Analytics and Citizen Data Scientists Ensure Business Advantage

Fact-Based Analytics and Citizen Data Scientists = Results

So, you want your business users to embrace and use analytics? You want your business to enjoy the benefits of fact-based decision making? You want your business to use the tools of business intelligence to improve market presence, customer satisfaction and team productivity and collaboration?

‘Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.’

Gartner has predicted that, ‘a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.’ And that is the good news. But, if the business is to leverage the potential of analytics within the organization, it must choose the right analytics tools to ensure that business users will adopt analytics in day-to-day tasks.

If your enterprise wishes to transition business users into Citizen Data Scientists and use augmented analytics to gain a competitive advantage, it must provide easy-to-use tools that do NOT require team members to be business analysts or IT professionals – tools that allow users to quickly gather data using self-serve data preparation, using data integrated from disparate data repositories with smart data visualization to view, format and share results that are clear, concise and actionable.

The business market is more competitive than ever and in today’s environment it isn’t enough to simply analyze historical data. To make good business decisions, adjust strategies and forecast and plan, you must use that historical data to plan for the future.

Businesses that can gather data from disparate sources and use historical data to understand trends and patterns and forecast for the future can establish and sustain a competitive advantage and plan more effectively and accurately, avoiding missteps in the market and costly mistakes.

If your business wishes to sustain a competitive advantage, if you as a user wish to advance in your career and build your value to the organization, it is incumbent upon you to embrace the trend of data democratization, data literacy and self-serve, augmented analytics.

For Competitive Advantage, Enable Citizen Data Scientists with Augmented Analytics

Today, augmented analytics and smart data discovery make it easier for business users, data scientists, IT staff and the organization to benefit from fact-based decision-making, collaboration, data literacy and the ability to easily, gather, integrate and analyze data.

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

What you need are apps and solutions that allow you to ask easy questions in your own words and receive guidance and recommendations on how to best visualize and present your data and what techniques to use to gain the most insight.

Use a simple low-code, no-code analytics platform and augmented analytics and BI tools designed for business users with real-world business cases to find answers and solve problems. You 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 predictions, helping users and the business to achieve success in industries and businesses like retail, pharmacy and wellness, insurance, manufacturing, government and public sector, utilities, and other industries.

‘If your enterprise wishes to transition business users into Citizen Data Scientists and use augmented analytics to gain a competitive advantage, it must provide easy-to-use tools that do NOT require team members to be business analysts or IT professionals.’

To find out more about how to ensure Return on Investment (ROI) and Total Cost of Ownership (TCO) results, gain a competitive market advantage, and enable user adoption, read our free White Paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’ Explore The Benefits of our Augmented Analytics And BI ToolsContact 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.

BI Tools and Augmented Analytics That Ensure User Adoption and ROI

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 ToolsContact 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!

AI-Enabled Analytics and Business Intelligence Has Its Benefits

Why Choose BI Tools and Analytics with AI?

Today, the use of Artificial Intelligence (AI) has a wealth of potential and prospective application in the field of analytics and its integration within analytical products provides numerous benefits to the business. There are many ways in which artificial intelligence (AI)  can augment the capabilities of existing analytics solutions, and provide additional insight, support and results.

 

World-renowned technology research firm, Gartner, predicts that ‘40% of application development teams will be using automated data science and machine learning services to build models and add AI capabilities to applications.’

 

True to this prediction, many business intelligence and analytics solution vendors have added AI capabilities to self-serve analytics to create an environment that encourages productivity, fact-based decisions and efficient business processes, approval processes, automated alerts, etc.

 

There are a number of ways that artificial intelligence can enhance and improve the features and functionality within an enterprise using the augmented analytics environment:

Business Intelligence (BI) – Artificial Intelligence can be used to analyze large datasets and to sort and present data to achieve actionable insight, recommendations and suggestions, spotting trends, providing forecasts and optimizing results.

Generative AI (GenAI) Applications – Using Natural Language Processing (NLP) and Machine Learning (ML), AI tools can create content including images, text, video and other components to enhance presentation, interact with customers and suppliers in a targeted way and personalize messages.

Analytics Tools and Techniques – Team members and end-users can leverage self-serve analytics with AI to identify patterns and trends, gain insight, present data in a way that is meaningful to a particular target audience, predict outcomes, analyze customer buying behavior and analyze performance of products, services and other operational components.

