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Two things are true today. The first is that we are a mobile society, tied to our devices, carrying them with us everywhere to stay connected, to get information and to communicate. The second true thing is that we are busier than ever and, if we are to keep up, we must find ways to be more productive. The advent of technology and the rapid pace of change has created a situation where there is always more to do than we have time to do!
When it comes to business, both of these true things are even truer! If we are a business owner or manager we know that we never have enough resources or staff and that the invaluable knowledge of our employees and professionals must be leveraged and optimized if we are to succeed. We also know that most companies today have team and staff members who are not working within the walls of a manufacturing plant or an office. Even in a retail business, our team members are often working after hours or they are on the road visiting suppliers or buyers.
That’s where mobile business intelligence (BI) comes in! Every business needs analytics and data to understand where the business is today, where it is going and what we need to do to keep the business moving on the path to success. But, information is everywhere and it can be difficult to gather it and make sense of it and use it to make decisions.
‘A mobile business intelligence (BI) app should not short change your users with restrictive formats or views.’
By integrating enterprise data and making it available in an easy-to-use mobile interface, you can allow every user in the enterprise to use data in a way that is meaningful to them and to their tasks and decisions and if that analytical solution is available on a mobile device, we enable them to be productive in airports, hotels, at client or supplier offices and while working at home.
According to a recent study by Mordor Intelligence, the fastest growing mobile BI market is in the Asia Pacific region and the largest market is in the United States.
If you are interested in expanding your business intelligence solution to a mobile environment, or in acquiring BI tools for your team, the right Mobile BI solution will:
A mobile business intelligence (BI) app should not short change your users with restrictive formats or views. Look for a solution with:
‘By integrating enterprise data and making it available in an easy-to-use mobile interface, we allow every user in the enterprise to use data in a way that is meaningful to them and to their tasks and decisions.’
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,’ and take a moment to watch and listen to this informative webinar, ‘Smarten Mobile BI.’
Original Post: Mobile BI is Not Just Nice to Have – It’s Crucial!
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.
By some estimates, bad data costs global organizations more than five trillion USD annually, and at the enterprise level, the quality of data can be a burden on IT, analysts and business users and acceptance of bad data can be inherent in business processes. Improving the overall quality of data increases confidence in decisions, reporting, strategies and the adoption of dependable analytical models across the organization.
When a business implements Data Quality, Data insight and Data Quality Management tools and techniques it can establish a comprehensive process with a solid set of tools to identify errors, enhance data quality, and boost productivity. Business users can leverage intuitive tools to uncover hidden insights and improve the overall quality of data with actionable recommendations to take prompt action.
Data insight takes data to the next level by providing comprehensive data analysis and quality assurance features that empower business analysts and users to quickly and easily identify errors, enhance data quality, and boost productivity. The business can harness the power of statistics and machine learning to uncover those crucial nuggets of information that drive effective decision, and to improve the overall quality of data. This approach allows users to let the system do the work for them and make confident decisions.
A foundational augmented analytics solution with machine learning, natural language processing and automation within an advanced analytics solution suite can improve results and support its team with augmented analytics designed as self-serve solutions for business users. Users can gather and analyze information with assurance of sustained data quality and produce results that are clear and concise.
Advanced data management features ensure data quality and provide crucial data insights with tools like Column Analysis, Feature Importance, Missing Value Analysis and Observations. Tools that support data insight include numerous data quality management techniques. These tools allow users to see and work with datasets in a way that is targeted and provides clear, actionable information for decisions and strategies.
If your business wishes to improve the easy of analytics and Quality Of Its Data and achieve data insight in a timely, dependable manner, find out more by watching this free Smarten Webinar: ‘Improving Data Quality With Data Insights,’ and read our free blog article, ‘Balance Data Quality With Data Agility.’ Explore our Smarten Augmented Analytics Products And BI Tools.
Original Post : Use Data Quality and Data Insight Tools to Avoid ‘Bad Data’!
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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.
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.
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!
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.’
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!
We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.
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If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!
Original Post : Smarten Support Portal Updates – March – 2025!
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?
This Client is a global telecommunications infrastructure provider, offering comprehensive end-to-end solutions for wireless network planning, optimization, and performance management. It offers services to over thirty (30) Tier 1 and Tier 2 telecom operators and Original Equipment Manufacturers (OEMs) worldwide, and excels in advanced 5G NR and LTE-A technologies as well as legacy networks. Business services include RF Planning, Optimization, Quality of Service (QoS) Benchmarking, In-Building Solutions, and skilled Manpower Deployment to provide seamless execution across diverse environments. The Client operates in more than fifteen (15) countries and spans five (5) continents.
