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Low Code No Code Development Supports Analytics Performance
Within the very near future, it is estimated that 70% of all software and application design will include a component of low-code or no-code development. So, it is no surprise that analytics software and tools are also affected by this trend. While advanced analytics and augmented analytics solutions provide a sophisticated, complicated underpinning of algorithms and analytical techniques, the average enterprise expects (and should look for) tools that are easy to use, so they can improve data literacy and data democratization and leverage analytics within the organization at the business user level, to improve results and efficiency.
It may be difficult to understand how such complex systems can benefit from the no code, low code approach, since the very concept of this approach seems at odds with the complexity of an analytical solution, but nothing could be further from the truth. When applied appropriately, these techniques can benefit the foundation of the augmented analytical solution and the users of those solutions.
- Time and Expense – In a world where new features and functionality must keep pace with market demand, the emergence of no-code and low-code allows developers to add analytical functionality quickly, while controlling costs and time to market.
- Business and Market Requirements – As organizations and business users embrace analytics, the need for new types of visualization, reporting and features changes quickly. In order to stay abreast of these changes and offer businesses the products they need, analytical vendors can quickly leverage, modify and develop new approaches to satisfy user requirements. Vendors can accommodate business-specific needs and data visualization requirements without time-consuming, expensive customization.
- Integration of Third-Party Apps – Low-Code, No-Code capabilities support the easy integration of other enterprise applications and solutions and allow data analysis across the organization.
- Performance and Scalability – Low-Code and No-Code solutions and platforms enable high-performance, scalable solutions and ensure that businesses can accommodate an expanding user base and data volume.
- Compliance, Data Security and Industry Standards – No Code, Low-Code development includes data encryption features and user access security controls to mitigate risk, and protect data integrity and privacy.
If you are still wondering whether low-code and no-code approaches are appropriate for software and applications, consider these predictions and statistics from technology research organizations:
- Gartner predicts that 75% of new software solutions will incorporate a low-code approach to development.
- By some estimates, the use of low-code, no-code and artificial intelligence in analytics solutions has increased user access to analytics by as much as 56%.
- Gartner predicts that organizations that lack a sustainable plan to operationalize and manage data and analytics will face a two-year setback in their data and technology efforts.
Choosing the right self-serve, augmented analytics solution can help the enterprise build a crucial foundation for analytics, for transition of business users into a Citizen Data Scientist role and for improved time-to-market, decision-making and collaboration. The use of new and cutting edge technologies and the seamless incorporation of these technologies is critical to the success of the analytical application implementation and to return on investment (ROI) and total cost of ownership (TCO) metrics.
Select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities and enjoy the benefits of advanced technologies like Artificial Intelligence (AI) And Low-Code, No-Code (LCNC) techniques to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read our free article, ‘The Benefits Of Low-Code No-Code in Augmented Analytics.’
Original Post : Why Choose Augmented Analytics with Low-Code, No-Code Development!
Use Predictive Analytics for Fact-Based Decisions
Like every other business, your organization must plan for success. In order to do this, the team must have a dependable plan and be able to forecast results and create reasonable objectives, goals and competitive strategies. These plans and forecasts will support investment in technology, appropriate resources and hiring strategies, additional locations, products, services and marketing strategies, partnerships and other components of business management to ensure success.
Forecasting and planning cannot be based on opinions or guesswork. It must be based on historical data, facts and clear insight into trends and patterns in the market, the competition and customer buying behavior. To accomplish these goals, businesses are using predictive modeling and predictive analytics software and solutions to ensure dependable, confident decisions by leveraging data within and outside the walls of the organization and analyzing that data to predict outcomes in the future.
‘Every industry, business function and business users can benefit from predictive analytics.’
According to CIO publications, the predictive analytics market was estimated at $12.5 billion USD in 2022 and is expected to reach $38 billion USD by 2028.
Predictive analytics encompasses techniques like data mining, machine learning (ML) and predictive modeling techniques like time series forecasting, classification, association, correlation, clustering, hypothesis testing and descriptive statistics to analyze current and historical data and predict future events, results and business direction.
When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.
With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists. The enterprise can provide the tools needed at every level of the organization with tools and data science for business users that are sophisticated in functionality and easy-to-use for users at every skill level.
The benefits of augmented analytics and self-serve predictive modeling include:
- No complex algorithms or data manipulation
- Auto-recommendations for algorithms to explore underlying data
- No advanced data science skills required
- Analyze, share, collaborate and optimize business potential
- Business users can prototype and hypothesize without professional assistance
- Recommend optimal actions to achieve specific goals
Every industry, business function and business users can benefit from predictive analytics. Here are some examples of the use of predictive modeling:
Retail – Predictive Analytics tools can be used to understand customer buying behavior and to suggest products and product bundling based on previous purchases, buying patterns, and demographics. This creates a more personalized and targeted shopping experience that is unique to each customer.
Supply Chain – The organization can forecast demand and manage the supply chain to optimize inventory using machine learning to predict customer demand, seasonality, product trends etc., to that the enterprise can mitigate stock shortages and avoid warehouse and inventory overstock.
Healthcare – By using historical data regarding specific diseases, conditions and treatment plans, providers can forecast treatment outcomes, limit risk and improve overall care, thereby reducing complications, readmission and provider resource, medication and hospital bed shortages.
Energy Infrastructure – Using predictive analytics allows these businesses to monitor and analyze data and performance and to detect patterns and trends that may indicate downtime, breakdowns and maintenance issues.