Marketing and Advertising – The organization can analyze data from disparate data sources to identify market trends, changes in targeted customer preferences, requirements for customer relationship management, and other factors that relate to competitive advantage and customer retention.

Analytics Features and Development – Vendors and solution providers can use AI to quickly and easily upgrade analytics solutions, add features and functionality and reduce development time to keep up with client and market demands.

 

Current Artificial Intelligence technologies like ChatGPT, GenAI, and Agentic AI all provide specific capabilities to satisfy business requirements and inform and improve analytics with data gathered from within the organization that can be repurposed, targeted and used to solve problems, identify opportunities, present data to management, partners and customers, and communicate with all stakeholders using relevant data and information garnered from within and outside the enterprise.

Choose Business Intelligence and Augmented Analytics with Artificial Intelligence to Improve Outcomes
  • Improve Data Visualization – Create interactive dashboards, graphs and charts to help users present and share data in a way that is meaningful to a particular audience, and to clearly present data for confident decision-making. It can recommend and suggest visualization techniques to improve and refine how data is presented.
  • Improve Analytics with Task Automation – Automate activities and tasks, using customized automation scripts, and baseline filters and rules to extract and present data that meets user parameters. It can schedule and produce repetitive reports, and scripts can be altered change parameters, thereby freeing users to perform other operational or more strategic activities.
  • Predictive Analytics – Create predictive models using self-guiding UI wizard and auto-recommendations for swift, effortless forecasting and predictive analytics using data from numerous data sources.
  • Natural Language Processing (NLP) – Expand the capabilities of text generation and human language processing. It can enhance low resolution images, recognize and synthesize images and generate images for creative presentation of data and information.
  • Auto Insights and Machine Learning – Automates the process of interpreting and presenting results using rich visualization techniques, and includes all salient details, so users can review, share or edit content as they please.
  • Automated Alerts – Analyze results and trigger and generate alerts to protect against security violations, fraud and other risks, by analyzing normal behavior and results and comparing it to current and real-world results to identify anomalies.
  • Reporting – Using visualization, graphs, images and combining those with summaries and details can provide reports and presentations that are clear and suitable for all audiences, including management and executives, as well as teams and staff members.
  • Interpretation and Summarization – Quickly interpret and summarize data without spending a lot of time creating content, editing and preparing.
  • Data Preparation – Improve data transformation and cleansing and help prepare data and improve the quality of that data using phonetics for clustering, identifying data types, and hierarchies, suggesting alternate values etc.
  • Support for Citizen Data Scientists – Use AI cutting-edge tools to support team members with sophisticated, intuitive tools that leverage artificial intelligence (AI) and analytical techniques to produce concise results without requiring the skills of Data Scientists.

 

The analytical solutions market is moving quickly to adopt Artificial Intelligence and if your business wishes to succeed, it too must move to find and improve products and services as quickly as possible to meet customer expectations and to satisfy the ever-changing landscape of business competition.

 

Select and implement an Augmented Analytics Solution With Artificial Intelligence (AI) components to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read White Papers, ‘Generative AI (GenAI): The Benefits And Applications Of AI In Analytics,’ and ‘The Practical Use Of GenAI In Business Intelligence And Analytics Tools’ and explore the benefits of AI in analytics and the full spectrum of benefits and advantages of current artificial intelligence (AI) technologies.

 

Original Post : AI-Enabled Analytics and Business Intelligence Has Its Benefits!

Enable User Adoption of BI Tools with Embedded BI

Embedded BI Assures User Adoption of Analytics

When a business sets out to initiate data democratization and improve data literacy, it must choose the right approach to business intelligence and select an augmented analytics product that is self-serve, intuitive, easy to implement and easy for business users to embrace. Transitioning business users into the role of a Citizen Data Scientist can be challenging.

 

‘If the organization wishes to convince its business users of the importance of data analytics and fact-based decision-making, it must provide tools that are intuitive, easy-to-use and can be established within the parameters of the user’s day-to-day tasks as an integrated part of their workflow.’

 

To ensure user adoption of BI tools, optimize return on investment (ROI) and total cost of ownership (TCO) and successfully deploy business intelligence and augmented analytics, businesses often choose Embedded BI.

 

Gartner defines embedded analytics in this way: ‘Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.’

