Tag: Data Literacy

Democratize Predictive Analytics and Support Citizen Data Scientists

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June 3, 2026

Enable Citizen Data Scientists with Predictive Analytics and BI

When a business recognizes the need for analytics and fact-based decision-making, it must choose the best BI tools and analytics to meet its requirements. While it is important to carefully consider the technology landscape, the integration needs and reporting requirements, one of the most important factors in choosing an advanced analytics solution is the foundation for data democratization and data literacy.

Today’s competitive business landscape makes it more important than ever to ensure that your enterprise can optimize productivity and team knowledge. The business must leverage BI tools to provide up-to-date, clear information to its team members so that they can collaborate, share data and make the best decisions. Analytics and predictive modeling tools also support the presentation of data in a way that is meaningful to the target audience and to those who are considering the data to capitalize on opportunities, solve problems and explain recommendations.

‘If you wish to encourage and enable Citizen Data Scientists, you must select a predictive analytics solution that can produce meaningful results to suit the role of the team member, and one that will satisfy the technical needs of an average user.’

According to Data Stack Hub, ‘Organizations that adopt data-drive decision-making are 5x more likely to make faster decisions,’ and ‘Approximately 73% of organizations say data analytics is a top priority in their digital transformation efforts.’

As businesses search for ways to plan, forecast and predict outcomes, the addition of predictive modeling as a tool for team members can enable and encourage user adoption of augmented analytics tools. Concise, clear and dependable predictions can help the team to plan accurately and to gain insight into how pricing changes, new products, and changes in customer communication will affect sales, customer retention, etc.

Support User Adoption and Citizen Data Scientists with Augmented Analytics and Predictive Modeling

When a team member adopts tools that help them to more easily and effectively complete tasks and share information, the team is more likely to embrace analytics and the organization can achieve digital transformation goals and transition team members into a Citizen Data Scientist role, thereby allowing business analysts and data scientists to focus on more strategic activities and ensuring that the team is producing fact-based information and making decisions that are based on data rather than on opinion or guesswork.

‘Concise, clear and dependable predictions can help the team to plan accurately and to gain insight into how pricing changes, new products, and changes in customer communication will affect sales, customer retention, etc.’

Ease-of-use and a clear understanding of results is paramount to successful user adoption of any software, but when it comes to predictive modeling and augmented analytics it is even more important. If you wish to encourage and enable Citizen Data Scientists, you must select a predictive analytics solution that can produce meaningful results to suit the role of the team member, and one that will satisfy the technical needs of an average user. By providing tools that help them do their jobs more efficiently, more quickly and with better results, you are much more likely to create an environment where Citizen Data Scientists can thrive.

Contact Us to discuss the unique needs of your organization and your users and find out more about our Predictive Analytics, Augmented Analytics Solution and services, enabling Citizen Data Scientists, and the use of Smarten Technology. Explore our free white paper, ‘Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’

Original Post : Democratize Predictive Analytics and Support Citizen Data Scientists!

Ensure Return on Investment and User Adoption for Augmented Analytics

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May 7, 2026

How Can My Business Ensure ROI and User Adoption for BI Tools?

A Reliable Research Study recently reported that, ‘The United States Augmented Analytics Software market is poised for significant growth, driven by increasing demand for data-driven decision-making and the integration of artificial intelligence. Businesses are leveraging advanced analytics tools to enhance data interpretation and automate insights, fostering a more agile operational environment.’

There is no doubt that the augmented analytics market is growing by leaps and bounds around the world. But for the business wishing to roll out its first augmented analytics software installation or for companies that wish to upgrade their analytics and improve data democratization and data literacy, the path to full implementation and user engagement can be fraught with missteps.

‘With careful planning and engagement of team members to extract feedback and plan for challenges, the business can ensure Return on Investment (ROI) and low Total Cost of Ownership (TCO), and enable user adoption.’

