Zuzanna Pajorska

Future of Business Intelligence: Emerging Trends in 2023

In today’s fast-changing world, almost every company relies on data. They are the foundation for improving employee satisfaction, streamlining operations, optimizing the supply chain, understanding customer behavior, or performing predictive analytics. The importance of data is critical to an organization’s success and making informed business decisions. However, with the variety, sheer volume, and velocity of the influx of data, the best results can only be achieved through using Business Intelligence (BI) tools, which are valuable assets for both small and large companies. How will this market evolve in 2023? Learn about the latest Business Intelligence trends and discover the future of Business Intelligence.

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Business Intelligence – what is it?

Business Intelligence (BI) encompasses various tools, technologies, and strategies to collect, analyze, and interpret business data to understand data and facilitate informed decision-making.

Essentially, BI provides a means to delve into the intricacies of your business, unveiling concealed patterns and trends within your data. By doing so, it empowers you to gain a comprehensive understanding of your business’s performance and identify measures that can be taken to attain improved outcomes.

Think of Business Intelligence as a versatile toolbox explicitly tailored for enterprises. It empowers you to amass an extensive collection of unstructured data concerning various aspects of your company, including sales, production, finance, customer relations, and more, and merge them into a cohesive and comprehensive whole.

Once all the existing data sets have been aggregated, Business Intelligence enables you to conduct thorough analyses, streamline data quality management, unearth valuable relationships, and comprehend the key factors influencing your business’s success. With this knowledge, you can make informed decisions to prop your business forward.


data discovery trend


The importance of Business Intelligence for companies


Actionable insights for informed decision-making

BI tools empower business users to convert raw data into actionable insights. Through robust data visualization, interactive dashboards, and intuitive reporting features, these tools help decision-makers analyze vast amounts of information at a glance. This enables them to:

  • promptly make data-driven decisions,
  • optimize resource allocation,
  • identify market trends,
  • and enhance operational efficiency.


Increased efficiency and productivity

By automating data management, data collection, consolidation, and reporting processes, Business Intelligence tools save valuable time for employees, allowing them to focus on strategic initiatives. According to industry reports, organizations that have implemented Business Intelligence tools experience an average of 40% reduction in time spent on data preparation, resulting in enhanced productivity and accelerated decision-making cycles.


Enhanced operational performance

BI tools enable companies to comprehensively view their operations, facilitating performance monitoring across various departments and functions. Real-time data updates and customizable KPI tracking ensure organizations can proactively identify bottlenecks, optimize processes, and drive continuous improvement. Companies leveraging BI tools report an average 15% improvement in operational performance metrics.


Improved customer understanding and engagement

BI tools allow businesses to discover customer behavior, preferences, and buying patterns. Companies gain a holistic view of their customers by integrating data from multiple sources, such as:

  • sales,
  • marketing,
  • and customer support.

This empowers them to tailor their products, services, and marketing strategies to meet evolving customer expectations, resulting in improved customer satisfaction, loyalty, and, ultimately, higher revenue.


Competitive advantage and market insights

With Business Intelligence tools, companies can leverage the power of data analytics to gain a competitive advantage.

Organizations can identify untapped opportunities, assess risks, and devise effective strategies by monitoring industry trends, market dynamics, and competitor activities. A study by Gartner reveals that companies adopting BI tools experience an average 20% increase in revenue due to improved market responsiveness and customer-centric decision-making.


Future of Business Intelligence – discover 7 key trends for 2023

By 2023, more than 33% of large companies will use decision-making processes based on advanced business intelligence analytics, and the global business analytics market will grow to USD 33.3 billion by 2025. Moreover, company representatives admit that big data analytics makes decision-making 5x faster.

Will the latest BI trends drive even better statistics? Let’s find out.


1. Self-Service BI

As the technological proficiency of business users continues to grow, their expectations for accessing necessary data to perform their tasks effectively have evolved.

They want to resolve issues independently, without relying on an analytics team. With centralized data encompassing the entire organization, users want the freedom to utilize their preferred tools to derive business value.

While self-service BI has already gained popularity, it is expected to become a global standard in the forthcoming years. This will empower users to obtain the insights they require to address complex business challenges promptly.

Furthermore, it will enhance decision-making capabilities across organizations by equipping business users with a unified and trustworthy version of the truth, regardless of their company positions.

By adopting a self-service data model, business users, who clearly understand their needs, will be able to achieve self-sufficiency. The future will witness users making more effective use of data, fostering a data-driven culture throughout the organization.

Self-service BI will eliminate the dependence on IT or data teams to access the correct data, allowing users to fulfill their analytical requirements effortlessly and make critical decisions at an accelerated pace.

