Author: Kartik Patel

Why Integrate Artificial Intelligence in New Software or Apps

author_img
by |
October 1, 2026

How Can I Make the Most Out of AI in My Apps and Software?

The University of Cincinnati reports that at least 50% of businesses state that they use AI for at least two business functions.

If your business is considering a new software application, mobile app or website for consumer or business use, it is likely you are also considering how to incorporate Artificial Intelligence within that project. But, before you make that decision, there are a number of factors to include in your project review.

First, it is important to understand WHY you want to include AI in your project. The reasoning cannot simply be because AI is the new buzzword or the newest technology. Ask your team what they hope to accomplish with AI. What features or functionality can AI satisfy that are critical to your project success?

Once you have an idea of how AI might appropriately fit within your project, you will want to look at the various options and choices to carefully select the right technology, and the right place within the structure of the project where it would be best to implement this technology and these features.

Gartner specifies three ways in which AI is best considered for business use.
  • To defend the existing business from competitive inroads with incremental improvements to existing processes and workflows.
  • To extend the reach of the business in the market, adding customers or products, etc. by modifying processes to accelerate growth and profitability.
  • To upend the market or the business environment using AI to steer its business in a new direction, alter its business model or transform in ways that redefine the market.

When approaching the management team to gain approval for AI within your business or consumer app, it is important to look at the wide variety of reasons other businesses have taken this approach and the benefits they have achieved through the use of AI in mobile apps, on websites and in software solutions.

What Are the Benefits of AI Integration in Mobile Apps, Software and Websites?

Here are just a few examples:

Accuracy and Efficiency

Artificial Intelligence can reduce human error and speed results, thereby mitigating risk and completing tasks and processes quickly and without rework.

Productivity

Tasks and activities handled by AI features and functionality can free staff and team members to perform more strategic activities and allowing the organization to optimize staff skills and knowledge.

Revenue

Maybe you are using AI to refine and complete business processes or for data analytics or even to create code and streamline the software development process. Whatever your business need, you can accelerate projects and complete products more quickly to generate revenue. You can improve forecasting, sales and marketing, reduce fraud, and quickly create new products and services.

Agility

Businesses that employ AI find it easier to improve agility and to adapt to change more quickly. It is easier to recognize patterns and react to trends in customer buying behavior and needs and in resource planning.

Customer Satisfaction

Whether you are trying to increase self-serve for customers and make it easier for them to complete tasks, order products and get more information, or you want to personalize your approach to target specific customer needs and anticipate their requirements, AI can help you improve customer retention and satisfaction. Gartner reports that the most valuable AI use cases for customer service and support include human agent enablement, low-effort self-service, automating operations support and agentic AI.

These are just a few examples of the benefits of using AI in applications, software and technology products and projects.

Contact Us to find out more about our AI Technology Capabilities and Review our White Paper, ‘What Is AI And How Can It Help My Business?,’ and our Blog article, ‘Improve Apps and Software with Artificial Intelligence.’

Original Post: Why Integrate Artificial Intelligence in New Software or Apps?!

User Adoption of BI Tools Must Include a Value Metric

author_img
by |
September 1, 2026

BI Tool Adoption is Measured by Value to the Organization

You implemented a business intelligence (BI) solution, and your IT team, or perhaps your IT consultant, has given you the good news! According to all the evidence provided by user visits, session times and audit logs, your BI tools are a rousing success. But, before you celebrate your Return on Investment (ROI) and user adoption results, you should dig a little deeper.

A recent BuiltIn.com article, cited the 2025 Self-Service Business Intelligence study from Dresner Advisory Services, in which Dresner reported that user self-service BI tools ranked 11th out of 65 technologies as strategic to the adoption of BI, with 60% reporting that self-serve is critical or very important to the adoption of BI tools.

If you have already committed to self-serve business intelligence and augmented analytics, your management team probably agrees with these statistics.

But, can you really say that your users have adopted and are using BI solutions just because the reported user visits and audit logs say so?

The true definition of user adoption lies in the use of a solution to drive results and derive value. In order to accurately determine the value of the business intelligence solution and the real user adoption picture, you must look at how analytics is integrated within workflow and business processes, and how often analytical data is used in presentations in staff meetings, to justify a budget or pricing decision or a change to an existing strategy.

Are you users accessing the business intelligence solution on a daily basis? What features do they use most often and why do they find them helpful? What feedback do you have from users to indicate usage and satisfaction with the solution?