Financial Services, Banks and Loan Businesses – Predictive analytics provides support for credit risk and fraud mitigation and allows businesses to create scoring models for loan approval, etc. based on credit history, and other financial considerations. Predictive modeling allows the organization to identify transactions that are outside the norm, and alert the business and its customers of hacks, fraud, etc.
‘When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.’
These are just some of the benefits and use cases your business can consider to decide on how best to implement predictive analytics and integrate the use of these tools into day-to-day use for business users to improve data-driven decisions and results.
To find out more about AI And Predictive Analytics, 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.
Original Post : Predictive Analytics Supports Citizen Data Scientists!
The Secret Sauce of Software and IT Consulting Partners!
If a business wishes to remain competitive or to achieve a competitive advantage, it must consider both its internal business applications, and its outreach to consumers, customers, suppliers and partners. Technology, software solutions, mobile apps, web services – all of these offerings can be important to customer satisfaction and internal applications for team members can mean the difference between a productive, collaborative team and a frustrated business user.
In this white paper, we focus on the practical use of Generative Artificial Intelligence (GenAI) in Business Intelligence (BI) and Analytics tools and present several business use cases to illustrate how this approach to analytics can support business goals and help the enterprise to achieve goals. We also discuss some of the challenges a business may wish to consider in order to ensure that its analytics solution effectively incorporates GenAI so the enterprise can confidently depend on results and improve user adoption and ROI.
Incorporate Data Into User Roles with Mobile BI
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.’
Original Post : Mobile BI Tools Solve Many Enterprise Issues!
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!
Select an AI, partner for Artificial Intelligence Application Development, or a partner for predictive analytics and technology partner and a solution 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 our 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 : DeepSeek Unseats U.S. AI, and Reveals India Potential!
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Original Post : Smarten Support Portal Updates – January – 2025!
Improve the Value of OEM and ISV Offerings with Embedded BI
If you read industry publications and stay up to date on business technology, you are no doubt aware of embedded business intelligence (BI), but you may be wondering how this approach can help your ISV products business thrive.
A Mordor Intelligence study found that, ‘… the growing requirement for embedded analytics software will boost productivity, save operating expenses, and save time when reviewing data.’
According to a study on Embedded Analytics:
68% of commercial application teams say they charge more for the analytics in their applications.
85% of commercial applications are currently embedding analytics capabilities and
91% of application teams say embedded analytics helps them increase end-user adoption.
So, you may be asking yourself, is it worth investing in the integration of an analytics solution to expand your software product offerings and provide a market edge? Is there value for your users? The answer to these questions is a resounding ‘yes.’
In this article, we look at the value of embedded BI for ISV and OEM environments and how the technology (and the delivery model you choose) can support your business and add value to your product and service offerings.
‘Embedded BI allows your enterprise apps business to keep pace with changing end user enterprise needs and support business agility by offering new features and functionality for your business clients and users.’
Embedded analytics makes analytics easier for the business user by bringing it closer to the user within a familiar or popular application or database environment and incorporating dashboards, graphs, charts, visualization to clarify results and make it easier for users to make decisions. By adding this capability to your software solution, app or product, you can provide more value without adding more resources to your team, without acquiring analytical skills within your IT environment, and without spending the time and money to develop a sophisticated analytical product.
As an OEM or ISV business, you can reap the value of Embedded BI and analytics to your users and clients.
- Embed advanced analytics without significant investment
- Get started in less than a month
- Avoid the cost of adding analytics experts to your team
- Generate additional revenue stream for your business
- Add value to your solution and create competitive advantage in your markets
- Provide clear business benefits of advanced analytics to your users
If you want a fast start-up, and a low-profile, light technology implementation, your ISV or OEM business can offer clients advanced analytics with a suite of natural language processing (NLP) search capabilities and Smart Data Visualization, Self-Serve Data Preparation, Assisted Predictive Modeling, Anomaly Alerts and other tools to provide a foundation for a self-serve, Citizen Data Scientist environment that requires no SQL or data science expertise. This accessible solution provides integrated reporting, dashboards and predictive modeling insights. Embedded BI can add a valuable component to existing software offerings and allow customer businesses to enjoy sophisticated features and functionality without costly physical implementation or time-consuming deployment.
‘So, you may be asking yourself, is it worth investing in the integration of an analytics solution to expand your software product offerings and provide a market edge? Is there value for your users? The answer to these questions is a resounding ‘yes.’’
By integrating business intelligence (BI) and augmented analytics within your Software-as-a-Service (SaaS) or Enterprise App, you can provide a seamless user experience to clients. By choosing the right Embedded BI solution, you provide valuable analytical tools to your clients so they can enjoy access to data sources and data warehouses with single tenant or multi-tenant modes, and flexible deployment via a public or private cloud (no environment dependency) or on-premise installations. Single sign-on (SSO) access provides security protocols and links with existing portals and applications. Users have access to embedded BI objects within the applications using integration APIs. SDKs support business frameworks and technology so you can use existing .NET, ASP.NET, PHP, MVC, .NET Core, Vue, Angular, React, Java and other frameworks and technologies in web applications or mobile apps and integrate advanced analytics components directly from within your app.
To find out more about Embedded BI Technology and delivery options for your B2B enterprise, 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.
Original Post: ISV and OEM: Embedded BI for your Enterprise App customers!!
MVP Design and Development for Start Up Businesses!
When you are the owner/executive of a start-up, you guard the time of your team carefully. You only have so many hands to get the job done and every effort, every initiative must pay off. And when it comes to investments, your logic and your plan must be solid. You can’t afford a misstep. The products and services you plan to introduce into the market must be spot-on, and the cost to design and deliver those products and services must be carefully controlled.
