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.
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.’
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.
If you are a business executive or an IT professional, you have probably seen a number of articles about the importance of Business Intelligence in industry publications and trade journals. If you are still unconvinced or uncertain about the critical importance of business intelligence (BI) and analytics for businesses like yours, here are some sobering, surprising and impressive statistics to ponder.
The global business intelligence adoption rate is 26%.
Organizations use 4 or more different business intelligence tools on average.
Organizations leave 97% of gathered data unused.
74% of employees feel unhappy or overwhelmed when working with data.
Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not.
Bad data costs the US economy $3.1 trillion each year.
When you review these statistics, you will notice that some of the issues described can be resolved by the careful selection of the right software and solutions to satisfy your business, your team needs and your data infrastructure.
If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.
‘Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.’
The right mobile BI tools can address the issues and statistics listed above in the following ways:
The global business intelligence adoption rate is 26% – Mobile BI tools will increase the user adoption rate by providing intuitive data analytics that users can access from anywhere at any time, making these tools an important part of each team member’s tool box.
Organizations use 4 or more different business intelligence tools on average – The right mobile BI solution can integrate data from disparate data sources, and allow users to visualize in a way that is meaningful to each team member. It can optimize technology infrastructure and mitigate the issue of data silos and complex data mining and data gathering.
Organizations leave 97% of gathered data unused – Data is often misunderstood, misused or unused simply because team members and the enterprise do not know how to leverage, gather and analyze the data, or because the IT and/or data science team is short on resources and does not have the time to produce reports. Mobile BI tools are designed to be used by business professionals on a daily basis and to encourage data literacy and data democratization across the enterprise.
74% of employees feel unhappy or overwhelmed when working with data – Understand and address your business user concerns and make data more accessible, easier to understand and use, concise and clear, so that every user can optimize data, make confident decisions and share and collaborate without data science skills or sophisticated data analytical experience.
Businesses using business intelligence are 5 times more likely to reach faster decisions than those that do not – Improve productivity, time to market and return on investment (ROI) and total cost of ownership (TCO) to gain a competitive advantage with mobile tools and easy-to-use techniques that will enable fact-based decisions.
Bad data costs the US economy $3.1 trillion each year – Banish bad data by integrating your data sources and analyzing and presenting data in a mobile environment to gain insight into trends, opportunities, issues and problems and reveal clear, concise soluti
‘If you are planning to acquire or upgrade a business intelligence or analytics app or solution to provide self-serve augmented analytics for your business users and improve productivity, access and data sharing, you will want to include the review of mobile business intelligence solutions in your requirements.’
Mobile business intelligence (BI) solutions improve user adoption, ensure access to data from anywhere and encourage the use of data-driven information across the enterprise.
If you want to support your business user team and provide a foundation for BI tools that will better serve your team and your customers, explore Smarten Mobile BI benefits and features, with powerful functionality and access for your business users including out-of-the-box Mobile BI and advanced analytics for every team member. For more information on Mobile BI and Augmented Analytics, read our article, ‘Mobile BI Business Use Provides Real Advantages.’
DeepSeek Reveals the Potential for India’s AI Market
The shock waves from the DeepSeek announcement in the artificial intelligence (AI) space are still being felt. As AI technology businesses, software developers and consumers digest the new reality, there is no doubt the market will shift, adapt and change in a drastic way.
At the heart of this change is the Chinese company, DeepSeek, a new venture that has achieved a significant breakthrough in inference speed, leapfrogging over previous, world-renowned AI models like OpenAI, and causing a massive derailment of chip-maker Nvidia’s stock by proving that lower-end chips can be used to achieve high-performance results in the AI space. This open-source market entry has radically changed the U.S. and global market and, in so doing, it has also changed the mindset of AI developers and investors in other countries, including India.
Prior to the DeepSeek announcement, the prevailing AI strategy was a scenario in which a business required a huge capital investment to build Large Language Models (LLMs) for training and to fund massive processing capabilities and a huge talent pool for development. That meant government support, and an industry and environment to achieve these multi-billion dollar investments and goals.
DeepSeek built an AI product for less than ten million USD, with only 200 engineers.
