownership (TCO).

‘Gartner predicts that 75% of new global software solutions will incorporate a low-code approach.’

When considering an augmented analytics solution, prospective users should carefully review the foundation and technology of the analytical software. The incorporation of new technologies and capabilities will drive current and future user adoption and the successful implementation of analytics within the business user community. Technologies and techniques like low-code, no-code, artificial intelligence (AI), and embedded business intelligence (BI) to provide access to analytics from within enterprise applications, will support data democratization, data literacy and fact-based decision-making within the enterprise.

Smarten  Augmented Analytics with low-code, no-code technology will support your team with tools that are intuitive and easy to use and will encourage user adoption. Leverage the essential components of the Smarten Technology foundation, and improve decision-making and outcomes. Explore the potential and capabilities of the Smarten Cloud software-as-a-service (SaaS) product with its low-code, no-code foundation and seamless functionality.

Original Post : The Low-Code, No-Code Approach to Augmented Analytics!

Use Smart Data Visualization to Improve Decisions!

Smart Data Visualization and Personalized Dashboards Improve Data Insight and Team Collaboration!

Augmented Analytics was designed to remove the barriers erected by the traditional business intelligence and analytics solutions. In order to achieve data democratization and improve data literacy among team members within an enterprise, the organization must provide simple, easy-to-understand solutions that display analytical results in a way that is meaningful and intuitive.

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.

How Can I Get My Business Users to Adopt Augmented Analytics?

Drive User Adoption with Embedded BI and Single Sign-On Convenience!

All of your business users have a favorite software application – an app they value because it helps them do their job more easily, or helps them get crucial information. These are the applications they have learned and they are used to leveraging them on a day-to-day basis to perform tasks. When you introduce augmented analytics into your business environment, one of the most critical factors is whether you can expect user adoption. Finding and implementing the right augmented analytics solution is just the first step. If you can’t get your users to USE the application, your return on investment (ROI) will be poor and your total cost of ownership (TCO) will be high.

Embedded BI Improves User Adoption of Enterprise Apps!

How Embedded BI Can Add Value and Improve ROI for Enterprise Apps!

No matter your reason for investing in that business application, the investment was meant to improve the business, to make team members more productive, to act as a repository for important business data and to somehow improve the bottom line. But, the effectiveness and success of a software solution depends on more than its features and functionality. Yes, one must consider its ease of use too, but that’s not the point of our discussion today.

Increase Team Member Value with Augmented Analytics!

Make the Most of Your Team Member Skills with Augmented Analytics!

Every business owner and manager understands the problem of limited resources. Today, you have fewer team members and you must do more to compete in the market. To enhance productivity and collaboration and ensure that every team member is making better decisions, it is wise to implement augmented analytics within your organization.

Using Predictive Analytics to Understand Your Business Future!

Can Predictive Analytics REALLY Help My Business During These Uncertain Times?

How accurate is predictive analytics? Is it worth using for my business? How can forecasting and prediction help me in such an uncertain environment? These are all valid questions and they are they are questions your business (and your fellow business owners) must grapple with to understand the value of planning and analytical tools.

Ease of Use for Augmented Analytics is Key!

Want to Succeed with Citizen Data Scientists? Choose Simple Augmented Analytics!

Gartner has placed an increased focus on augmented analytics and solutions that support data democratization and business user transformation to the Citizen Data Scientist role. It predicts that those organizations that engage in Citizen Data Scientist initiatives will outperform businesses that do not take this approach and they will be more competitive and better prepared, by increasing productivity, optimizing resources and making better decisions. As your business competitors embrace this evolution, your organization must seriously commit to the Citizen Data Scientist concept and to the Augmented Analytics solution approach that will support the Citizen Data Scientist.