While audit logs, session times and login data can help you understand if the solution is in use, you need to understand the real benefits of the solution and establish measurable goals that provide metrics for user adoption. User adoption metrics reveal how, when and where users integration the solution within their daily workflow and indicate engagement and value to the user and to the organization.

So, when your IT team or IT consultant presents reports that capture audit logs, or session times or user visits, ask for more context. How are the users leveraging these tools today to change how they work? How do these modified processes improve the user’s daily tasks, collaboration, etc.? Does the use of BI tools improve results, ensure that there is less rework, or provide a clearer picture of where the issues, challenges and opportunities lie?
Audit Logs and User Visits Do NOT Reveal the Value of Self-Serve BI Tools or True User Adoption

Perhaps it might be easier to understand a simple audit log or user login vs. the real value of user adoption by comparing it to the purchase of a pair of new running shoes. The fact that the runner wears the new shoes every day does not tell you how the shoes improve results. Does the runner achieve a faster completion time? Does the runner find that they have less discomfort or muscle fatigue when they wear the new shoes? If they invested a significant amount of money in these new shoes, they will want measurable results!

When a business implements self-serve business intelligence (BI), they usually have promised results to the management team. Giving the management team an audit log is not going to prove the worth of the new solution. However, if the business can show real results and compare previous processes to new workflow to elaborate on time-to-market, mitigation of rework, etc., the user adoption metrics reveal not just the numbers, but the improved results.

Contact Us to find out more about the Benefits Of Augmented Analytics And BI Tools for your enterprise and how you can successfully implement this approach within your organization.

Original Post: User Adoption of BI Tools Must Include a Value Metric!

How Does AI Coding Affect the Software Industry and Programmers

author_img
by |
July 29, 2026

Is AI Coding a Required Skill in Software Development Today?

If this is the first time you are hearing about Artificial Intelligence (AI) and its impact on society, technology and development, then you have probably been living in the jungle or in outer space! When we consider the influence of AI on the world, the software industry and its career professionals are among the most profoundly impacted segments.

According to Medium, by Some Estimates, developers using AI tools can complete tasks 55% faster, with 85% reporting increased confidence in code quality, and it is estimated that AI-powered development could contribute $1.5 trillion USD to the global GDP by 2030.

When we consider these statistics and predictions, it is clear that AI has had (and will continue to have) a profound impact on software development and software programmers.

If you are working in the software development industry today, it is likely that you have worked on or are going to be asked to work on coding projects that include agentic AI tools like Cursor, Claude Code, GitHub, Copilot and others.

AI Agent Coding Does (and Will) Affect the Software Industry, Programmers and Developers

Not so long ago, AI was a tool to support and help programmers but, today, these tools can handle tasks for a developer and free them to perform other tasks. Programmers who have embraced AI technologies now consider AI a co-pilot, helping them navigate to the conclusion of a project, and quickly create sophisticated, complex code and features that are accurate and secure.

Today’s AI is less like a summer intern or a ‘gopher’ on a construction site, and more like a partner. It goes beyond ‘suggestions’ to consider the WHY, and bases its findings on large language models (LLMs) that digest, analyze and understand context and appropriateness.

But, before you become too concerned, it is important to consider the very real need for human intervention, programmer knowledge and insight and the ‘human’ factor. AI can, and will, offer a solution, and that solution may be appropriate and well-conceived, but human developers still need to review outcomes and use their knowledge and experience to decide whether a certain approach works or whether there is risk involved. Review, validation and editing are crucial, as is a human understanding of context and purpose.

As a programmer, that means you must understand how AI logic works and use your experience and training to ensure compliance, security and understanding of the goals and purpose of the project.

At the heart of software development excellence lies a team of people, processes and tools that support creativity, logic, structure and results. AI can build a structure, establish integration points, coral and analyze data and design a user interface (UI), but it is likely to miss some of the finer points and subtle aspects of security, error handling, accessibility, etc. AI lacks the human dedication, perseverance and work ethic and contextual experience. That’s where you come in!

As a human developer, working with AI, your ability to acquire the tools, learn their limitations and strengths, and then combine those with your own experience, knowledge of best practices and governance and guidance skills, will allow you to progress in your career while, at the same time, using tools and technologies that make your job easier and get the job done more quickly.

