Choosing Between Cloud and On-Premises Augmented Analytics
Your business may be upgrading a business intelligence solution OR it may be considering the implementation of business intelligence (BI) for the first time. Either way, you will be faced with numerous decisions as you navigate the augmented analytics market and look for the right product and solution for your team and your organization.
Considerations include pricing, features, ease-of-use, data storage and data management location, and the capability of the solution to support upgrade and growth. When it comes to the technical foundation of the product and services, you will need to decide whether to choose a solution that resides on premises or one that is cloud-based.
Perhaps the most difficult aspect of this decision is advanced planning and anticipating the changing needs of the organization. If you are choosing an advanced analytics product, a business intelligence or augmented analytics solutions, you may wish to select a vendor that allows you to choose an on-premises OR cloud-based approach, with the flexibility to change your approach in the future WITHOUT having to change the software your team has adopted – the one they now understand and use on a daily basis.
On-Premises: Software is hosted onsite using enterprise hardware and infrastructure. Some businesses choose this option because they wish to retain control and provide assured security.
Cloud-Based: When a business chooses this option, it relies on third-party servers to support the software and data and accesses information via secured internet connections using cloud. This option provides a flexible, scalable approach and allows the enterprise to access software and features without the need for its own resources, IT support, and hardware expense.
Gartner Has Predicted that, ‘Demand for integration capabilities, agile work processes and composable architecture will drive continued shift to the cloud.’
To choose the right solution, work with your IT partner, to consider:
Strategy for Business Growth
Industry, Government Security Compliance
Availability of and Access to Technical Experts
Ability to Easily Manage Data Sources, Data Access, etc.
Cost of Solution and Support and Maintenance
Performance, Scalability, Flexibility
Support for Upgrade, Future Needs, Digital Transformation (Dx)
Look for a flexible, low-code, no-code analytics platform with scalable technology infrastructure and architecture that offers on-premises, private cloud or public cloud implementation for Amazon, Microsoft Azure, Google Cloud and other options. Your IT consulting partner will help you decide on your approach based on data velocity, data sources and locations, data security and governance policies and your desired return on investment (ROI).
Why Adopt Mobile BI? Data Access and Data Democratization
The global business environment has changed dramatically. With employees working remotely, and even in other countries, it is mandatory to provide technology and tools your team can use to complete tasks and, hopefully, to add value to the organization on a daily basis.
If you have not yet adopted a business intelligence or augmented analytics solution, it is wise to consider one now. Your competitors are already implementing these solutions! If you HAVE adopted a BI tool or self-serve analytics solution, but you have yet to provide your team with mobile business intelligence, it is past time to consider this addition because your competitors area already implementing THESE solutions as well!
‘Out-of-the-Box Mobile BI can provide natural language search analytics, clickless analytics for quick, easy analysis, key performance indicators, dashboards and reports, dynamic charts and graphs, and intuitive visualizations, with self-serve features that are suitable for every user.’
According to Market Research Future studies, ‘The Business Intelligence market segmentation, based on Technology, includes Mobile BI, Cloud BI, and Social BI…’ This market is…’is expected to grow and expand during the projected timeframe as it will help businesses make data-driven decisions, boosting the overall market growth.’ This study estimates that the business intelligence market will grow from USD 33.12B in 2024 to USD 78.42B in 2032.
The reason for that growth is simple. Businesses, large and small, are discovering the value of fact-based decision-making, and the wise business owner, executive or manager understands that their competition is actively involved in improving productivity (to do more with less), in improving customer satisfaction (with targeted products and services), in decreasing re-work and increasing collaboration, and above all in increasing the data literacy of its team through data democratization, easy access to crucial data and improved user adoption of technology.
But the old methods of BI tool installation can no longer support strategic goals. Your team may be spread across countries, regions or cities. They may work in the field. They may be meeting with a client or a supplier. Any or all of these scenarios require mobile tools that provide your team with the information they need to make the right decision, to review historical data or transactions and work with others to create a pricing strategy, check on stock, understand customer buying behavior etc.
If you truly wish to make your team more productive and effective, it is crucial to give them access to data and the information they need to do their job, no matter where they are working (in the office or remotely). Easy-to-use, self-service tools ensure user adoption and can move your team members toward a Citizen Data Scientist role, with advanced analytics that is intuitive, interactive and flexible.
Out-of-the-Box Mobile BI can provide natural language search analytics (NLP), clickless analytics for quick, easy analysis, key performance indicators (KPIs) for metrics and results, dashboards and reports, dynamic charts and graphs, and intuitive visualizations, all designed for ease-of-use with self-serve features that are suitable for every user.
With these tools, your users can easily find and analyze information, working from anywhere, at any time of the day. They will not have to guess at information, or carry copies of old reports that are no longer relevant.
