Tag: Augmented Analytics

Smarten Support Portal Updates – March – 2026!

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March 26, 2026

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. General : Custom Columns (UDDC) : UDDC Functions
  2. Data Sources : Improve data extraction performance from database data source
  3. Schedulers : Delivery and Publishing : Working with E-mail Delivery and Publishing Task

Predictive Use cases

  1. Assisted predictive modelling : Medical Cost Prediction Using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : Independent Sample T-test Using Smarten Augmented Analytics

Forum Topics

  1. Graphs : Global Variable : How can I plot the dynamic graph based on measure selected from the list of measures
  2. Embedded / API Integration : How to rebuild cubes/ datasets through API call?

Manuals and Technical Guides

  1. Smarten Administrator Manual
  2. Smarten Concept Manual SnapShot
  3. Smarten Securing Application Server

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post : Smarten Support Portal Updates – March – 2026!

What I’ve Learned About Empowering Non-Technical Users With Predictive Tools

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March 23, 2026

How Predictive Tools Empower Non-Technical Users

Many organizations collect large amounts of information but struggle to turn it into decisions that feel clear and reliable. Smarten approaches this problem from a human POV. Instead of assuming Analytics belongs to specialists, it treats prediction as a shared responsibility across teams. This shift changes how people think, how they ask questions, and how decisions are made inside organizations.

Read as I talk about the power Non-Technical Users hold in business decision-making and how tools like Smarten pave the way for future-ready analytics workflows.

The Potential of the Citizen Data Scientist Approach and Augmented Analytics
 Download the White Paper

Why Non-Technical Users Need Predictive Tools Just as Much

I have encountered several instances where business users created Predictive Models without a formal background in data science. These users were not guessing or experimenting blindly. They were applying years of domain experience through a system that respected how they already think. The right predictive tools guided them step by step, allowing them to focus on meaning rather than mechanics.

What stood out most in these stories was how quickly confidence developed. When people understand what a model is doing, they are more willing to rely on it and improve it. Users did not wait for validation from technical teams before acting. They could see how inputs affected outcomes and why certain patterns appeared. This visibility removed fear and hesitation.

Modern CDS Tools create that structure by guiding decisions without dictating them. This balance allows non-technical users to succeed without feeling overwhelmed or constrained.

Why Explainability Is Not Optional

Predictive models fail when people cannot explain them to others. A result that cannot be explained cannot be defended, trusted, or improved. When explainability becomes a requirement and not an extra feature, every outcome gets connected to visible drivers that users can understand in simple language. This clarity changes how people interact with predictions.

When explainability is built in, conversations improve across teams. Sales, finance, and operations can discuss the same model without confusion. People focus on what changed and why it matters. Meetings become more productive because participants share understanding instead of debating definitions, which reduces friction and speeds up decision-making.

Explainability also protects organizations from silent mistakes. When assumptions are visible, they can be questioned early. Citizen data scientists can think critically rather than accept results without reflection, creating a culture where Analytics supports thinking instead of replacing it.

How CDS Bridges the Skill Gap

Many analytics tools expect Non-Technical Users to adapt to complex systems. CDS tools take the opposite approach by adapting the system to the user. They democratize data, allowing organizations to combine analysis with the professional knowledge and domain skills of the individual. This enables a better understanding of trends, patterns, issues, and opportunities, and improves business agility and efficiency in the long run.

Here’s how CDS bridges the skills gap:

  • Designed around familiar business steps: CDS tools are designed around familiar business steps that feel logical and intuitive; users are guided through the modeling process without needing to learn new technical concepts.
  • Provides context at every step: CDS recognizes that skill gaps are simply differences in training and focus. It bridges those gaps by providing context at every step. Users know what they are doing and why it matters. This understanding helps them make better choices and avoid common mistakes.
  • Keeps workflows clear and structured: CDS allows users to build reliable models without shortcuts. Validation checks help users see weaknesses early without discouraging exploration. This balance encourages learning while maintaining responsibility. Over time, users grow more capable and confident in their analytical thinking.