No executive team will approve new technology without some guarantee that it will pay off! Which means that the business team must find a way to ensure Return on Investment (ROI) and prove the benefits of the augmented analytics implementation.

Is Mobile BI Really a Necessity in Today’s Business Environment?

There are a number of considerations a business should include in order to address the issues inherent in this type of installation:

  • How and why does the team the business can benefit from this implementation?
  • What is the level of technology skills for the average intended augmented analytics user?
  • What resistance to workflow and process changes might arise? This issue will require engaging with the enterprise team to understand and address issues
  • What benefits will the enterprise team enjoy if the new analytics system is implemented?
  • How can collaboration, productivity, fact-based decision-making and data literacy improve the day-to-day team process and the organization?
  • Does the augmented analytics solution under consideration meet the stated requirements for features and functionality for the team and the company?
  • Does the solution support embedded BI, single sign-on and integration APIs to encourage users to explore analytics within the confines of familiar enterprise applications?
  • Does the solution provide ease-of-use for all users and flexibility and personalization options to make its use more meaningful to each user?
  • Does the IT team have the appropriate support from an expert Augmented Analytics partner to review and address requirements and provide support?

When selecting an augmented analytics solution or BI tool, the business should take the time to plan carefully in order to avoid implementation of a solution that does not suit the needs of the organization or one that users will not adopt because of poor training or communication or cultural bias against new work processes or workflow.

With careful planning and engagement of team members to extract feedback and plan for challenges, the business can ensure Return on Investment (ROI) and low Total Cost of Ownership (TCO), and enable user adoption. Take the time to develop requirements, consider the features and functionality that will best serve you organization and create user cases to test the features against the planned use of the software product.

‘No executive team will approve new technology without some guarantee that it will pay off! Which means that the business team must find a way to ensure Return on Investment (ROI) and prove the benefits of the augmented analytics implementation.’

Contact Us to discuss the unique needs of your organization and your users and find out more about our Augmented Analytics Solution and services, and about Smarten Technology. Explore our free white paper, ‘Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’

Original Post : Ensure Return on Investment and User Adoption for Augmented Analytics!

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!

Which BI or Analytics Tool is Best for My Business?

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January 5, 2026

Traditional BI, Augmented Analytics, or Modern BI/Analytics?

Whether your business is planning to acquire a business intelligence (BI) or augmented analytics tool for a first-time installation or looking to upgrade an existing system, the decision starts with the ‘what’ of the solution. What kind of solution will best fit your needs for infrastructure, integration, user requirements, pricing, upgrades etc. and what kind of approach, features and functionality will be most suitable for your business.

‘When considering a new or upgraded business intelligence or advanced analytics solution, it is important to look at your enterprise requirements to accommodate existing technologies and infrastructure, business processes and models and user needs.’

A Recent Study reveals a number of considerations to be included in your choice of BI tools and analytical platforms, including:

  • Zero footprint: 100% web-based, no client-side installs or downloads required
  • Support for role-based reporting and dashboards
  • Support for mobile Business Intelligence
  • Communication features like notes, comments, and likes
  • Updates in real-time: your dashboard is always up to date
  • Basket, advanced and predictive analysis
  • Support for machine learning and generative AI
  • Usability: ease-of-use and ease-of-learning
  • Insights (graphs, definitions, et cetera) that are reusable across BI applications

While this study carves out what it considers to be the optimal analytics framework and platform, some of all of these considerations may not apply to your business needs.

What Do I Need to Consider When Choosing BI Tools and Analytics Solutions?

When reviewing the various iterations of analytics frameworks and platforms, you will need to understand the following capabilities and structures. Understanding how each of these approaches works and what advantages and limitations they include will make it easier for you to choose a solution and approach to suit your needs.

Augmented Analytics

Today’s augmented data analytics incorporates artificial intelligence (AI) and machine learning (ML) to streamline, automate and improve the process of data analysis, so business users can more easily gather, interact with, select and report on data, simplifying data prep, insight and collaboration and allowing your team to explore data in a way that is meaningful to them.