If Your Business is Considering BI and Augmented Analytics, Embedded BI Will Enable User Adoption

Embedded BI solutions differ from the typical business intelligence solution in a number of ways. Here are just a few examples:

User Experience (Ux) – In the traditional BI environment, business users must learn a new solution and interface and may be required to among other solutions and software products to use that data within the BI tool. Users with average or poor technical skills are not likely to adopt a solution that requires additional training and multiple steps to accomplish a task. In the Embedded BI environment, analytics is accessible from within a familiar enterprise solution using a single sign-on and tools that are intuitive, so the user can quickly find information and analyze it all in one place.

User Adoption – In a traditional BI environment, users must invest time to learn a new BI tool and work within data silos to try to analyze information and share that information with others. Embedded BI allows users to leverage analytics within the natural flow of their daily tasks and easily share that data with other users, so the team and the individual user adoption is supported.

Integrated Workflow – Business team members are busy, and they are often scrambling to complete tasks on time and to make decisions, create presentations and move on to the next thing. Traditional BI tools require users to interrupt their workflow, and use multiple enterprise solutions to gather and analyze data within the BI environment, so the analytics process is cumbersome and inefficient. Embedded BI allows users to work in an integrated environment, gain data insight and make relevant data-driven decisions without delay or frustration.

 

‘Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.’

 

In a business environment that is more competitive than ever before, team members must have the tools they need to perform tasks and complete activities dependably, and to have a firm grasp on the solutions and tools they use without spending a lot of time in training, or in gathering and preparing data to gain insight into challenges, issues, opportunities or trends that affect business success. If the organization wishes to convince its business users of the importance of data analytics and fact-based decision-making, it must provide tools that are intuitive, easy-to-use and can be established within the parameters of the user’s day-to-day tasks as an integrated part of their workflow. This approach to BI and analytics will ensure user adoption.

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 : Enable User Adoption of BI Tools with Embedded BI!

Why Choose Augmented Analytics with Low-Code, No-Code Development

Low Code No Code Development Supports Analytics Performance

Within the very near future, it is estimated that 70% of all software and application design will include a component of low-code or no-code development. So, it is no surprise that analytics software and tools are also affected by this trend. While advanced analytics and augmented analytics solutions provide a sophisticated, complicated underpinning of algorithms and analytical techniques, the average enterprise expects (and should look for) tools that are easy to use, so they can improve data literacy and data democratization and leverage analytics within the organization at the business user level, to improve results and efficiency.

It may be difficult to understand how such complex systems can benefit from the no code, low code approach, since the very concept of this approach seems at odds with the complexity of an analytical solution, but nothing could be further from the truth. When applied appropriately, these techniques can benefit the foundation of the augmented analytical solution and the users of those solutions.

  • Time and Expense – In a world where new features and functionality must keep pace with market demand, the emergence of no-code and low-code allows developers to add analytical functionality quickly, while controlling costs and time to market.
  • Business and Market Requirements – As organizations and business users embrace analytics, the need for new types of visualization, reporting and features changes quickly. In order to stay abreast of these changes and offer businesses the products they need, analytical vendors can quickly leverage, modify and develop new approaches to satisfy user requirements. Vendors can accommodate business-specific needs and data visualization requirements without time-consuming, expensive customization.
  • Integration of Third-Party Apps – Low-Code, No-Code capabilities support the easy integration of other enterprise applications and solutions and allow data analysis across the organization.
  • Performance and Scalability – Low-Code and No-Code solutions and platforms enable high-performance, scalable solutions and ensure that businesses can accommodate an expanding user base and data volume.
  • Compliance, Data Security and Industry Standards – No Code, Low-Code development includes data encryption features and user access security controls to mitigate risk, and protect data integrity and privacy.
Augmented Analytics with Low-Code, No-Code Development Provides Performance and Adaptability

If you are still wondering whether low-code and no-code approaches are appropriate for software and applications, consider these predictions and statistics from technology research organizations:

  • Gartner predicts that 75% of new software solutions will incorporate a low-code approach to development.
  • By some estimates, the use of low-code, no-code and artificial intelligence in analytics solutions has increased user access to analytics by as much as 56%.
  • Gartner predicts that organizations that lack a sustainable plan to operationalize and manage data and analytics will face a two-year setback in their data and technology efforts.

