The Client is a leading electric mobility company in India, specializing in high-performance electric two-wheel scooters engineered for sustainable urban transportation. With a robust presence across 200+ cities, the organization leverages lithium-based battery technology, and advanced electric powertrain systems that are tailored to accommodate Indian road conditions.
The world of data scientists and business analysts is chock full of data and busier than you might expect – especially today! Businesses have discovered the value of data in decision-making and, as markets and competition shift and change, these businesses have come to depend on IT staff and on data scientists to provide data to make decisions at the department, divisional, operational and strategic level.
The problem is, as always…TIME! There aren’t enough analysts and data scientists, the IT team is busy working on other tasks and the clock does not stop ticking.
And there is one other factor at play in the data analytics movement. As data democratization and data literacy drive the enterprise strategy and business users begin to leverage augmented analytics and business intelligence (BI) tools, the data scientist is also called upon to refine and present analytics and reports created by team members in order to ensure that these are appropriate for more strategic decisions.
The world-renowned technology research firm, Gartner, states that, ‘Data Scientists typically spend more than 40% of time in preparing and enriching data.’
Imagine what you, as a data scientist could do with a data analytics solution that can save time on data preparation and data enrichment!
‘When an enterprise includes data scientists, business analysts and IT staff in the roll-out of augmented analytics and self-serve BI tools, it enables productivity, streamlines and speeds the analytical process and improves results.’
You have the tools and systems for data extraction, transformation and loading (ETL), you have scripting tools like R, you have spreadsheets and more, but using all of those tools to gather, analyze, scrub and present that data takes time.
As a Data Scientist, you have the responsibility and accountability to produce reliable analytics to satisfy all manner of needs within the organization. You never know what corner of the enterprise might need your services but you DO know that your analysis and services must be 100% accurate and dependable. When business users depend on you to produce information on a day-to-day basis, it is nearly impossible to focus on the more strategic, crucial imperatives.
When an enterprise includes data scientists, business analysts and IT staff in the roll-out of augmented analytics and self-serve BI tools, it enables productivity, streamlines and speeds the analytical process and improves results. Data Scientists can optimize time and resources and to use their core expertise to achieve results. Data Scientists can use self-serve data preparation, to quickly create datasets without deep SQL or ETL skills, and they can use smart data visualization and tools to use output of algorithms in R, Python or other Data Science platforms to leverage existing investments in these technologies, and they can create and roll-out predictive models in a production environment to support the organization and business user needs.
‘Imagine what you, as a data scientist could do with a data analytics solution that can save time on data preparation and data enrichment!’
As business users create analytics for quick decisions and the organization needs to refine this analysis for strategic use, a data scientist can use the same augmented analytics tools to focus on that project and ensure accuracy, collaborating with Citizen Data Scientists and IT to align analytics with key objectives and goals.
With the time your Data Scientists will save, they can focus on the most critical strategic initiatives and move the enterprise forward with fact-based decision-making.
To learn more about Augmented Analytics that are suitable for data scientists, business analysts, IT staff and business users, and explore the potential of Advanced Reporting Tools, Contact Us now.
The Client is a prominent engineering company in India, renowned for its extensive history. For over 160 years the Client has delivered bespoke design engineering and precision manufacturing solutions, specializing in enabling seamless motion across industries that include automotive, agriculture, marine, light construction, firefighting, and railways. The Client provides cutting-edge power solutions for critical installations and diverse applications, with expertise in fuel-agnostic engines and precision manufacturing of key engine components. It has expanded offerings in electric power train for mobility and other industrial power applications and a strengthening position in the motion control solutions space with strategic acquisitions, empowering progress across multiple sectors. The Client business is publicly traded on the National Stock Exchange of India (NSE) and the Bombay Stock Exchange (BSE) and a robust distribution network including 200 distributors, 8000 retail stores and 20,000 mechanics across India.
In 2016, the technology research firm, Gartner, coined the term ‘Citizen Data Scientist,’ and defined it 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.’
‘When business users make the transition to Citizen Data Scientists with access to augmented analytics solutions, they can provide additional value to the team, to managers and executives and allow IT and data scientists to focus on strategic goals.’
In the ensuing years, the Citizen Data Scientist role has become more refined, and those businesses that embrace this approach have seen real benefits. But just who are Citizens Data Scientists, and how does a business recognize candidates and benefit from enabling this role?
How Do I Find Citizen Data Scientist Candidates Within My Business? You will find your Citizen Data Scientist candidates among your business users and team members. They are curious and eager to learn new skills to contribute to the organization and to hone their skills for career advancement. Team members who make great Citizen Data Scientists are often power users, and are acknowledged as leaders within their own team. They are NOT IT professionals, analysts or data scientists but they share a common characteristic for precision and wanting to get it right the first time.