Augmented analytics uses machine learning, natural language processing (NLP), and algorithms to easily analyze and manipulate large datasets and reduces the time needed for processing, thereby allowing business users to leverage analytics in their day-to-day workflow and freeing Data Scientists to perform more strategic tasks.

Benefits of Augmented Analytics

  • Streamlined data prep and analytics
  • Optimizes business user and data scientist time and effort
  • Faster, more insightful decision-making
  • Increased operational efficiency
  • Democratized data analytics

Traditional Business intelligence

Traditional BI Tools use conventional analytical techniques and technologies to collect, analyze and present data. These systems typically rely on a centralized data source and a selected set of formatted reports. Users leverage data extraction, transformation and loading tools (ETL) to extract data from a data warehouse and online analytical processing (OLAP) tools to analyze data. Reports and visualization are typically delivered through a dashboard with standard key performance indicator (KPI) software to monitor metrics.

Benefits of Traditional BI Tools

  • These tools provide support for a range of data types and data sources
  • IT and/or data scientists can create standardized reports and models to address business and user needs
  • The enterprise can maintain and control data sources on-site

Modern BI Tools and Augmented Analytics

When an organization integrates the use of modern BI tools with more advanced augmented analytics it can leverage artificial intelligence and traditional tools to satisfy the needs of a diverse set of users, business units, etc. Modern Business Intelligence technologies integrates more sophisticated features to bring analytics to all users and allow them to choose the tools that best suit their needs in a self-serve environment with automated data preparation, fast and easy data access and insight, Natural Language Processing (NLP) that allows users to ask questions using common language and receive answers using visualization techniques.

Benefits of Modern BI Tools and Augmented Analytics Combined

  • Sophisticated self-serve analytics suitable for business users with limited technical skills
  • Real-Time insights and reduced time-to-decision
  • Monitoring and managing of trends, anomalies and other factors that impact results
  • Collaboration and data democratization with unique tools to suit every user
‘When reviewing the various iterations of analytics frameworks and platforms, you will need to understand the following capabilities and structures. Understanding how each of these approaches works and what advantages and limitations they include will make it easier for you to choose a solution and approach to suit your needs.’

When considering a new or upgraded business intelligence or advanced analytics solution, it is important to look at your enterprise requirements to accommodate existing technologies and infrastructure, business processes and models and user needs.

Contact Us to discuss the unique needs of your organization and your users and find out more about Smarten Technology. The process of choosing the right Analytics Solution for your busine is crucial and must include a careful assessment of your needs. Explore our White Paper: ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics,’ and our article, ‘How Does Low Code And No Code Development Support BI Tools?’

Original Post : Which BI or Analytics Tool is Best for My Business?

Augmented Analytics Can Support a Large User Base

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November 7, 2025

Support Your Large Business User Base with the RIGHT BI Tools

According To Finance Online, Allied Market Research reports that small and medium businesses are driving enterprise use of analytics, but World Data Science Initiative reports that 80% of global companies are investing in data analytics, thereby revealing analytics growth across, small, medium and large enterprises.

For your large enterprise, data analytics can and will be a definitive issue impacting your business and market growth. Choosing the right solution to support data democratization and improved data literacy across the enterprise will ensure that your team can create, share, collaborate and report on data, make recommendations and suggestions based on fact, and use data-driven metrics to ensure that strategies and operational decisions are relevant, accurate and effective.

‘While many large organizations are daunted by the idea of implementing analytics across the organizations, it is completely feasible to plan for an deploy this software and to modify business processes to build on fact-based decisions.’

Today’s self-serve augmented analytics and modern business intelligence solutions are designed to support users across the enterprise, and a solution that is built on the right technology platforms, will enable rapid implementation and user adoption and requires very little training or transition time. Auto-suggestions and recommendations allow users to work on their own, no matter their skill levels.