Choosing the right self-serve, augmented analytics solution can help the enterprise build a crucial foundation for analytics, for transition of business users into a Citizen Data Scientist role and for improved time-to-market, decision-making and collaboration. The use of new and cutting edge technologies and the seamless incorporation of these technologies is critical to the success of the analytical application implementation and to return on investment (ROI) and total cost of ownership (TCO) metrics.

Select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities and enjoy the benefits of advanced technologies like Artificial Intelligence (AI) And Low-Code, No-Code (LCNC) techniques to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read our free article, ‘The Benefits Of Low-Code No-Code in Augmented Analytics.’

Original Post : Why Choose Augmented Analytics with Low-Code, No-Code Development!

Mobile BI Tools Solve Many Enterprise Issues!

Incorporate Data Into User Roles with Mobile BI

If you are a business executive or an IT professional, you have probably seen a number of articles about the importance of Business Intelligence in industry publications and trade journals. If you are still unconvinced or uncertain about the critical importance of business intelligence (BI) and analytics for businesses like yours, here are some sobering, surprising and impressive statistics to ponder.

  • The global business intelligence adoption rate is 26%.
  • Organizations use 4 or more different business intelligence tools on average.
  • Organizations leave 97% of gathered data unused.
  • 74% of employees feel unhappy or overwhelmed when working with data.
  • Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not.
  • Bad data costs the US economy $3.1 trillion each year.

When you review these statistics, you will notice that some of the issues described can be resolved by the careful selection of the right software and solutions to satisfy your business, your team needs and your data infrastructure.

Why Mobile BI? Because it Solves Common Business Analytics Complaints!

If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.

‘Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.’

The right mobile BI tools can address the issues and statistics listed above in the following ways:

  • The global business intelligence adoption rate is 26% – Mobile BI tools will increase the user adoption rate by providing intuitive data analytics that users can access from anywhere at any time, making these tools an important part of each team member’s tool box.
  • Organizations use 4 or more different business intelligence tools on average – The right mobile BI solution can integrate data from disparate data sources, and allow users to visualize in a way that is meaningful to each team member. It can optimize technology infrastructure and mitigate the issue of data silos and complex data mining and data gathering.
  • Organizations leave 97% of gathered data unused – Data is often misunderstood, misused or unused simply because team members and the enterprise do not know how to leverage, gather and analyze the data, or because the IT and/or data science team is short on resources and does not have the time to produce reports. Mobile BI tools are designed to be used by business professionals on a daily basis and to encourage data literacy and data democratization across the enterprise.
  • 74% of employees feel unhappy or overwhelmed when working with data – Understand and address your business user concerns and make data more accessible, easier to understand and use, concise and clear, so that every user can optimize data, make confident decisions and share and collaborate without data science skills or sophisticated data analytical experience.
  • Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not – Improve productivity, time to market and return on investment (ROI) and total cost of ownership (TCO) to gain a competitive advantage with mobile tools and easy-to-use techniques that will enable fact-based decisions.
  • Bad data costs the US economy $3.1 trillion each year – Banish bad data by integrating your data sources and analyzing and presenting data in a mobile environment to gain insight into trends, opportunities, issues and problems and reveal clear, concise soluti

‘If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.’

Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.

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.’

Original Post : Mobile BI Tools Solve Many Enterprise Issues!

Smarten Support Portal Updates – January – 2025!

How to Choose the Right Low-Code/No-Code BI Tools and Analytics!

Be Sure You Choose the Right Low Code No Code BI and Analytics!

By some reports, the no-code and low-code development platform market is expected to grow from $10.3 billion in 2019 to $187 billion by 2030, reflecting a compound annual growth rate (CAGR) of over 31%.

No code Predictive Analytics, low code data analytics and No Code Business Intelligence Solutions provide numerous advantages and benefits to the enterprise and its users. To leverage predictive analytics and low code no code, the organization must choose the right vendor and the right solution.

Choose the Right Low-Code, No-Code BI Tools and Predictive Analytics Solution

As with any other software solution or business application, there are many factors and considerations that influence solution selection. Here we highlight some of the primary areas of focus your business will want to include in its vendor and solution review.

‘If you are ready to choose a business intelligence (BI) solution, with self-serve augmented analytics, LCNC and AI-enabled tools, we encourage you to find out more about the benefits of this approach, and the capabilities of our advanced analytics solution.’