AI can help you optimize performance, identify patterns and address those appropriately, revise and simplify loops and clean up code. It can act as a tutor to suggest solutions and explain reasoning so that it is easier to follow and understand the concepts presented. You can use these tools to generate test cases, documentation, and even presentations that address how the solution will satisfy user requirements. With appropriate input and an understanding of the target audience, AI can produce output to support the project, the client, training documentation etc.

As a first time AI programmer, it is wise to consider AI recommendations and suggestions as an opportunity, to review the proposed solutions and ensure that there are no inappropriate shortcuts or errors. Think of yourself as a college professor reviewing a paper on a subject you know well. Look for the errors, the incorrect assumptions, etc.

While there is no doubt that AI will continue to evolve, and that its evolution will allow the tools to become more useful and more automated, it is also undeniable that, at the end of the day, AI serves the human population, whether that population is a customer base or a development team. The issue is less about code and the endless details and variables, and more about making the process more efficient, more accurate and more timely. The human factor is critical, and the role of a human programmer will continue to evolve as a manager, an experienced pair of eyes to review, advise, and ensure appropriateness and context are considered as the project moves forward toward completion.

Just as a great sports coach or professor can guide, teach and analyze based on their own experience and knowledge, the new world of AI coding and programming will require developers who can bring these skills to bear, embrace sophisticated tools and add those tools to augment, support and improve the outcome for the team, the client and the solution.

Contact Us to find out more about our AI Technology Capabilities and Review our White Paper, ‘What Is AI And How Can It Help My Business?,’ and our Blog article, ‘Improve Apps And Software With Artificial Intelligence.’

Original Post: How Does AI Coding Affect the Software Industry and Programmers!

Why Use Embedded AI In My Business Apps and Products?

author_img
by |
May 27, 2026

The Use of Embedded AI in Apps and Software Products

It is hard to miss the relevance of artificial intelligence (AI) in our society today. Discussions about its impact on our day-to-day lives, on technology and on competitive markets appear in the media, in industry publications and in kitchen table conversations.

When it comes to the use of Embedded AI within existing and new applications and software products, the discussion is no less active or relevant.

The University of Cincinnati recently reported that AI could contribute $15.7 trillion USD to the global economy by 2030. The integration of that technology into existing and new software products, applications and websites can, and should, be a part of any competitive strategy where business users or consumers and end users use technology to buy, communicate, gather information, etc.

The use of embedded AI within software products, apps and websites can:

  • Streamline development time and deliver new features and functionality to keep pace with the market and customer needs
  • Provide innovation within existing or new products to enhance competitive advantage
  • Enhance and improve customer and user satisfaction with quick, responsive features that provide detailed information, targeted to user needs
  • Improve productivity within business teams by providing automated workflow and processes to complete inquiries, approvals, etc. with limited or no human intervention

These are just a few of the advantages of Embedded AI.

Using Embedded AI to Upgrade and Improve Your Apps, Software Products and Competitive Advantage

TechTarget recently published a paper reporting on the findings of renowned research organizations and the global use of AI within businesses.

  • McKinsey & Co. – 88% of businesses report regular AI use in at least one business function (up from 78% in a prior year survey).
  • Gartner – Advantages of AI use within apps and the organization include incremental improvements to existing processes and workflows, modified processes that accelerate growth and profitability and altering business models to transform the business in ways that will redefine the market.

When integrating artificial intelligence (AI) and embedding it within your apps and software, it is important to work with an expert team that can help you assess your vision and requirements, your current technology landscape and your user targets to focus on the right goals and metrics and create a roadmap that will position you to make the changes you want now and to be flexible enough to upgrade and make changes for future requirements.

AI engineers, data scientists, designers and developers can use cutting-edge technology, cloud platforms, and enterprise analytics tools and techniques to build a scalable, secure, high-performance solution using dependable AI tools, machine learning, analytics systems and other methodologies and technologies to ensure rapid development, flexible deployment and long term dependability.

Here are just a few of the ways you can incorporate AI into existing systems to achieve results:

  • Language translation, data summarization and responding to queries and questions.
  • Automate routine tasks and enhance communications to improve customer support.
  • Create, tune and evaluate prompts for input and output in business systems to leverage available data.
  • AI approaches and predictive algorithms can contribute to finding new business opportunities, market optimization and more effective marketing and sales.