What Future-Ready Analytics Actually Looks Like

Future-ready analytics is not about complexity or volume but about flexibility, clarity, and learning. Today’s users expect models to change as conditions change, and that’s what modern CDS tools like Smarten do. They help decision makers stay connected to data and focus on understanding direction and impact.

Smarten CDS gradually integrates into existing processes. It empowers business users to take responsibility for insights instead of waiting for reports, while allowing analysts to focus on deeper problems instead of routine requests. This redistribution of effort increases overall capacity without increasing headcount.

Over time, data becomes a shared resource rather than a specialized asset. Decisions feel deliberate because people understand the reasoning behind them. Confidence grows from clarity, and organizations can act decisively even when outcomes are uncertain.

FAQs

1. What does Smarten CDS help users do?

Smarten CDS helps business users build and understand predictive models without needing technical skills.

2. Why is explainability important?

Explainability allows users to trust results, defend decisions, and improve models over time.

3. How does CDS bridge skill gaps between business users and advanced analytics?

CDS bridges skill gaps by guiding business users through predictive modeling using familiar steps, clear explanations, and built-in validation, allowing them to apply domain knowledge without needing technical training.

Original Post: What I’ve Learned About Empowering Non-Technical Users With Predictive Tools!

Assessing Ten Years of the Citizen Data Scientist Approach

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March 3, 2026

Ten Years Into the Citizen Data Scientist Revolution

It has been a decade since Gartner first defined the role of a Citizen Data Scientist. In 2018, Forbes published an article, referencing Gartner’s updated analysis of the role and stating that, ‘And the best part is, mid-market organizations already have potential citizen data scientists on their staff—it’s just a matter of tapping those with potential and interest in the work, and cultivating an analytical mindset across their workforce. Then, those who serve as citizen data scientists can grow their own skillsets, all the while being active players in their companies’ ability to tap the value of big data and drive transformation.’

‘It is likely that the Citizen Data Scientist role will continue to evolve, and it is important that the enterprise facilitate collaboration and knowledge sharing and build a sustainable technology environment with appropriate policies.’

A lot has happened in the past decade, and today the role of Citizen Data Scientist is no longer new. So, what has changed in the ensuing years? How as this role changed? Has the average enterprise embraced the role and made the technological and cultural changes required to truly support this approach?

A Decade of Citizen Data Scientist Evolution

Here are a few of the ways in which the Citizen Data Scientist approach has evolved within the organization.

  • In the early days of the Citizen Data Scientist approach, Data Scientists often worried that their positions would become obsolete. Nothing can be further from the truth. The use of Data Scientists to perform strategic analytics and to refine analysis performed and submitted by business users has kept Data Scientists busy.
  • The evolution of augmented analytics and self-serve tools has expanded analytical capacity, the speed at which business users can gather and analyze data and the dependability of the outcomes. Drag and drop capabilities, machine learning and, more recently, artificial intelligence (AI) have significantly improved tools and made it easier and more desirable for business users to dive into analytics and make it part of their day-to-day role.
  • As cloud-based access expanded, the enterprise leveraged improved access and data platforms to enable collaboration and create multi-disciplinary teams and power user roles that would further encourage the use of these tools across the enterprise. Methods and guidelines improved data literacy and encouraged business user expertise creating more confident Citizen Data Scientists and supporting the role as a mainstream concept.

Every enterprise must do more with less, increase productivity and reduce missteps in order to remain competitive. So, it is likely that the Citizen Data Scientist role will continue to evolve, and it is important that the enterprise facilitate collaboration and knowledge sharing and build a sustainable technology environment with appropriate policies for user access, upgraded technology and data analytics tools and standards and regulations to govern and manage risk and maintain alignment with enterprise strategies and goals.

‘Those who serve as citizen data scientists can grow their own skillsets, all the while being active players in their companies’ ability to tap the value of big data and drive transformation.’

If you wish to know more about the Citizen Data Scientist approach and how augmented analytics tools and your industry and market knowledge can position you for success in this role, Contact Us today to find out how our team can help you to improve business results and increase team collaboration, data literacy, productivity and competitive advantage. Get started today with our self-paced FREE Online Citizen Data Scientist course.

Original Post : Assessing Ten Years of the Citizen Data Scientist Approach!