To support a large user base, you will want to select an augmented analytics solution designed with a low-code, no-code, artificial intelligence and machine learning environment to ensure scalability and seamless, responsive, mobile access.

Contrary to Some Opinions, a Large Enterprise with Many Users CAN Adopt Augmented Analytics

Your team can untangle quality and maintenance issues, refine customer targeting and marketing optimization, make appropriate financial investment decisions, and even use external data to analyze trends and patterns and make forecasts and predications.

Real-time data management lets users connect to data sources in real time, and compiles data for fast performance to deliver real time analytics. Cached data management caches data and performs pre-aggregation and other computations for superior performance and analytics, and refreshes data from data sources at a defined frequency.

Your enterprise can choose on-premises or private or public cloud-based data management to access the analytics solution from any business location around the world, or for remote workers or those working on the road, in hotels or airports.

‘For your large enterprise, data analytics can and will be a definitive issue impacting your business and market growth. Choose the right solution to support data democratization and improved data literacy and use data-driven metrics to ensure that strategies and operational decisions are relevant, accurate and effective.’

While many large organizations are daunted by the idea of implementing analytics across the organizations, it is completely feasible to plan for an deploy this software and to modify business processes to build on fact-based decisions. Work with your IT partner to plan a reasonable roll-out and address cultural concerns, and to budget for and implement an affordable, dependable analytics solutions across the enterprise. No matter how many business users your business has, you CAN adopt and leverage self-serve augmented analytics to support your business, improve competitive advantage and gain crucial insight into data for planning, problem-solving and identification of trends, patterns, issues and opportunities.

Ensure appropriate Technology, skills and knowledge, Cutting-Edge Features and an advanced approach to Augmented Analytics And Business Intelligence. Contact Us to find out more about the Smarten suite of products. Explore our free white paper: ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics.’

Original Post : Augmented Analytics Can Support a Large User Base!

What Are Citizen Data Scientists Doing Today?

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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?

Citizen Data Scientists Are Important to Business Transformation

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October 7, 2025

Transform Your Business with Citizen Data Scientists

The business environment today is competitive. Whether your business is global or local, you are challenged to do more with less, to set and achieve goals more quickly and to stay ahead of your competitors by gaining a comprehensive understanding of what your customers want, what they WILL want, and how to best attract their attention and retain them.

To meet these challenges, every team member and employee must have a thorough understanding of how their roles and responsibilities fit into the grand scheme of things and how the projects, tasks and activities they pursue on a day-to-day basis will affect revenue, outcomes and results.

When a business (large or small) makes the decision to transition business users to Citizen Data Scientists, it supports the alignment of goals and objectives with fact-based decision-making and improved data literacy, encouraging its users to embrace and understand data and use that data to collaborate, present information to management and gain insight into results to identify opportunities and address issues.

‘The Citizen Data Scientist approach transforms the organization by improving time to market, reducing rework and mitigating market missteps and improving productivity and the alignment of workflow and tasks with the goals and objectives of the enterprise.’

World renowned technology research firm Gartner first coined the term ‘Citizen Data Scientist’ in 2016 and defined the role as ‘a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’

Nearly a decade later, the role has been refined and structured within many organizations and recent Gartner research reports that, ‘Citizen Data Scientists can be leveraged to perform repetitive and redundant tasks in the analytics workflow, and therefore create value to the organization, while allowing expert data scientists to focus on more complex tasks.’

The increased pace and tenor of competition has forced businesses to accommodate rapid change in markets and customer buying behavior by using analytics, data scientists and business analysts to work with IT and create reports and presentations to be used for decisions. But there just aren’t enough professional resources of funds to support this approach. Hence, the evolution of Citizen Data Scientists.

Transform Business Users Into Citizen Data Scientists AND Transform Your Business

The evolution of self-serve augmented analytics tools and technologies like natural language processing (NLP) and NLP search, machine learning, flexible data visualization, and artificial intelligence (AI) provide support for business users without technical skills to gather and analyze data and produce reports, collaborate with other users and make recommendations using insight derived from advanced analytics. And this approach supports data democratization and data literacy.