Contact Us to find out more about our AI Technology Capabilities and Review our White Paper, ‘What Is AI And How Can It Help My Business?,’ and our Blog article, ‘Improve Apps And Software With Artificial Intelligence.’

Original Post: Why Use Embedded AI In My Business Apps and Products?

How Can Minimum Viable Products Help My Start-Up Business

author_img
by |
March 25, 2026

Minimum Viable Products Are Key to Start-Up Success

Your business has a great idea for a software application or solution. If your enterprise is a start-up with a money-making concept, or you have an existing app and you want to make it more competitive, it is imperative that you take the most direct, effective route to product launch.

Microsoft Estimated that there were more than 50 million start-ups launched in 2022 alone. According to Crunchbase data and a CB Insights report, global venture funding declined 35% year over year in 2022. What does this mean? This decline in funding reflects a correction by venture capitalists and investors who no longer wish to bet on a unicorn.

SO…if you still think you have a great idea, and you want to fund a product or an upgrade, you MUST do so with a cost-effective approach; one that will provide the best chance of success with the least investment.

That’s where the Minimum Viable Product (MVP) concept comes in!

Let Your Start-Up Soar With Minimum Viable Product (MVP) Development

By engaging an expert in Minimum Viable Products, your start-up can plan for a product test to test theories and create features for feedback from users and customers without the extended cycle and expense of full product development, thereby ensuring success without betting all of your funding on a product that is not suitable for the market or the users you wish to target.

  • Strategy – Identify core product features that will deliver the most value for the largest user audience
  • Market – Define the market need and the target user or customer
  • Metrics – Establish metrics for success and a feedback and evaluation loop to gather and process data for the final product
  • Implementation and Roll-Out – Establish a scalable, workable plan for implementing the test strategy
  • Involve Stakeholders – Align goals and strategy and plan for reporting and stakeholder engagement
  • Alignment – Assure that the MVP features align with business value, revenue growth and the goals of the organization
  • Quality – Assure quality and security of MVP product
  • Define Success – Work with the team and stakeholders to define success and customer or user acceptance criteria
  • Incorporate Feedback – Establish feedback loops to ensure continuous improvement, and methods to incorporate appropriate features in final product

The examples provided above will give you an idea of the components and considerations included within a Minimum Viable Product (MVP) strategy. The MVP process provides swift, affordable market feedback and builds a process of iterative improvement to speed and enhance product development.

Expert MVP services include rapid prototyping, user testing, and iterative development to help you prove your idea’s potential before large scale investment. Be sure that the partner you choose has proven experience in MVP development.

Contact Us to find out more about our Minimum Viable Product (MVP) expert services. Our minimum viable product software development process focuses on identifying essential features, crafting an intuitive user experience, and delivering a functional prototype that investors and users can experience. Whether you need MVP development for startups or tailored enterprise solutions, we make sure your product stands out from the start. Review our MVP Case Studies: Recruitment Industry Start-Up Sourcing Platform, and Integrated Web and Mobile App for Holistic Healthcare.

Original Post : How Can Minimum Viable Products Help My Start-Up Business!

Conversational AI and NLP Expand Access to Analytics

author_img
by |
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!

Can Agentic AI Help My Business, and How Will it Impact My Staff?

author_img
by |
January 28, 2026

Agentic AI Can Be Used to Support Business and Teams

A recent study by Deloitte Reports that 52% of respondents say that Agentic AI is the most interesting area of artificial intelligence today.

Agentic AI takes artificial intelligence to the next level by enabling decision-making and independent behavior that involves reasoning, planning and completing tasks and actions in real time to achieve established goals.

Thirty years ago, we could not have imagined this technology, nor the impact it would have on productivity, work processes, businesses and consumers. In this rapidly evolving environment, it is worth considering the impact on jobs and on the people who previously performed the tasks we now as AI to complete.

Let’s consider some of the uses of Agentic AI so that we can better understand its potential and how it can be (and is) used in today’s business environment and how the use of Agentic AI will impact those currently working in each of these environments.

How Can Businesses Use Agentic AI to Help the Business and Support Team Members?

Manufacturing

Use Case: The typical manufacturing environment is supported by numerous systems, functions and processes. To complete the cycle, the business must incorporate the supply chain for parts and components and manage a multi-step, multi-level workflow. Agentic AI can work independently to identify supply shortages and review alternative sources for supplies that meet requirements for the timing of shipping and the price of materials. It can complete and submit forms and manage production schedules to accommodate the arrival of materials and meet deadlines.