Conversational AI and NLP Expand Access to Analytics

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February 25, 2026

Users LOVE Conversational AI and Intuitive Analytics

Forbes Reports that Conversational AI is making autonomous agents capable of completing end-to-end workflows, so much so that Deloitte projects that 25% of businesses using GenAI will deploy AI agents in 2025 (growing to 50% in 2027).

Analytics solutions represents an ever-expending segment for conversational AI for features and function, and the use of Natural Language Processing (NLP) and Conversational Artificial Intelligence will continue to impact the industry as end users demand easier, more intuitive ways to prepare, analyze, share and report on data.

When we consider this evolving technology, and how it will continue to affect BI solutions and augmented analytics software, one thing is clear. The average enterprise and its users will push for more intuitive products and services, for ease-of-use and improved productivity, improved user adoption, affordability, the flexibility to grow and change with new technology and with business markets.

While we cannot make specific predictions about the evolution of AI and NLP, we can predict that businesses and users will push software vendors and technology companies to provide simpler tools, better, more accurate insight and results and automated features that provide users with alerts, suggestions and support to make their jobs easier and improve results.

Incorporating conversation AI bots and NLP within BI tools will allow users to monitor and manage results more easily and optimize their time by focusing on other, more crucial tasks.

When the organization invests in new or upgraded self-serve analytical tools, it must first ensure that users will adopt these tools and that the features and analytics provided will result in increased productivity and collaboration and resource optimization. When the enterprise selects BI tools with Conversational AI and NLP features, it can achieve all of these goals and assure a good Return on Investment (ROI) and Total Cost of Ownership (TCO).

As Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies evolve, these technologies will be applied within advanced analytics, self-serve analytics and business intelligence (BI) tools to further improve features, provide better, faster insight and clearer, more concise results and optimize human resources and productivity.

Businesses and Users Push for More as Conversational AI and NLP Expands Access to Analytics

The future of AI and NLP in BI tools will support:

  • Processing large volumes of unstructured data (text, speech, written) to produce actionable insight and reports.
  • Automatically identifying trends, patterns and sentiments to alert users of changes and shifts that may affect goals.
  • Supporting decisions with conversational business intelligence to allow team members and executives to interact through NLP.
  • Real-time analytics to reveal sentiment, emotion, context and tone in customer interaction.
  • Automated reporting to save time and analyze complex data.
  • External data integration to analyze markets, social media, financial markets, investments, and other aspects of external data that will affect businesses.
  • Understanding and responding to voice commands, analyzing and working with contextual information, predicting user needs.
  • Eliminating static reporting, using conversational, dynamic analytics that can leverage predictive and analytical algorithms to produce results.

Contact Us to find out more about how your business can incorporate Artificial Intelligence (AI), natural language processing (NLP) and machine learning into your products, your business processes and your Digital Transformation (Dx) initiatives. Our AI-Enabled Advanced Analytics Solutions and Products And Services can help you achieve your vision with affordable, dependable technology. Explore our white paper ‘Conversational AI And NLP Analytics Reduces The Dependence And Usage Of Traditional BI Tools, And Improves User Adoption And Data Democratization,’ and our free articles about Agentic AI: ‘The New Age Of AI: Agentic AI’, and ‘What Is Agentic AI And Why Should I Consider It For Apps?’

Original Post : Conversational AI and NLP Expand Access to Analytics!

Mobile BI Tools Are Not Just Nice to Have, They Are A Necessity

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February 18, 2026

Mobile BI Tools Support Users and a Competitive Strategy

No matter the size of your business or the industry or market in which you compete, the importance of business intelligence (BI) and self-serve augmented analytics is no longer in question. Nearly every business is using some form of business intelligence today and, if your business is not, you are already behind the competition!

When we consider the growth of this important solution market, we find that the mobile market for business intelligence solutions is growing exponentially and that is not surprising. Today’s workforce is mobile and, even where employees work onsite, their work will take them away from a desk and into a manufacturing or production environment, or perhaps within the walls of a hospital, a university, a retail store, etc.