The Citizen Data Scientist approach also transforms the organization by allowing business users to interact with and collaborate with IT and data scientists to take day-to-day data analytics and translate them into strategic initiatives with measurable results, accurate predictions and rapid flexible processes.

The Citizen Data Scientist approach transforms the organization by improving time to market, reducing rework and mitigating market missteps and improving productivity and the alignment of workflow and tasks with the goals and objectives of the enterprise. It provides a career path for business users and advances their knowledge and skills, allowing them to understand how their role directly influences results and to create and innovate.

‘When a business (large or small) makes the decision to transition business users to Citizen Data Scientists, it supports the alignment of goals and objectives with fact-based decision-making and improved data literacy, encouraging its users to embrace and understand data.’

To plan for and execute a Citizen Data Scientist initiative, the organization must engage an expert in augmented analytics and develop a comprehensive understanding of technology and cultural changes in order to advance this new idea within the ranks of IT, data scientists, business users, managers and executives.

Learn more about how the transformation of business users to Citizen Data Scientists can benefit your business, and how technology and appropriate Self-Serve Analytics Tools can support Citizen Data Scientists in their new role, and provide fact-based decision-making and advantages to the organization. Explore our free white papers and articles: ‘The Potential Of The Citizen Data Scientist Approach And Augmented Analytics,’ and ‘Leverage Citizen Data Scientists For Business And Business Users.’

Original Post : Citizen Data Scientists Are Important to Business Transformation!

Leverage Citizen Data Scientists for Business and Business Users

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July 23, 2025

Business and Team Member Benefits of Citizen Data Scientists!

When a business considers the prospect of implementing business intelligence and augmented analytics tools to align objectives and streamline processes and decision-making, the business management and executive team can often see the project as time-consuming and expensive.

In fact, most proposals that include process changes, training and new technology get stalled because:

a. change is hard

b. there is a tendency to say that everything is just fine the way it is

c. the management team believes that the expense is not equal to the value of the transition.

When it comes to BI tools and self-serve analytics, all of these claims can be disproven by results.

‘By providing business users with easy-to-use BI tools and augmented analytics features that produce results and allow them to make the most of their knowledge and time, the organization is more likely to retain its human resource assets and to identify and utilize its team member skills to achieve results, thereby creating a competitive advantage and a more agile, streamlined enterprise.’

In fact, Gartner has predicted that ‘Early adopters of augmented analytics have the potential to realize more strategic and differentiating business benefits from their analytics investments than those who wait until these technologies are widely adopted.’

Results and benefits are proven across the enterprise by businesses that have already adopted business intelligence and augmented analytics.

Minimum Viable Products (MVP) Produces Better Business Start-Up Results

For the organization, these benefits include:

  • Support for data-driven, fact-based decision making
  • Insight and perspective into history, results and trends and patterns for strategy and operational decisions
  • Encouraging collaboration among team members, IT, business analysts and data scientists
  • Business agility and efficiency
  • Leveraging human resource assets and improving productivity
  • Creating a competitive advantage with rapid decision-making and market response
  • Improving and optimizing financial investments, forecasts and predictions

For business users, transitioning to Citizen Data Scientists, the advantages include:

  • Combining professional and industry knowledge with data to achieve accurate results
  • Leveraging simple BI tools and self-serve analytics to receive recommendations and suggestions and make quick, clear decisions
  • Reducing the need for IT and data scientist assistance
  • Collaborating with other business users to create and share data, reports and information
  • Advancing career goals by learning and using tools that combine existing skills with new analytical capabilities
  • Improving data-driven decisions and reducing re-work

By providing business users with easy-to-use BI tools and augmented analytics features that produce results and allow them to make the most of their knowledge and time, the organization is more likely to retain its human resource assets and to identify and utilize its team member skills to achieve results, thereby creating a competitive advantage and a more agile, streamlined enterprise.