Staffing Impact: If the business intends to engage Agentic AI to perform these tasks, it would be wise to include team members in the process to control specific, critical points along the manufacturing lifecycle and to monitor and manage the process to ensure appropriate decisions and action.

Call Centers

Use Case: Agentic AI is in use today in many call centers. AI agents gather and use existing intelligence to address and serve customers, considering order history and customer preferences, customer satisfaction, and company policies for returns, shipping and other factors.

Staffing Impact: Agentic AI can relieve live agents from the more mundane tasks and, when a live agent interacts with a customer, that agent can quickly leverage information gathered from previous interactions and orders and even suggest solutions and purchases or alternatives based on the information gathered by the AI assistant.

Healthcare

Use Case: Human interaction is crucial to healthcare but Agentic AI can help with the more routine activities like scheduling appointments, processing insurance claims and aligning government and industry regulations with tasks performed to ensure compliance. The system can review electronic health records (EHR) to bring together unstructured notes into a summary and provide classification information.

Staffing Impact: By streamlining the routine tasks, note-taking and summarization, Agentic AI can enable staff optimization and allow healthcare professionals to focus on patient interaction, records review and diagnostics and other crucial activities.

Research and Compounding

Use Case: Whether a business is developing a pharmaceutical compound or creating a food recipe, this process can take a lot of time and involve a lot of trial and error. Agentic AI allows the business to consider other additives, ingredients and compounds, compare the pricing for these new ingredients and compounds and the manufacturing requirements, alternatives and possible issues.

Staffing Impact: Skilled team members can use the information gathered and recommended by Agentic AI to review results, and make alternative recommendations or test theories and make final decisions.

As Artificial Intelligence (AI) evolves, it is important for businesses to weigh the experience, skills and knowledge of its team members and to incorporate those factors into the decisions surrounding the use of AI. Agentic AI and other technologies can be very helpful in performing routine activities, redundant tasks and even some decisions. But human intervention and experience are always important to identify and address the more nuanced issues and bring a trained eye to the final product, service or decision.

AI is at its best when it is used to its full potential, in concert with the human element of skills, experience and knowledge and it can be a benefit to your team by relieving them of routine tasks and by revealing interesting ideas and concepts that can be refined and used to create new business products and services and solving problems.

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 Products And Services can help you achieve your vision with affordable, dependable technology. Explore 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: Can Agentic AI Help My Business, and How Will it Impact My Staff?

Should I Choose Cloud-Based or On-Premises Business Intelligence?

author_img
by |
December 10, 2025

Choosing Between Cloud and On-Premises Augmented Analytics

Your business may be upgrading a business intelligence solution OR it may be considering the implementation of business intelligence (BI) for the first time. Either way, you will be faced with numerous decisions as you navigate the augmented analytics market and look for the right product and solution for your team and your organization.

Considerations include pricing, features, ease-of-use, data storage and data management location, and the capability of the solution to support upgrade and growth. When it comes to the technical foundation of the product and services, you will need to decide whether to choose a solution that resides on premises or one that is cloud-based.

Perhaps the most difficult aspect of this decision is advanced planning and anticipating the changing needs of the organization. If you are choosing an advanced analytics product, a business intelligence or augmented analytics solutions, you may wish to select a vendor that allows you to choose an on-premises OR cloud-based approach, with the flexibility to change your approach in the future WITHOUT having to change the software your team has adopted – the one they now understand and use on a daily basis.

On-Premises: Software is hosted onsite using enterprise hardware and infrastructure. Some businesses choose this option because they wish to retain control and provide assured security.

Cloud-Based: When a business chooses this option, it relies on third-party servers to support the software and data and accesses information via secured internet connections using cloud. This option provides a flexible, scalable approach and allows the enterprise to access software and features without the need for its own resources, IT support, and hardware expense.

Gartner Has Predicted that, ‘Demand for integration capabilities, agile work processes and composable architecture will drive continued shift to the cloud.’