What Does a Citizen Data Scientist Do? Within the context of their roles and responsibilities, every business user needs clear, meaningful information to make fact-based decisions and recommendations. Citizen Data Scientists use data to create reports on a daily basis. As the Citizen Data Scientist role evolved, team members have leveraged the advantages of this data to share reports, to create and format presentations for recommendations and suggested changes to support pricing decisions, hiring, production, new products and services, financial investments, marketing and advertising campaigns, and many other decisions. As the movement grows within your organizations, you can enable data democratization and improve data literacy. Citizen Data Scientists can also work with IT, data scientists and business analysts to share their research and analytics when the business feels it is necessary to take the analytics to another level to ensure credibility for strategic decisions.
What Tools and Training Does a Citizen Data Scientist Need? One of the primary reasons the Gartner predictions have come to fruition is he evolution of the business intelligence (BI) and augmented analytics market to support the concept of Citizen Data Scientists. Today’s analytics solutions are easy-to-use, self-serve tools driven by Natural Language Processing (NLP), and machine learning, as well as Artificial Intelligence (AI). All of these technologies come together to support the business user and provide tools that are sophisticated in their functionality, yet intuitive and easy for a business user. These tools do not require IT skills or data science knowledge. When the team uses these tools, they can adopt a common language and techniques to work with IT and data scientists to create use cases and refine and share reports, formats and outcomes. The more complete, and intuitive the solution, the less training and onboard time the user will require. There are simple, Free Training Courses available that can help your business and your team understand the uses and benefits of this approach and enable user adoption.
When business users make the transition to Citizen Data Scientists with access to augmented analytics solutions, they can provide additional value to the team, to managers and executives and allow IT and data scientists to focus on strategic goals. Using Augmented Analytics Tools like self-serve data preparation to gather and prepare data, and smart data visualization to receive suggestions and recommendations on how to best view data, users can combine predictive analytics to forecast and model, and sophisticated tools like anomaly monitoring, key influencers, and sentiment analysis to gain crucial insight into changes in customer buying behavior, supplier issues, product time-to-market, trends, patterns and opportunities with dependable metrics to make data-driven decisions.
‘The Citizen Data Scientist role has become more refined, and those businesses that embrace this approach have seen real benefits.’
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.
Original Post : Is the Citizen Data Scientist Approach Right For My Business?
Research indicates that, ‘within the next several months, 65% of Application Development Will Be Done Using No-Code Platforms.’
Here, we discuss the benefits of LCNC-enabled analytics, no code business intelligence benefits and employing analytics and low code no code for teams, business users, Citizen Data Scientists and, ultimately, for the enterprise.
‘LCNC analytics enhances workflow and automates business processes across systems and data repositories to improve process uniformity, user and management communication, efficiency and productivity.’
What follows is a list of the primary benefits of Analytics With A Low Code No Code Component. There are many other advantages to this approach, but this list will give you an idea of how this simplified development process can have a positive impact on your organization and your staff.
Data Creation vs. Data Consumption – When a team member or business user is presented with self-serve analytics, the user will often see the new tool as less of an opportunity and more of a burden. By providing augmented analytics with LCNC-enabled features, the team can easily incorporate useful tools into day-to-day tasks. They can create, share and collaborate and the value of analytics will become clear to them, thereby enabling user adoption. Your team will advance beyond consuming data created by IT staff to conceiving, creating and sharing data and making the transition to Citizen Data Scientists, thereby reducing dependency on the IT team and freeing IT to focus on more strategic issues.
Fact-Based Decision-Making and Data literacy – LCNC-enabled analytics and BI tools creates an intuitive data exploration environment that is accessible and easy to navigate, so the team can create real-time insights, collaborate, present information to management teams and work in an agile environment, incorporating analytics within day-to-day workflow to make data-driven decisions.
Empowering Users – The low code, no-code analytics approach enables team members with tools that allow for data visualization, data preparation, predictive modeling, and the Use Of Analytics to create reports, dashboards and data visualization. Data is presented in a way that is meaningful to each user, no matter their business function or their technology experience. Users can quickly respond to customer needs, market changes, and management directives and goals without the assistance of IT team members, thereby freeing the team to adapt and address issues quickly, and optimizing the IT team and resources. The user is empowered to use data in a way that allows them to leverage domain, industry and business functional knowledge, making them more independent and encouraging them to become power users. Analytics with LCNC platforms allows users to leverage dashboards and reports and dashboards that incorporate data integrated from disparate systems, without complex data preparation and coding.
Personalization and Customization – Low-code, no-code supports an intuitive drag and drop environment with pre-built components, so the organization and its users can create custom views, visualizations and tools to support the needs of a team, a business function, or a particular user, so users are not limited to restrictive reports, dashboards, visualization and tools. Because every business and every user is different, the ability to personalize and customize workflow to support user needs is key to user adoption and to successful use of data, and meaningful interpretation of data.