‘Gartner has predicted that ‘Early adopters of augmented analytics have the potential to realize more strategic and differentiating business benefits from their analytics investments than those who wait until these technologies are widely adopted.’

If your business wishes to capitalize on the potential of the Citizen Data Scientist approach, it important to work with an IT Partner who can help you define your requirements and strategize for optimal success, providing the augmented analytics tools and knowledge of the industry that is required to position you for success. Get started today with our self-paced FREE Online Citizen Data Scientist course.

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.

Original Post : Leverage Citizen Data Scientists for Business and Business Users!

BI Tools and Augmented Analytics That Ensure User Adoption and ROI

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May 7, 2025

Ensure ROI, TCO and User Adoption with the Right BI Tools

When a business sets out to implement BI tools or self-serve augmented analytics, it must consider the entire technology landscape of the business, the expectations of end-users, the cost of the solution, how easily it can be upgraded and integrated and, well…so much more!

 

‘To ensure user adoption and achieve the ROI and TCO the business deserves, take the time to do the work. Develop requirements, consider the features and functionality of a solution and compare those to your use cases and your user expectations.’

 

Management teams do not take kindly to poor Return on Investment (ROI ) or Total Cost of Ownership (TCO) and if the business has had difficult projects in the past, the next time a software solution is presented for approval, senior managers will remember the challenges and failures of the past!

 

Still, when you are attempting to transition business users into Citizen Data Scientists, there is bound to be some pushback from users and that pushback, combined with senior management concerns can and WILL bring your project to its knees if you do not anticipate and address these concerns.

 

Here are some statistics that will help you to understand the issues faced by businesses in implementing BI tools and analytics:
  • The global BI adoption rate is 26%
  • On average, businesses use at least four different BI tools
  • 97% of the data gathered by businesses is not used
  • 74% of employees express dissatisfaction and are overwhelmed when working with business data

 

In order to assure successful deployment, user adoption, improved Return on Investment (ROI) and Total Cost of Ownership (TCO), the business should include detailed requirements in its solution selection. When choosing a BI tool and augmented analytics solution for your business, one of the most crucial concerns is the features and functionality of the prospective solution and how this solution will meet user and organizational needs. When planning for deployment of BI tools and augmented analytics, the business should take the time to work through a process, ensuring that it has considered what users need and want to ensure user adoption and the ease-of-use and features the solution will provide.
To Achieve User Adoption, ROI and TCO Goals, Select the RIGHT BI Tools and Augmented Analytics
It is important to remember that there are also specific features a business should consider, like embedded BI and easy-to-employ Integration APIs, that will assure user adoption and appropriate ROI and TCO. These considerations will affect how well the solution is received, whether users will adopt it and be satisfied with the selection, and how the investment will perform when considering total cost of ownership (TCO) and return on investment (ROI) when compared to other possible uses of the same investment funding.

 

With this foundation of documented features, services, skills and capabilities, the business can implement, manage, upgrade and support Business Intelligence and Augmented Analytics capacity and growth within the organization.

 

‘When you are attempting to transition business users into Citizen Data Scientists, there is bound to be some pushback from users and that pushback, combined with senior management concerns can and WILL bring your project to its knees if you do not anticipate and address these concerns.’

 

To ensure user adoption and achieve the ROI and TCO the business deserves, take the time to do the work. Develop requirements, consider the features and functionality of a solution and compare those to your use cases and your user expectations. INVOLVE your users and middle managers in planning to understand how and when to deploy the tools and how to support your business users as you transition them into Citizen Data Scientists.

 

To find out more about how to ensure Return on Investment (ROI) and Total Cost of Ownership (TCO) results, and enable user adoption, read our free White Paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’ To find out more about our Augmented Analytics And BI Tools, Contact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

 

Original Post : BI Tools and Augmented Analytics That Ensure User Adoption and ROI!