On-Premises vs Cloud-Based BI Tools: Consider Your Enterprise Requirements

To choose the right solution, work with your IT partner, to consider:

  • Strategy for Business Growth
  • Industry, Government Security Compliance
  • Availability of and Access to Technical Experts
  • Ability to Easily Manage Data Sources, Data Access, etc.
  • Cost of Solution and Support and Maintenance
  • Performance, Scalability, Flexibility
  • Support for Upgrade, Future Needs, Digital Transformation (Dx)

Look for a flexible, low-code, no-code analytics platform with scalable technology infrastructure and architecture that offers on-premises, private cloud or public cloud implementation for Amazon, Microsoft Azure, Google Cloud and other options. Your IT consulting partner will help you decide on your approach based on data velocity, data sources and locations, data security and governance policies and your desired return on investment (ROI).

Contact Us to discuss your analytical needs and to find out more about Smarten Technology, Architecture And Infrastructure, and the process of choosing the right Analytics Solution for your business. Explore our White Paper: ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics,’ and our free article, ‘How Does Low Code And No Code Development Support BI Tools?’

Original Post: Should I Choose Cloud-Based or On-Premises Business Intelligence?

What Are Citizen Data Scientists Doing Today?

author_img
by |
October 29, 2025

How Has the Citizen Data Scientist Role Evolved?

Ten years ago, the term ‘Citizen Data Scientist’ was coined by the world-renowned technology research firm, Gartner. The term refers to business team members whose expertise and role are not focused on analytics as a primary job function. Using self-serve analytics solutions, these team members can leverage analytics to create models, reports and analysis to collaborate, share and make decisions. Gartner predicted the emergence of this role within businesses as part of the growing importance of data analytics and data-driven decisions within the business environment.

A decade later, it is worth reviewing the status of this role in the business enterprise and within the average organization. Is the Citizen Data Scientist role a standard role within most businesses today? Does a Citizen Data Scientist replace or work independently from a Data Scientist or Business Analyst? Has the Gartner prediction come to fruition?

While there are no current statistics regarding the number of companies currently using a Citizen Data Scientist approach, the trend toward data-driven planning and forecasting is clear. As with many other business trends, the larger organizations usually take the lead. They have the budget and the depth of resources to plan for and deploy changes across the enterprise and to test theories and enforce cultural changes.

Here are some statistics that reflect the growth of the Citizen Data Scientist movement and the supporting technologies that engender this approach:

After Ten Years, Is the Promise of Citizen Data Scientists Fulfilled?
  • Studies reveal that the number of Citizen Data Scientists is growing five times faster than the number of Data Scientists.
  • Automation technologies support the growth of the Citizen Data Scientist approach with over 40% of data science tasks automated through augmented analytics and/or machine learning.
  • The Machine Learning (ML) market is growing at a compounded annual rate of more than 15%, reflecting the need for data analytics capabilities within self-serve solutions.
  • By some estimates, interest in the Citizen Data Scientist role has tripled in the past decade, as medium and small enterprises embrace new, intuitive, more affordable technologies to support the Citizen Data Scientist concept within their organization.

As this concept became mainstream, the industries saw a trend toward increasing data-driven insight while reducing dependence on Data Scientists.

While the Citizen Data Scientist role began as a basic initiative to gather data and create simple reports, today’s Citizen Data Scientists are now using business intelligence (BI) tools and augmented analytics with Natural Language Processing (NLP), machine learning, low-code and no-code platforms and other technologies to leverage limited technical skills and create sophisticated analytics with clear results. Reports, dashboards and data sharing allow team members to create and use data models and to increase data literacy and data democratization.

Team members can use smart data visualization and assisted predictive modeling to gain insight and solve day-to-day problems, advise management and collaborate with other team members to understand trends, patterns, challenges, and opportunities and leverage metrics to make fact-based decisions.

This evolution of the Citizen Data Scientist role within the organization can free Data Scientists to perform more strategic activities without the daily distraction of simple report requests. If and when a particular data model or analytical approach must be refined to be more strategic, the Citizen Data Scientist can work with the Data Scientist to achieve that goal.

Using this approach, the enterprise can empower team members with the tools to analyze data and to use their knowledge of the industry, market, customers and business environment to make decisions and improve results.

When we consider the last decade of Citizen Data Scientist evolution, we see that businesses across all industries are working toward a more data-driven approach to decision-making, and embracing data democracy as a means to improve productivity and the quality of decisions and to reduce re-work and missteps.

Contact Us to discuss your analytical needs and to find out more about Citizen Data Scientists, and the process of choosing the right Analytics Solution for your business. Explore our free White Papers: ‘The Potential Of The Citizen Data Scientist Approach And Augmented Analytics,’ ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics,’ and ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI Tools.’

