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.
Find Out the How of the Citizen Data Scientist Approach
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.
What Are the Benefits of Low-Code No-Code in Analytics?
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.
User Benefits
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.
Enterprise Advantages
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.’
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.
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.
‘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.’
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.
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.
‘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.’
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.’
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:
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.
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.’
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.
Avoid Complex Analytics Solutions (Your Users Will Hate)
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:
Search-based, self-serve analytics provides swift access to data and familiar natural language processing (NLP) search capability so business users can ask a question, get an answer and drill down to discover the root cause of issues. There is no need for the user to wait for IT or a data scientist to produce a report. They can continue to work on a task or a problem with full insight into results, challenges and possibilities.
The enterprise can enable data democratization and data literacy across the business landscape, thereby ensuring that there is a rapid response to market and competitive changes and to changing customer buying behavior.
Business users can leverage their industry knowledge and functional skillset and combine data insight with experience to produce the best results.
Intuitive, easy-to-use solutions help to combat user resistance and ensure user adoption. While there are always cultural issues surrounding this type of adoption and the perceived changes in responsibilities, when business users see the value of having crucial information at their fingertips, the enterprise can ease the transition and ensure user adoption.
No matter the role of the user, the team can enjoy the benefits of augmented analytics and make the transition to Citizen Data Scientists to improve collaboration, data sharing and fact-based decision-making.
The business can understand quality and maintenance issues, refine customer targeting and marketing optimization, and make appropriate financial investments, and they can analyze trends and patterns and make forecasts and predictions.
When the enterprise adopts these tools and techniques, they allow Citizen Data Scientists to perform analytics on a day-to-day basis and, where appropriate to effectively interact with and collaborate with the IT team and data scientists to refine data and prepare it for more strategic initiatives, so there is a seamless handoff from the business user to the analytical community, when and as necessary.
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.
The term, ‘Citizen Data Scientist’ has been around since 2016, when the world-renowned technology research firm, Gartner, coined the phrase. Whether you want to know more about the concept, understand the concept and would like to know if your business can leverage this approach to improve its market position and customer visibility, or you have embraced the Citizen Data Scientist approach and are looking for ways to expand and refine the concept within your own business environment, we are here to help.
As Gartner research states, ‘Early adopters of augmented analytics have the potential to realize more strategic and differentiating business benefits from their analytics investments than those who wait until these technologies are widely adopted.’
One of the most important aspects of any new, large scale initiative, is preparation and when it comes to the Citizen Data Scientist approach, preparation is equally important. Let’s look at some of the primary factors and considerations you must include in your planning process.
‘Will you deploy the augmented analytics solution across the entire enterprise at once, or will you roll it out by division, department, location, etc.? Who will be in charge of the deployment?’
Review Technology and Business Processes
Look at your current technology and all the places your data resides (data warehouses, the cloud (private or public), best-of-breed software, legacy software, ERP, CRM, HR, SCM, and other focused solutions that support a particular division, team or department. You will want to integrate data from all possible sources in order to give your users the information they need to perform analytics.
Work with your IT team, and (if you have already chosen an IT consultant) with your advisors to analyze the technology and infrastructure and establish a plan of attack. Consider the network, hardware and software, and decide whether you will want Embedded BI within any popular software solution to allow users to leverage a single sign-on environment to access data and analyze it all in one place.
Review business processes, workflow, approval loops etc., and see where you can gain advantage by including analytics and technology to improve productivity and the quality and speed of decisions.
Involving Stakeholders, Customers, Users, IT, etc.
Management and/or IT cannot plan for and execute this type of change alone. You will need to understand how cascading analytics throughout the organization will impact your users, your customers and others. Establish a team that includes representatives from the various functions, levels and areas within the enterprise.
Listen to their concerns and address those concerns with an appropriate plan for deployment, training, ongoing support, etc. Otherwise, you are unlikely to succeed. User adoption is important but you can also use this time to identify and highlight those areas where you can find opportunities and thereby improve the success metrics and outcomes you hope to achieve.
Choosing an Augmented Analytics Solution
Choosing the right augmented analytics and business intelligence (BI) solution will drive success of a Citizen Data Scientist initiative. These solutions are key to helping you achieve your goals and to supporting your business users as they make the transition to Citizen Data Scientists. Look for a full suite of features and functionality to support your users.
Not all augmented analytics solutions are equal! Be sure the solution you choose has all the features you need and will be easy for your users to learn and adopt. Look for a comprehensive solution suite that includes:
Will you deploy the augmented analytics solution across the entire enterprise at once, or will you roll it out by division, department, location, etc.? Who will be in charge of the deployment? Your team should include representatives from the various groups that have a vested interest in the outcome. When you choose an IT consultant, they can help you plan for and execute your strategy so that it is successful and you are not overwhelmed.
Depending on the solution you choose, you will have to consider citizen data scientist training. While there are citizen data scientist certification courses, if you choose the right augmented analytics solution you are not likely to need this type of training but, rather a simple introduction that will explain the new role, how to work with and collaborate with data scientists and IT and how to use the augmented analytics solution to get the information the business user needs in a way that is meaningful to them.
‘One of the most important aspects of any new, large scale initiative, is preparation and when it comes to the Citizen Data Scientist approach, preparation is equally important.’
A Citizen Data Scientist Initiative Can Optimize Data Scientists and Encourage a Data-Driven Culture!
According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. If your business wishes to accommodate a ‘data-first’ strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive professionals, or it can take a different approach.
‘Citizen Data Scientists can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.’
Citizen Data Scientists are business users who have a place on your team and are hired because of their professional and career experience in a particular industry, business function or discipline. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.
Depending on the size, market and industry of your business, you may choose to augment your staff with one or more data scientists to refine results produced by Citizen Data Scientists on a day-to-day basis. So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.
Whether you choose to employ the services of a Data Scientist, provide business analysts or IT professionals to support your business users, you can create a comprehensive foundation for analytics across your organization.
By democratizing data analytics you can achieve many benefits, including:
Improved Data Literacy Across the Enterprise
Improved Productivity of Data Scientists, IT and Business Analysts (who can spend time on strategic initiatives rather than producing daily reports)
Optimized Return on Investment (ROI) and Total Cost of Ownership (TCO) for all software and systems
Fact-Based Decisions and Metrics-Driven Strategies, Goals and Objectives
Team Member Career Advancement
Optimization of Resources and Improved Team Productivity
With these tools, the Citizen Data Scientist can leverage Natural Language Processing (NLP) and search analytics with machine learning to ask questions using simple human queries and receive insightful answers. They can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.
Citizen Data Scientists can predict customer responses to new product features, and to new marketing campaigns, analyze the likelihood of fraud or risk, identify supply chain issues, etc. These tools can also help the organization to foster collaboration and data sharing and encourage business users to innovate, create and explore opportunities using data-driven, factual information.
‘When Citizen Data Scientists are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.’
These are just a few of the factors you must consider when implementing a Citizen Data Scientist approach. Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and working at the leading edge of a new approach to collaboration and decision-making. initiative. Consider engaging an expert for your Citizen Data Scientist. IT consultants with experience and skill in this area can provide crucial support to help you succeed with your Citizen Data Scientist initiative and can provide simple Training Programs to bring your team on board and help them see the value to themselves and to the organization.
We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also disclose information about your use of our site with our social media, advertising and analytics partners.Accept Cookies