‘If you have adopted a BI tool or self-serve analytics solution, but you have yet to provide your team with mobile business intelligence, it is past time to consider this addition because your competitors area already implementing these solutions.’
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.’
The Client owns a leading specialty chain of pharmacy and wellness stores in Ahmedabad, India, providing pharmaceuticals, medications, and wellness products to the community and consumers. As a component of its business, it sponsors a popular customer loyalty program. The Smarten model demonstrated remarkable performance, achieving 98% accuracy in predicting customer churn on the testing dataset.
Whether your business wishes to implement its first business intelligence solution, or you wish to upgrade your solution to satisfy additional requirements, or your business divisions have diverse business needs, the RIGHT business intelligence and augmented analytics solution is crucial. To protect your Return on Investment (ROI) and reduce your Total Cost of Ownership (TCO), you must select a solution that will suit all your team members, and be flexible enough to grow with your organization and provide support now and in the future.
Gartner names 12 mandatory and common features of a comprehensive BI tool, which includes:
Data visualization
Governance
Reporting
Analytics Catalog
Data preparation
Data science integration
Automated insights.
Metrics layer
Data storytelling
Natural language query (NLQ)
Collaboration
Composability
For many businesses today, the decision can lead them down a winding path to the question: ‘Can I truly find one solution to suit all my needs and, if I can’t, is it possible to successfully combine and integrate more than one BI tool?’
Let’s take a closer look at these questions in an effort to help you understand the tradeoffs and the decision-making process.
Choosing ONE BI Tool
Benefits
Data Centralization – Team members can seamlessly access a single data solution
Provides a centralized, simplified platform for user management and access rights
Maintenance and Administration – The IT team has only one system to manage
Reporting – Dashboards and reports leverage one data model, and reporting formats and scenarios are uniform and interconnected
Ensures one focused, experienced IT and technical team
Challenges
Scalability – As your organization grows, you may have issues supporting an expanded user base and data volume
Performance Issues – For organizations with a large data volume, users may experience a lag in response time
Data Security – If your business has multiple business units, the administration of a single solution may be a challenge, as the model will require multi-layered, granular security and permissions
Constrains the business to one solution, with one roadmap for the future provided by one vendor
Choosing Multiple Solutions
Benefits
Scalability – Smaller, more modular solutions allow the organization to execute development independently without affecting other systems
Performance – User experience (Ux) for dashboards and reporting is likely to be better, with suitable speed and responsive dashboards and reporting
Support – Each independent module or solution can be supported independently without affecting other solutions
Challenges
Duplicate Data or Analytics – If proper architecture is not in place, the systems may duplicate data or analysis or a system may use the wrong model for reporting
Integration – Combining and integrating multiple systems requires a sophisticated roadmap to accommodate cross-functional reporting and analytics and data access
Continuity – Data mapping, distribution and consistency can be a challenge
User Management and Access Rights – It can be challenging to manage these processes across disparate platforms
Technical and IT – Multiple tools require expertise across all frameworks and platforms
These are just a few of the examples of benefits and challenges of the one vs. many approach of business intelligence solutions. While the temptation to consolidate and choose one tool can seem practical, the enterprise should consider the benefits and the challenges of each approach and compare them to their needs. Each tool may offer specific benefits that cannot be achieved by a one solution approach, and may better address user expectations and needs and satisfy the goals of the organization.
For a long time, the analytics industry has touted the idea of ‘best of breed,’ and there is a case to be made for choosing the ‘best’ for each scenario. Gartner’s most recent Magic Quadrant places 6 of 20 vendors in the niche quadrant and many of these niche vendors may offer solutions that meet a specific need within your own enterprise. So, don’t be too quick to eliminate the possibility of multiple solutions.
Many CIOs think that at standardization on one platform should always be considered at the enterprise level. While that approach has its advantages, it has lot of disadvantages too.
Advantages include:
One vendor, one relationship
Concentrated skill set within the team
A simple, uncluttered application landscape
Disadvantages include:
Commitment to one vendor (who may or may not be dependable)
Enterprise is confined to one vendor roadmap, limitations, upgrades and future development
One solution platform limits enterprise platform choices and flexibility
One tool may not satisfy niche or specific use cases across all divisions, departments and teams
While a one solution choice may work for a smaller organization or one without complex needs, you may wish to consider a balanced approach. When you strike a balance using a practical, limited best of breed approach, you can address the needs of specific business units or users. Be judicious about your choices, so as not to clutter the application landscape with too many applications and complicate your architecture.
You may wish to choose one solution for enterprise IT reporting, or one for smart data visualization for business users, or one that supports Citizen Data Scientists, or a tool that is focused on big data processing. Your assessments should be based on your use cases, user needs, license needs, budget, etc. While some organizations use as many as five (5) BI tools, the enterprise should limit their expansion to 2-3 tools in order to avoid chaos in integration, maintenance, the need for IT skills, costs etc.