That reality has shifted the India AI landscape by proving that the India software industry can move beyond an AI app focus to create base models and fully functional concepts. In fact, India has done it before! In defiance of all common expectations, India’s ISRO space program reached the moon at a fractional cost of the U.S. NASA program.
So, why not now? India (and other countries) have often watched from a distance as their own technology talent developed the best and brightest applications in the U.S. Today, the India government has the opportunity expand the capabilities of AI within the country, going beyond chatbots and AI contextual applications to leverage the technology talent within its borders and Create Solutions For Government, Agriculture And Other Industries.
The media and industry publications like to use the word ‘gamechanger,’ but in this case, the revelation of DeepSeek is a gamechanger in the true sense of the word, especially for India. The government is now supporting the new concept of AI evolution and development with the acquisition of 10k GPUs to support development and building the infrastructure to roll out AI models in India within 4-6 months. Yes, it’s possible!
Union IT Minister Ashwini Vaishnaw recently announced that, ‘the planned compute facility (cloud-based servers that are geared to run and handle AI inference), Vaishnaw stated that it has exceeded initial expectations with the country securing more than 18,600 GPUs. Among these are 12,896 Nvidia H100 GPUs, 1,480 Nvidia H200 GPUs, and 742 AMD MI325 and MI325X GPUs. Originally, the target was to procure 10,000 high-end AI chipsets. “DeepSeek AI was trained on 2,000 GPUs, ChatGPT was trained on 25,000 GPUs, and we now have 18,000 high-end GPUs available,” the IT Minister said.
As the technology market evolves, we can expect to see more changes, and those changes will come faster and more frequently. DeepSeek is just one example of the need for India to establish a nimble, adaptable approach that will respond quickly to new developments and identify the opportunities for growth and application of these developments in the global and local market.
The game is changing, and India no longer needs to defer to the U.S. or other countries in the AI market or in the use of its own development talent and investment infrastructure. It can build an ecosystem that will stand on its own without deference to other market leaders.
As IT Minister Vaishnaw said, ‘India will offer the cheapest compute in the world at less than $1 per hour for high-end chips that power generative artificial intelligence (GenAI) as the government’s ₹10,000 crore IndiaAI Mission comes into play….’
There is much to research, investigate and understand about the most recent DeepSeek development. But it does prove one thing. We do not need complacency or acceptance in technology. We need innovation, and India is up to the challenge!
Mobile BI Business Use Illustrates Real Advantages!
Mobile Business Intelligence (or Mobile BI) is defined as ‘a system comprising both technical and organizational elements that present historical and/or real-time information to its users for analysis on mobile devices such as smartphones and tablets (not laptops), to enable effective decision-making and management support, for the overall purpose of increasing firm performance.’
Aberdeen Group reports that businesses adopt Mobile BI to:
Improve business process efficiency
Improve employee productivity
Make better decisions, more quickly
Provide better customer service
Deliver real-time bi-directional data access to make decisions anytime and anywhere.
‘Mobile BI benefits go well beyond simple reporting and the sharing of data across user groups, to address real business issues and to keep users up to date and allow them to respond to real world, real-time issues.’
As local and global competition increases, most businesses are looking for ways to improve their competitive advantage, and to quickly adapt to the changing market, to employee needs and to customer buying behavior.
It can be helpful to consider some real-world business use cases, in order to understand the value and benefit of incorporating a Mobile BI solution within your technology landscape and your analytics approach.
The advantages of Mobile BI go beyond team collaboration and individual reporting needs, to provide the background and foundational information needed to make decisions on business strategy and to understand customer preferences.
The following list of companies represents a small sampling of businesses currently using Mobile BI to improve business results and efficiency:
Amazon – Amazon analyzes purchasing behavior and browsing history to predict what products a customer might want to see, and what they are likely to buy, personalizing the customer experience and making it easier for customers to complete a transaction. BI tools help the business to forecast demand and ensure that stock is available.
Starbucks – The business has implemented a loyalty program to help with customer engagement and sales, personalizing marketing strategies and allowing customers to order, pay and receive rewards. It gathers data using its digital channels and uses that data to create targeted offers and to improve customer retention, as well as increasing the amount customers spend during a visit.