‘The shift to mobile BI tools is not just a matter of convenience. It is crucial that your team remain informed and that they have the tools they need to collaborate, share and present data, whether they are on the road, with a client or in an airport. This flexibility reflects the evolving business environment and the need for agility.’

A recent Mordor Intelligence Report revealed that the 2025 market size for mobile business intelligence was 19.33 billion USD and that the 2030 projected market size is 55.56 billion USD.

While many businesses rely solely on BI solutions and look to their team to implement and use these solutions, the growth of business intelligence services is also of note. The complexity of technology landscapes, in-house vs. cloud implementations, security and regulatory and industry compliance, as well as artificial intelligence (AI) add-ons and integration have created an environment that is often best served by expert services.

These services can help businesses to personalize and customize their approach and to provide meaningful mobile BI tools, embedded BI for familiar best-of-breed and legacy software solutions and other tools that will support end users and make the team more productive.

User accessibility and ease-of-use are paramount considerations. The shift to mobile BI tools is not just a matter of convenience. It is crucial that your team remain informed and that they have the tools they need to collaborate, share and present data, whether they are on the road, with a client or in an airport. This flexibility reflects the evolving business environment and the need for agility.

Whether you are a sales manager, a media executive, a healthcare provider or a business analyst, it is important to have access to a suite of BI tools that will help you gather and analyze business data using mobile devices.

Why is Mobile Business Intelligence Important for My Business in Today’s Work Environment?

The team needs interactive data tools and tools that enable sharing and collaboration, reporting and sophisticated analytics – all with dependable security. Users should also be able to tailor their mobile BI tools to suit their role and preferences and integrate the use of these tools within workflow to foster a data-driven, fact-based culture.

‘Today’s workforce is mobile and, even where employees work onsite, their work will take them away from a desk and into a manufacturing or production environment, or perhaps within the walls of a hospital, a university, a retail store, etc.’

Look for a mobile BI tool that will:

  • Support a native mobile environment for Android and iOS, with an intuitive user experience (Ux).
  • Provide access rights defined at the server level with appropriate security and privacy at all levels.
  • Accommodate hosting within the IT infrastructure, on-premises or in public or private cloud environs.
  • Provide users with access to dashboards, reports, and clickless analytics with a natural language processing (NLP) search function.
  • Provide expertise and services that are appropriate for the needs of your organization.

If you want to support your business user team and provide a foundation for BI tools that will better serve your team and your customers, explore Smarten Mobile BI benefits and features, with powerful functionality and access for your business users including out-of-the-box Mobile BI and advanced analytics for every team member. For more information on Mobile BI and Augmented Analytics, read our article, ‘Mobile BI Business Use Provides Real Advantages,’ and take a moment to watch and listen to this informative webinar, ‘Smarten Mobile BI.’

Original Post : Mobile BI Tools Are Not Just Nice to Have, They Are A Necessity!

Case Study : Augmented Analytics for India Electrical Sector Organization Focused on Testing, R&D and Certification

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February 10, 2026

The Client is a premier not-for-profit institution in India, established as an independent organization with strong government and industry backing, and widely recognized for leadership in the electrical power testing, certification, inspection, and research domain.

Continue reading “Case Study : Augmented Analytics for India Electrical Sector Organization Focused on Testing, R&D and Certification”

Smarten Support Portal Updates – January – 2026!

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February 5, 2026

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Datasets & Cubes : Migration from Cube to Dataset
  2. Data Sources : Improving performance for fetching data from the database
  3. Crosstab : Spot the Gross Sales highlighters

Predictive Use cases

  1. Assisted predictive modelling : Classification : Customer Churn model using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : Independent Sample T-test Using Smarten Augmented Analytics

Forum Topics

  1. Dashboards : How to improve the dashboard loading time in Smarten?
  2. Others : General : How to add SSL certificate to the Smarten BI Portal?

Manuals and Technical Guides

  1. Smarten Concept Manual SmartenInsight
  2. Smarten Working with Real time data
  3. Smarten Working with On-Premise Gateway

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post : Smarten Support Portal Updates – January – 2026!