While the assessment of needs and requirements for ANY software solution can be time consuming, it does pay off in the end and, especially if you are considering multiple BI tools, it is worth taking the time to thoroughly assess your needs so your business can create the ideal analytical landscape for IT, data scientists, business analysts and business users.
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.
Cross-Tab and Tabular Reporting Tools Are Foundational!
The evolution of advanced analytics has been rapid and impressive. With features that provide support for business users and help to transition them into Citizen Data Scientists, and the addition of Artificial Intelligence (AI) and other capabilities like Natural Language Processing (NLP) and search analytics, augmented analytics is suitable for every team member in your organization. It is easy to be impressed with all of the new bells and whistles and these additions certainly do make a user’s life easier and help the organization to analyze and use data in a more meaningful way.
But while we are admiring these new BI tools and analytics features and technologies, we should give equal respect to the bread and butter of the business intelligence (BI) and analytical landscape! Foundational, comprehensive visualization techniques are not only meaningful, they are mandatory.
‘With flexible views and report formats and interactive features and presentation capabilities, your business users, managers, IT team and data scientists can leverage data across disparate data structures and view and present that data with intuitive formats for fact-based decision-making.’
Analytics and business intelligence (BI) tools provide many such options including:
Cross-Tab – Cross-tabulation analysis (or crosstabs), analyzes and categorizes data to reveal the relationship between two or more variables to help you make sense of survey results, reveal actionable tasks, find patterns and correlations. Cross-tab analytics can be used for categorical variables (with independent or dependent variables), for contingency tables, marginal totals, or conditional frequencies, and many other purposes.
Tabular – Tabular visualization facilitates quick comparison of data in a tabular form, marrying data classification with data presentation to reveal measures and averages in a structured format that is easy to manipulate, compare and understand. Tabular analytics can be used for statistical analysis or units of measure among other uses.
According to research at the University of North Carolina (UNC), cross-tab and tabular analytics account for 90% of the analytical techniques used in all research analysis.
A BI reporting tool that enables users to customize their view and approach and is easy to understand and use will make the user more productive and ensure Return on Investment (ROI).
These foundational analytical visualization techniques are easy to understand and use and are suitable for business users and all team members. When you choose a Business Intelligence reporting tool that enables report, template and document design and configuration and supports preprinted fixed formats too. With flexible views and report formats and interactive features and presentation capabilities, your business users, managers, IT team and data scientists can leverage data across disparate data structures and view and present that data with intuitive formats for fact-based decision-making. IT team members or consultants can leverage a simple, basic programming or scripting environment to define format templates and use data from Datasets and objects to produce stunning pixel perfect reports. Users can preview reports, export data to PDF files and share documents and reports via email at predefined frequency using delivery and publishing agents.
‘While we are admiring new BI tools, features and technologies, we should give equal respect to the bread and butter of the business intelligence (BI) and analytical landscape! Foundational, comprehensive visualization techniques are not only meaningful, they are mandatory.’
Improve Results, Precision and User Adoption with Mobile BI
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:
Provide a native application with a seamless user interface that supports a great user experience (Ux) for ALL users (even those with average technical skills)
Be available for iOS and Android
Be suitable for self-serve analytics to encourage user adoption
Be easy to deploy and use
Provide good support
Be affordable
Provide support for data democratization and improved data literacy
Provide suitable return on investment (ROI) and total cost of ownership (TCO)
A mobile business intelligence (BI) app should not short change your users with restrictive formats or views. Look for a solution with:
Clear, flexible data visualization
Dynamic charts and graphs
Supportive dashboards and clear reports
Clickless analytics that are easy to use
Key performance indicators (KPIs) and metrics
Natural Language Processing (NLP) analytics that are intuitive and easy
‘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.’
BI Tools with Low Code No Code Development Provide Flexibility
What is Low-Code, No-Code development? Is it important for your business to understand its value and how it can be used in business intelligence? Well, if you are planning to upgrade your BI tools or invest in business intelligence (BI) for the first time, it is important for you to understand the components and how the composition of your BI tools can establish a solid foundation for growth and provide flexibility for change.
Low-code and no-code application development are methodologies for faster and simpler software development. The techniques use platforms and software to minimize code and enable drag and drop and other techniques to simplify and speed the development process.
‘The LCNC approach allows business intelligence vendors to create, configure, integrate, deploy and support BI tools at a lower cost, reducing the cost of the solution and ensuring that your team can transition to a Citizen Data Scientist role.’
According to a recent study:
No-code and low-code platforms help reduce app development time by 90%.
70% of new business applications will use low-code/no-code technologies by 2025.