Original Post : What Are Citizen Data Scientists Doing Today?

Low-Code No-Code Software Development Options

author_img
by |
September 24, 2025

Consider Low Code and/or No Code Development

If you are considering the development of a software solution or app for business use or consumer release, you know that there are numerous crucial considerations involved in the process of software development. One of the most important factors in solution development is choosing the platform upon which you will build your mobile application, your software product or your business application. Today’s industry publications and technology journals are full of articles about low-code and no-code development technologies and techniques.

There is growing popularity among development teams and technology companies to suggest that the Low-Code and No-Code development (LCNC) approach has taken hold and that it has enabled businesses to move quickly to address market and business needs.

Gartner Defines Enterprise Low-Code Application Platforms (LCAPs) as platforms for accelerated development and maintenance of applications, using model-driven tools for the entire application’s technology stack, generative AI and prebuilt component catalogs.  According to Gartner, ‘low-code platforms will be used in 65% of application development by the end of this year.’

Low code/no code application development is a game-changing approach for software development and challenges the assumptions about the cost and time it takes to create a software solution or app. Low-Code, No-Code development approaches facilitate seamless and efficient development and allow businesses to expeditiously address individual client requirements with ease and precision.

The capabilities and advantages of the low-code, no-code or LCNC approach include:

Streamlined Development – Leveraging reusable components and a visual interface streamlines the development process exponentially, speeding up development and ensuring swift application delivery.

Promotes Inclusivity – The drag-and-drop features empower non-technical individuals with little to no coding knowledge to participate in development, thus promoting inclusivity.

Cost-Effectiveness – Low code/no code development demands no extensive coding or programming expertise, which lowers development costs, making it a cost-effective solution.

Rapid Prototyping – The visual approach of no code/low code development not only simplifies development but also fosters innovation by enabling rapid prototyping and easy project adaptability.

Low-Code and No-Code Development Options Like Creatio Ensure Speed and Reliability

Let’s take a moment to consider the differences between the Low-Code and No-Code development approach:

Low-Code Development

This approach supports the development team by decreasing the amount of ‘from scratch’ coding required, and creating a foundation of reusable code with components that become building blocks for future development. This development approach allows programmers to leverage low-code user interface components roughly 80% of development tasks, thereby limiting the manual coding efforts to 20% of developer time. Because low-code application development requires a knowledge of other tools and development skills, it is typically used by professional programmers with coding skills and knowledge. A Low Code development platform allows developers to extend component libraries and web frameworks to address specific use cases. Developers can work faster and more precisely with proven tools and combine coding and programming experience with tools designed for rapid software development.

No-Code Development

The No Code approach utilizes a visual workflow in an Integrated Development Environment (IDE), eliminating the need for manual coding. This technique creates a kind of ‘snap in’ system of components that developers can use and reuse to solve problems and create features and functionality. This closed system of tools restricts the developer by limiting use to pre-existing capabilities and user interface tools. The No-Code approach can provide a start-up with quick results and foundational features and allow them to enter the market and build visibility. Now that we have a better understanding of low-code/no-code app development, let us consider how technology research firms and publications see these development techniques.

If you are looking for a popular No-Code platform, you may wish to consider Creatio. Creatio is ideal for businesses that are focused on Customer Relationship Management (CRM), marketing, sales and service, and for the banking, insurance, credit unions, retail, transportation, business services, and telecommunications industries. Its no-code, open platform environment enables custom business applications for quick results.

The Creatio platform is designed with composable architecture, and does not require coding. It provides a simple, secured environment with frequent upgrades, and good performance and reliability. The Creatio framework enables fast and easy integration, integrating easily with other services and apps within your ecosystem and it supports rapid deployment and implementation and  configuration and ensures data security and appropriate data governance, so it is a good option for a project with tight timelines and/or budgetary controls.

Whether you are considering LCNC as one component of your software or app development project, or as a foundational development approach, it is important to understand the opportunities and challenges it may present and to engage an IT partner who can review your requirements and make the best recommendations to satisfy those requirements.

Contact Us to discuss your needs and to find out more about Low-Code No-Code Capabilities and the Creatio Framework.  Explore our free White Paper: ‘Understanding The Concept And Value Of Low-Code And No-Code Development’, and our blog article, ‘When Not To Use LCNC And Creatio.’

Original Post: Low-Code No-Code Software Development Options!