Is the Solution Truly LCNC?

In this article, we have defined low-code and no-code development and how it fits within the business intelligence (BI) and augmented analytics environment. But it is important to remember that the low-code/no-code market of platforms and how this technology is integrated within analytics solutions will vary greatly. While some business intelligence (BI) and augmented analytics solutions do incorporate LCNC concepts, features and tools, not every solution or application can truly be called low code/no code. In short, some solutions have a minimal LCNC component and will require the skills of a programmer or developer to leverage their features and functionality. If you plan to roll out LCNC-enabled analytics to provide your business users and Citizen Data Scientists with tools, be sure that the analytics and BI tools you choose are truly LCNC-enabled with features that will allow your team to work on their own and use the solution on a daily basis to create, collaborate and make decisions. Avoid complex and highly-customized projects that will take time and money to complete and will require costly updates and upgrades when you wish to make a change.

Choose a Solution That Meets the Skills and Needs of Users and the Enterprise

By incorporating LCNC within analytics and BI tools, you can enjoy many benefits, but it is important to understand that low-code platforms are not suitable for all types of applications for analytics and BI or for business use cases. Depending on how you plan to use analytics within the organization, and on the use cases you develop to test solution capability, you may find that some solutions will not meet the needs. Low-Code components are not suitable for extremely complex or highly-customized analytics or BI projects and, depending on the solution and vendor, the solution may not be able to handle certain volumes or types of data or workflow i.e., big data or large-scale analytics. Standard low-code platforms are not always secure, because the generated code may lack the robust security controls and features normally seen in code written by a professional programmer or developer. Be sure that the solution you choose meets your needs for security, privacy and standards. Be sure that the solution you select leverages LCNC in a way that is appropriate for analytics and BI tools and applications.

Vendor Understanding of LCNC

As with all software programs, tools, techniques, platforms and frameworks, the capabilities of and features and functionality of a particular technology cannot be fully leveraged if the development team does not understand the full potential, restrictions and opportunities inherent in the technology. When you choose an LCNC-enabled analytics solution be sure you understand the skills, experience and capabilities of the development team responsible for designing, creating and maintaining the analytics solution. We often refer to LCNC as a drag and drop technology, but that does not mean that its incorporation and integration into a complex analytics solution should be taken lightly. There is much to be done to ensure that the technology is used appropriately and that the vendor has planned for the future with flexible, scalable solutions that will serve you well.

Solution Integrity

Is the business intelligence, augmented analytics solution built on a solid foundation of sophisticated analytics tools and techniques? LCNC should be used to enhance a solid product, not to mimic a robust solution. Be sure that the product and vendor have references and a history of providing analytics and business intelligence and that the solution you are selecting is not just a good looking front-end that has very little capability. Does the solution provide rich functionality and features with self-serve tools to leverage sophisticated algorithms and analytical techniques or is it a simple data gathering and reporting tool?

Roadmap for the Future

When a vendor incorporates new technology within its existing products, it must have an idea of where the product is going – a product roadmap that takes into consideration the new technology, how it may change in the future and how the product can and should be upgraded to take advantage of what is happening in a rapidly changing technology environment.

The future of LCNC will include expanded and enhanced artificial intelligence (AI) capabilities. For example, the concept of Unified Commerce Business Optimization System (UCBOS), a zero-code approach that is designed to enable digital transformation throughout the enterprise by connecting all systems, data and workflow. The technology world of the future will allow programmers to use natural language to describe what they need and their requirements for an app, and then translate that into functional applications, allowing developers to program using natural dialogue to create and upgrade software. While we are few years away from this future, it easy to see how application development, and the skills required of an app development team will have to change, and how the evolution of software and applications will involve a different process than it does today, employing human skills, creativity, and artificial intelligence to take on more routine tasks and processes. Be sure your vendor has a vision for the future of the analytics product and will continue to leverage LCNC, AI and other technologies and tools as they become available and as they are deemed appropriate and practical for business intelligence and analytics solutions.