User Adoption – When an enterprise invests in business intelligence and analytics, it must ensure user adoption in order to make the most of its investment and its analytics strategy. By employing LCNC-enabled analytics, the organization ensures that users will WANT to use the selected solution to complete tasks and follow business processes and workflow to complete approval processes, present data, and increase the value of each team member’s knowledge and skill for the organization.
Enable Citizen Data Scientists – Create an environment where business users can thrive and become Citizen Data Scientists with solutions that are easy-to-use, intuitive and can quickly produce results and data insight that will enhance the team value to the organization.
Improved Return on Investment and Total Cost of Ownership – The deployment of analytics and BI tools with LCNC components improves Return on Investment (ROI) and Total Cost of Ownership (TCO) by increasing user adoption, improving productivity and decreasing the time it takes to make a decision, and by leveraging the skills and knowledge of your team, as well as optimizing the time of your IT team and data scientists by redirecting their attention to more strategic issues.
Responsive to Changing Workflow and Technology Environs – LCNC analytics enhances workflow and automates business processes across systems and data repositories to improve process uniformity, user and management communication, efficiency and productivity. It improves team collaboration, so the business can make the most of its technology and human resources. LCNC is flexible and agile and can help the enterprise to respond to changes in technology and changes within the business environment.
Scalability and Governance – Governance, security and scalability are all important aspects of technology management. To protect its interests, mitigate risk and establish best practices, the enterprise can use the capabilities and backend components of its analytics solution to build appropriate frameworks, create policies and best practices, and build an integration strategy to support LCNC analytics within existing systems.
Cost vs. Productivity – When the enterprise chooses LCNC analytics and BI tools it can leverage low-code/no-code platforms to reduce reliance on programmers and developers and allocate those resources to more strategic projects. By encouraging collaboration among users and with IT and Data Scientists the business can leverage business, technical and other specialized knowledge and encourage innovation, data democracy and data literacy to drive enterprise efficiency and growth.
Data Integration and Embedded BI – LCNC analytics allows for ease of data integration among data resources, with APIs and pre-built connectors so the enterprise can easily integrate data from ERP, CRM, HRM, finance, SCM and other systems with no complex coding required. LCNC components allow for ease of data integration visual tools to map and transform data from disparate sources and systems so the organization has a comprehensive view of data and can gain valuable data insight. Embedded BI and analytics components can further enhance user adoption and enterprise ROI and TCO by integrating analytics within familiar and popular business applications.
Preparing for the Future – The Future Of No-Code And Low-Code within BI tools and analytics solutions is promising. Current and future development in Artificial Intelligence (AI), and Machine Learning (ML) will enable further expansion of LCNC capabilities. As these tools become more intuitive and adaptive, the enterprise will see more advantages. Users and businesses will enjoy a more personalized experience, more seamless contextual awareness and more responsive user interfaces for data preparation, predictive analytics, data visualization, and clear, concise dashboards and reports. The business will enjoy more personalized guidance, more refined data insight and more targeted data analytics to support the future of the enterprise.
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.’
‘There are numerous benefits of LCNC-enabled analytics and employing analytics and low code no code for teams, business users, Citizen Data Scientists and, ultimately, for the enterprise.’
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,’ ‘What Is LCNC And How Does It Change The Analytics Market?’, ‘How Does LCNC Enhance BI And Predictive Analytics,’ and ‘Choose The Right LCNC BI Tools And Predictive 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.
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.’
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.
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.
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.
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?
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 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,’ ‘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.’
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.
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 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,’ ‘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 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.
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 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.’
When a business decides to undertake a data democratization initiative, improve data literacy and create a role for Citizen Data Scientists, the management team often assumes that business users will be eager to participate, and that assumption can cause these initiatives to fail.
When a business is considering a business intelligence or analytics solution, it is important to recognize that today’s solutions are very different than the solutions of the past. Not only do they include more analytical techniques and features, but they have come a long way in providing access to sophisticated analytics for the average enterprise team member.
Harvard Business Review Analytics Service reports that
a) businesses can substantially improve business performance by giving frontline workers modern self-service analytics tools to enable fast intelligent action and,
b) not all self-service analytics provide this effective approach.
The Harvard Business Review Analytics Service surveyed nearly 500 executives and found that they reported significant performance improvement when they empowered frontline workers with augmented analytics. More than one-third of those surveyed noted improvement in customer and employee engagement and in product and service quality.
While some businesses may still be using business intelligence and analytics that are designed for data scientists and IT professionals, most of those are actively working to upgrade and/or migrate to augmented analytics and solutions that are designed for self-serve business user access.
Here’s why:
When the business is ready to acquire augmented analytics or to upgrade from existing, more restrictive solutions designed for professional analytical resources, it is important to choose the right solution – one with sophisticated tools that are presented in an intuitive user interface with auto-suggestions and recommendations to assist business users, and ample personalization of dashboards and reports.
With the right IT consulting partner, you can select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities, and ensure that every user can leverage these tools, no matter their skillset or technical capabilities. Explore our free white paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI Tools.’