Netflix – The company uses BI tools to personalize the viewing experience and to analyze customer viewing preferences and push specific options to the customer based on viewing history. Mobile BI tools allow teams to analyze and share information regarding regional viewing and to make decisions on the fly.
Uber – The company business model is dependent on the rapid changes and shifting behavior of customers from one local and regional area to the next. Real-time pricing and operational decisions are made to support surge pricing and driver deployment for high demand areas. The back-end systems and BI tools allow drivers to access information using the Uber app so that they can quickly respond to the changing environment.
Tesla – Mobile BI and wireless car data analytics allow Tesla to connect remotely to corporate offices and collect and analyze vehicle data to address issues and update customers on maintenance etc.
X/Twitter – Mobile BI provides support or moderators to identify and quickly address platform safety issues, violations, etc. The integration of artificial intelligence (AI) with BI tools allows the business to quickly respond and ensure a safe user experience.
Mobile BI provides the background and foundational information needed to make decisions on business strategy and to understand customer preferences.
These examples illustrate the many ways in which Mobile BI can be used to address business issues, providing user access and analytics for team members no matter where they are and how they need to use the data. Mobile BI benefits go well beyond simple reporting and the sharing of data across user groups, to address real business issues and to keep users up to date and allow them to respond to real world, real-time issues.
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, ‘Understanding The Truth About Mobile BI.’
Use Embedded BI to Encourage Business User Analytics Adoption!
Today, even the smallest business depends on technology and software to manage the business process, capture data and move the enterprise forward. No matter the size of a business, executives and managers now realize the value of providing analytics to make decisions. In the past, the analytics process was the sole domain of IT, business analysts and data scientists but today, organizations know that data democratization and data literacy are key to business performance and to keeping pace with the market and with changing customer buying behavior.
In order to accommodate this need, the business must provide easy-to-use analytics solutions that offer sophisticated functionality and features in an intuitive environment so team members can embrace analytics and willingly adopt these solutions.
‘Embedded BI brings the power of analytics closer to the user and allows them to use popular software and apps to achieve analytical goals with a single sign-on approach.’
If you want to take advantage of this approach, there is a consideration you should include in your strategy – and that consideration might surprise you. Consider the number of applications and software products your team uses to complete tasks and to find information. Did you know that, by some estimates, team members lose up to ten (10) percent of their time switching tasks and applications. One of the most frustrating realities an employee can face is trying to gather and analyze data. Suppose you want to analyze sales for a particular location, or a particular sales team for a certain period of time. In the old technology world, you would have to export the data, or you might use an integrated analytics solution and gather the data there by choosing the fields you want to analyze.
Today, you can use Embedded Business Intelligence (BI) to find and analyze data without ever leaving the confines of your sales software. Embedded BI is designed to embed within a popular, familiar software platform. By placing this capability within a familiar application or software solution, the organization gives its team members access to data, pulling information from the system of origin, integrating and streamlining data processing and reporting time.
Embedded BI brings the power of analytics closer to the user and allows them to use popular software and apps to achieve analytical goals with a single sign-on approach, so they don’t lose time switching between software solutions or exporting and importing data. Users have access to dashboards, charts, graphs and analytical tools, all within the ERP, HRM, CRM, SCM or other enterprise solution. Embedded BI allows users to integrate analytics within workflow and collect and analyze data easily.
When considering an Embedded BI solution, be sure you choose one that accommodates access both in the office and on the road, with mobile access that enables business users to take analytics on the road.
‘In order to accommodate this need, the business must provide easy-to-use analytics solutions that offer sophisticated functionality and features in an intuitive environment so team members can embrace analytics and willingly adopt these solutions.’
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.’
What Do I Need to Know Before I Choose a Mobile Business Intelligence (BI) Solution for My Business?
What makes a great Mobile Business Intelligence (BI) solution? There are many factors to consider and, if you do not choose wisely, you risk a) spending a lot of money and getting very little in return, b) working with incorrect, old or incomplete data, c) having to upgrade and spend even more money, d) disappointing your team and falling short of objectives, e) missing your Citizen Data Scientist initiative goals.
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