Case Study : Augmented Analytics for India-Based Municipal Corporation to Support Smart City Initiative

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January 30, 2026

The Client is one of the largest municipal corporations in India, and is responsible for delivering essential civic services, i.e., water supply, sewage treatment, solid waste management, road infrastructure, public health, education, and environmental programs for an urban population of over 3.1 million citizens.

Continue reading “Case Study : Augmented Analytics for India-Based Municipal Corporation to Support Smart City Initiative”

Embedded BI: What Makes a User Adopt BI Tools?

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January 7, 2026

Embedded BI: Productivity vs. User Needs

Executives and managers may want to believe that staff and team members will always embrace and adopt new tools and processes just because they are told that these tools or processes will help the company. But this belief does not take into the consideration the pressures, stress and day-to-day realities a team member faces.

While the best of our team members may truly wish to support the company and have the best interests of the business in mind, even THEY are subject to the pressures of getting the job done, dealing with conflicting opinions and direction from other team members and from managers and just getting through the day!

When an IT team, executives and managers come together to choose the right business intelligence (BI), and augmented analytics tools, they often fail to consider ease-of-use, existing business processes and technology and user and team member skills and preferences.

‘When considering BI tools and self-serve analytics, it is wise to consider embedded BI solutions.’

As an executive or manager, your primary goal is to support the objectives of the business and to get the most out of the skills, knowledge and time of your team members. But, if you don’t provide the right tools and acknowledge the issues that impact productivity and team satisfaction, you will not achieve your goals.

A recent Forbes Article includes statistics from studies that include surveys of employees and the results are eye-opening:

  • 40% of those surveyed feel their daily responsibilities have changed to a large extent within the past year.
  • 78% rank flexibility as key to choosing a job.

So, if you want to recruit and keep the best team members, you need to provide the most efficient, productive, intuitive technology and tools.

When Considering BI Tools and Productivity, Don’t Forget the Needs of Your Team

When considering BI tools and self-serve analytics, it is wise to consider embedded BI solutions. These solutions allow your team to leverage familiar, existing software and solutions with integrated analytics. There is no need to migrate or move information from one system to another in order to perform analysis, and your team can use a single sign-on to access popular software and work in a way that is familiar and meaningful to them – all while having access to intuitive, self-serve BI tools that enable quick, clear analysis of data.

Benefits of Embedded BI

  • Improved user adoption
  • Reduced TCO
  • Improved ROI
  • Integration APIs provide intuitive, self-serve BI tools from within enterprise applications and public websites
  • Users have access to facts, data and business insight

When surveyed, businesses using embedded BI reported the following results:

  • 67% of companies say time spent in their applications increased after they embedded analytics
  • 93% of application teams say embedded analytics improves their user experience
‘When an IT team, executives and managers come together to choose the right business intelligence (BI), and augmented analytics tools, they often fail to consider ease-of-use, existing business processes and technology and user and team member skills and preferences.’

If an enterprise includes team member satisfaction and user adoption concerns when it considers Business Intelligence (BI) and Augmented Analytics requirements, it can address productivity, employee optimization and user satisfaction. Adding Embedded BI to the technology landscape will ensure adoption of crucial software and business processes to improve business results and allow team members to leverage data, and capitalize on technology investment, while improving the quality of decisions and making the most of the knowledge, skills and time of its employees.

You can find out more about the Smarten Embedded BI And Integration APIs solution and add powerful functionality and access to existing ERP, SCM, HRMS, CRM or any other products. Provide analytics capabilities within existing products without major Investment. Your business users and your customers will appreciate the ease-of-use and access and you will gain a competitive advantage. Read our White Paper: ‘Making The Case For Embedded BI And Analytics.’

Original Post : Embedded BI: What Makes a User Adopt BI Tools?

White Paper – Conversational AI and NLP Analytics Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization

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January 7, 2026
White Paper – Conversational AI and NLP Analytics Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization!

Conversational AI and NLP Analytics
Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization

The incorporation of Artificial Intelligence (AI) and Natural Language processing (NLP) in existing business intelligence and self-serve analytics tools has had (and will continue to have) a profound influence on ease-of-use, on user adoption and on the democratization of data across the enterprise, and the use of Conversational AI and NLP is rapidly changing the face of BI tools and business user and organizational expectations.

Download White Paper