There are other factors inherent in choosing the right LCNC-enabled analytics and BI tools. Here, we have provided some of the primary considerations for your review. If you are ready to choose a business intelligence (BI) solution, with self-serve augmented analytics, LCNC and AI-enabled tools, we encourage you to find out more about the benefits of this approach, and the capabilities of our advanced analytics solution.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

‘No code Predictive Analytics, low code data analytics and No Code Business Intelligence Solutions provide numerous advantages and benefits to the enterprise and its users. To leverage predictive analytics and low code no code, the organization must choose the right vendor and the right solution.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore our seamless Analytics Solution TechnologyDownload A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions,’ ‘What Is LCNC And How Does It Change The Analytics Market?’, ‘How Does LCNC Enhance BI And Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users And Citizen Data Scientists.’

Enhance BI Tools and Analytics with Low-Code, No-Code Development!

BI Tools and Analytics with Low-Code, No-Code Features!

Whether your team is currently using traditional business intelligence, or augmented analytics tools, or you are planning to implement your first analytics solution, it is important to understand the relevance of low-code and no-code development (LCNC) and LCNC features and techniques to your team and your selected analytics solution.

Analytics with business intelligence and low code no code go hand-in-hand. The solution you choose can and should include both standard BI tools and sophisticated augmented analytics.

The global technology research firm, Forrester highlights the complexity of existing technology environs, and the importance of supporting the business with agile, adaptable tools and workforce and suggests that low-code/no-code development allows organizations to accelerate innovation and increase business agility and sustainability.

‘By integrating this approach within the business intelligence and augmented analytics environment the business can eliminate the need for expert programmers and IT professionals and allow team members to perform simple analytical, reporting and visualization tasks and create and explore analytics without the assistance of consultants or IT staff.’

When we add a low code no code complement to this environment, we integrate simple technology that allows the analytics solution to keep pace with your changing organization while enabling data sharing and user adoption so the enterprise can produce fast, dependable insights and improve the value of business analysis across the enterprise, and democratize the use of advanced analytics.

How Can Low-Code, No-Code Development Enhance BI Tools and Predictive Analytics?

To further illustrate how low code and no code development can be leveraged in BI tools and analytics, let’s look at some examples of how LCNC can be integrated within the analytics environment to improve, enhance and innovate analytics features and functionality.

Data Preparation, Transformation and Cleaning

Connect to multiple data sources, clean and transform data using intuitive visual tools, wizards, data pipeline charts and configuration, without the need to create complex extraction, transformation and loading (ETL) scripts.

Data Visualization

A drag and drop smart visualization engine allows the user to select the best fit and most appropriate options to visualize a particular dataset based on data columns, types, data volume and other factors.

Self-Serve Reports, Graphs and Dashboards

The team can leverage self-serve tools and wizards with drag n’ drop features to create dashboards, reports and summaries, to pivot and unpivot data, to add columns, spot lighters, and other features to enhance and clarify data presentation.

Predictive Modeling

A wizard-based, guided user interface (UI) helps users to create predictive models with no need for IT intervention, and no programming or scripting experience. The system will suggest the best-fit algorithm for the data the user wishes to analyze and fine tune parameters to create accurate, appropriate predictive models.

Anomaly Alerts

Key Performance Indicators (KPIs) are configured with simple or complex expressions, thresholds and frequencies, using a wizard-based user interface (UI), so the team can achieve swift results without IT intervention.

Expressions

An easy-to-use expression engine leverages functions and syntax with examples and test/validation features for key performance indicators (KPIs), new columns and other areas where expressions are required.

BI Platform Administration

The Application Administrator is a 100% graphical user interface (GUI) system that allows for platform and application management without scripting.

User Access Rights and Permissions

Configure and manage user access rights without scripting or programming using a 100% graphical user interface (UI) approach.

Embedded BI

Optimize application integration with easy-to-use Application Programming Interfaces (API) to embed BI objects and predictive models within third-party applications, and perform administrative tasks including user management and user access rights management.

By integrating this approach within the business intelligence and augmented analytics environment the business can eliminate the need for expert programmers and IT professionals and allow team members to perform simple analytical, reporting and visualization tasks and create and explore analytics without the assistance of consultants or IT staff, thereby reducing dependency on data scientists and IT and enabling power users and Citizen Data Scientists.

In addition, the use of low code and no code techniques and platforms allows for improved performance, and provides the flexibility to address rapidly changing user and business requirements as well as allowing the solution vendor to quickly add features and upgrade the solution to keep it evergreen.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

‘Analytics with business intelligence and low code no code go hand-in-hand. The solution you choose can and should include both standard BI tools and sophisticated augmented analytics.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore  our seamless Analytics Solution TechnologyDownload A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions,’ ‘What Is LCNC And How Does It Change The Analytics Market?’, ‘Choose The Right LCNC BI Tools And Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users And Citizen Data Scientists.’