Gartner forecasts that low-code adoption will be so widespread that 75% of the software solutions built around the globe will be made with the help of such tools.
So, why would this be important to YOUR business?
First, the flexibility and speed provided by Low-Code, No-Code (LCNC) development will allow your vendor of choice to quickly and easily respond to the market and provide new features and functionality.
Secondly, the ease of development allows developers to customize and personalize to respond to your needs.
When Low Code and No Code techniques are applied to business intelligence and augmented analytics solution development, there are numerous advantages. Here are just a few:
Application Development – The low-code, no-code approach reduces the time involved in application development, providing features and functionality to support user needs, supporting data visualization, reporting and a seamless user experience (Ux).
Solution Flexibility – LCNC development allows the development team to achieve flexible data construction and to easily integrate data from disparate data sources, producing an intuitive dashboard view and reports for users, so your team can use advanced analytics without advanced technology skills. Your enterprise can enjoy personalized dashboards and views that are suitable for the team, department, division, etc.
Building for the Future – Low code no code development allows the vendor development team to produce rapid results and to build in flexibility for the future, so BI software can keep pace with the market, with business needs and with your users. This approach allows the development team to support analytics, reporting requirements, data visualization, and data integration and modeling.
Productivity and Resources – Because this approach supports rapid development and creates a responsive environment, business owners and managers can work with the vendor and development team to address new business requirements, support team members with easy-to-use tools and anticipate changes in their competitive landscape with features and functionality that support workflow, business processes and user productivity.
Total Cost of Ownership (TCO) and Return on Investment (ROI) – The LCNC approach allows business intelligence vendors to create, configure, integrate, deploy and support BI tools at a lower cost, reducing the cost of the solution and ensuring that your team can transition to a Citizen Data Scientist role, thereby holding costs for data scientists, etc. The BI tools included in the technology stack will be affordable and provide a solid foundation for cost-effective growth.
‘The flexibility and speed provided by Low-Code, No-Code (LCNC) development will allow your vendor of choice to quickly and easily respond to the market and provide new features and functionality.’
What is Low-Code, No-Code development? Is it important for your business to understand its value and how it can be used in business intelligence? Well, if you are planning to upgrade your BI tools or invest in business intelligence (BI) for the first time, it is important for you to understand the components and how the composition of your BI tools can establish a solid foundation for growth and provide flexibility for change.
To learn more about the use of Low-Code/No-Code Development in augmented analytics and business intelligence tools, explore our free article, ‘Low-Code, No-Code In Analytics.’
Find out how to ensure Return on Investment (ROI) and Total Cost of Ownership (TCO) results, gain a competitive market advantage, and enable user adoption, read our free White Paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’ Explore The Benefits of our Augmented Analytics And BI Tools, Contact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.
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.
Improve Data Visualization – Create interactive dashboards, graphs and charts to help users present and share data in a way that is meaningful to a particular audience, and to clearly present data for confident decision-making. It can recommend and suggest visualization techniques to improve and refine how data is presented.
Improve Analytics with Task Automation – Automate activities and tasks, using customized automation scripts, and baseline filters and rules to extract and present data that meets user parameters. It can schedule and produce repetitive reports, and scripts can be altered change parameters, thereby freeing users to perform other operational or more strategic activities.
Predictive Analytics – Create predictive models using self-guiding UI wizard and auto-recommendations for swift, effortless forecasting and predictive analytics using data from numerous data sources.
Natural Language Processing (NLP) – Expand the capabilities of text generation and human language processing. It can enhance low resolution images, recognize and synthesize images and generate images for creative presentation of data and information.
Auto Insights and Machine Learning – Automates the process of interpreting and presenting results using rich visualization techniques, and includes all salient details, so users can review, share or edit content as they please.
Automated Alerts – Analyze results and trigger and generate alerts to protect against security violations, fraud and other risks, by analyzing normal behavior and results and comparing it to current and real-world results to identify anomalies.
Reporting – Using visualization, graphs, images and combining those with summaries and details can provide reports and presentations that are clear and suitable for all audiences, including management and executives, as well as teams and staff members.
Interpretation and Summarization – Quickly interpret and summarize data without spending a lot of time creating content, editing and preparing.
Data Preparation – Improve data transformation and cleansing and help prepare data and improve the quality of that data using phonetics for clustering, identifying data types, and hierarchies, suggesting alternate values etc.
Support for Citizen Data Scientists – Use AI cutting-edge tools to support team members with sophisticated, intuitive tools that leverage artificial intelligence (AI) and analytical techniques to produce concise results without requiring the skills of Data Scientists.
The analytical solutions market is moving quickly to adopt Artificial Intelligence and if your business wishes to succeed, it too must move to find and improve products and services as quickly as possible to meet customer expectations and to satisfy the ever-changing landscape of business competition.
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