Low-Code and No-Code Development in Analytics!

Using LCNC in Augmented Analytics

Low-Code Development and No-Code Development have been getting a lot of press in technology publications and conferences of late. If you are interested in finding out more about this topic, and about how low-code, no-code (LCNC) can be used to enhance analytics and change the approach of the self-serve, augmented analytics market, this article will provide you with a primer.

‘Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Let’s begin with a Definition Of Low Code And No Code, and a discussion of the difference between Low Code And No Code Development.

What is Low-Code, No-Code Development and How Is It Used in the Analytics Market?

 

Low-Code Development

Low-Code Development allows programmers and developers to quickly and easily create applications using tools that simplify the development process with drag and drop components that enable the team to add features without writing code ‘from scratch.’ This visual development approach uses a graphical user interface (GUI) to support programmers as they build applications. To understand how this benefits the development team and the business, it is important to understand how low code platform works. By enabling swift development and mitigating the use of complex code, developers can easily add features to keep pace with the market and customer needs, so upgrades and iterations are fast and easy. The low-code platform is easy to integrate with existing systems, so it will support users of popular and familiar solutions with new features that are easy to use.

No-Code Development

No-Code Development requires no coding and is used to create simple, basic applications that can be quickly deployed and upgraded. The no code environment uses a graphical user interface (GUI) that is user-friendly and easy for developers to navigate. It supports developer productivity with easy-to-use tools and is less expensive than the typical software development approach, and it is easy to customize, though it is not scalable for complex application development and will produce only limited functionality. The no-code platform is fast and easy to use and provides an additional set of tools and an approach that will support programmer productivity and get products and upgrades to market quickly.

When considering the difference between low code and no code development, here is the bottom line:

Low-Code solutions use visual development environments and automated links to back-end systems, databases, web services and APIs.

No-Code solutions utilize visual drag-and-drop interfaces and require no coding, but rather are configured and implemented quickly, using the skilled application of tools and techniques.

The top low-code platforms are easy for developers to learn and the no-code environments have a library of pre-built components from which the team can choose.

World-renowned technology research firm, Gartner, predicts that low-code development tools will account for 75% of new application development by 2026. This prediction is primarily based on what Gartner perceives as increasing pressure for businesses to adapt quickly to market and competitive trends and changes.

The global technology research firm, Forrester highlights the complexity of existing technology environs, and the importance of supporting the business with agile, adaptable tools and workforce and suggests that low-code/no-code development allows organizations to accelerate innovation and increase business agility and sustainability.

Given the recent elevated status of low-code no-code in development and low-code no-code tools, it is important to consider whether the market has responded by adopting these techniques.

According to SlashData the use of LCNC has increased from 46% to 57% over a period of eighteen (18) months, with the usage of LCNC tools estimated at:

70% Data Science

66% Machine Learning

75% Embedded Software

69% Apps and Extensions for 3rd party ecosystems

58% Mobile Apps

Many businesses have employed LCNC to step up their competitive positioning and create and innovate quickly. Examples Of Low Code And No Code Business Innovation Include Amazon, Google, Apple, Akkio, DataRobot, and Microsoft.

When we consider the use of LCNC in business intelligence (BI) tools and predictive analytics, the reason for the uptick in usage among developers and IT professionals is quite clear.

As businesses embrace data democratization and recognize the need for data literacy among team members, and as enterprises launch Citizen Data Scientist initiatives, they face numerous obstacles and challenges, including the selection of an intuitive, self-serve BI and augmented analytics solution. Finding and choosing the right solution will drive willing user adoption, improved Return on Investment (ROI) and low Total Cost of Ownership (TCO).

But the selection of the right BI and analytics solution must also include considerations for sustainability, keeping pace with team, customer and market trends and changing behaviors, and ensuring that the technology investment will serve the organization in the long term.

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore our seamless Analytics Solution Technology.
Download A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development in Business Intelligence (BI) and Predictive Analytics Solutions,’ ‘How Does LCNC Enhance BI and Predictive Analytics,’ ‘Choose the Right LCNC BI Tools and Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users and Citizen Data Scientists.’