[Read also: What Are Large Language Models: Definition + Best Examples]


data literacy


2. Data Governance

As data privacy and data security regulations become stringent, effective data quality management is indispensable for achieving business excellence. In the upcoming years, organizations will undoubtedly prioritize efforts to classify data, understand its origin, control access, monitor its usage, and determine its retention period.

Within the Business Intelligence trend, data governance will emerge as a crucial focus for organizations of all sizes. This change will be driven by the growing number and complexity of data sources. Implementing a robust data governance strategy should enhance the return on investment (ROI) from BI endeavors and establish a healthy equilibrium between poor data quality and consistency and transparency. This, in turn, will serve as the foundation for accurate, ethical, and evidence-based decision-making.

What’s more, data governance will empower organizations to gain a clear understanding of the information needs of the entire enterprise. Continually improving data and information quality will ensure privacy and confidentiality and prevent unauthorized usage. It will enable companies to harness the appropriate data for informed BI decision-making, leading to enhanced business outcomes.

Additionally, data governance will guarantee the secure acquisition from approved sources, their processing for intended purposes, sharing with authorized staff, and proper removal within predefined timelines. After all, it is vital to remember that the consequences of a data violation are very high fines, which can contribute to the companies’ bankruptcy.


3. Natural Language Processing in Business Intelligence

Natural Language Processing (NLP) technology is critical in today’s world. It allows us to communicate with computers and devices more naturally, similar to how humans talk to each other.

One example of using NLP technology is popular platforms such as Google Voice and Google Translate. They allow us to ask questions in our language and receive answers in a way we can understand without translating or learning specialized vocabulary.

It is not only in communication and translation that NLP technology has its uses.

Leading business analytics platforms, such as Microsoft Power BI, have already introduced solutions for asking questions in natural language and receiving feedback from the system. This means that analysts no longer have to manually sift through thousands of data to get the necessary information. They have to ask a question naturally, and the system automatically provides the answer.

Besides, using the power of NLP, companies can also analyze customer sentiment data, specific information from a piece of text, or determine positive or negative views around their brand on social media.

According to Gartner, by the end of 2024, as many as 75% of companies are expected to implement solutions based on natural language processing technology. This confirms the great importance of this technology for business development and effective information management.


BI data strategy


4. Explainable Artificial Intelligence as a future of BI solution

Explainable Artificial Intelligence refers to the capability of AI systems to provide transparent explanations for their decision-making processes, enabling stakeholders to understand the reasoning behind AI-driven predictions and recommendations.

Unlike traditional black-box AI models, explainable AI algorithms utilize techniques that shed light on the inner workings of the AI systems, making it easier to trace the factors influencing their outputs.

As businesses increasingly rely on AI for critical decision-making, trust becomes paramount. According to a PricewaterhouseCoopers (PwC) study, 65% of business leaders view a lack of transparency as a significant barrier to artificial intelligence adoption. Explainable AI offers a solution by providing clear justifications for AI-driven outputs, ensuring decision-makers can confidently understand and defend the results obtained.

Explainable AI facilitates collaboration between data scientists and domain experts by making complex AI models more accessible. Clear explanations enable stakeholders from various backgrounds to engage with artificial intelligence systems, providing valuable domain-specific insights. This collaboration enhances cross-functional understanding and paves the way for shared knowledge that drives innovation and problem-solving.

According to Gartner stats, by 2025, more than 60% of enterprises will adopt explainable AI techniques in their Business Intelligence processes to ensure regulatory compliance and mitigate biases. Allied Market Research shows that the global explainable AI market is projected to reach $2.6 billion by 2027, growing at a CAGR of 40.5% from 2020 to 2027.

These figures speak for themselves – one of the top Business Intelligence trends up for 2023 will undoubtedly be Explainable AI.


analyze data and collecting data


5. Embedded Analytics revolutionizing the future of Business Intelligence

In today’s data-driven world, businesses are constantly seeking innovative ways to harness the power of analytics to make informed decisions.

Embedded analytics has emerged as a game-changing approach integrating data analytics capabilities into existing applications and workflows. This integration empowers businesses to extract valuable insights and enhances user experience, fostering a new era of data-driven decision-making.

By embedding analytical capabilities within existing applications, employees can access real-time insights into data within their familiar workflows, eliminating the need for switching between different tools. According to a survey by Logi Analytics, 93% of business leaders reported faster and better decision-making due to embedding analytics into their applications.

Embedded analytics takes self-service to the next level by democratizing data access and analysis within applications. Besides, it enhances internal decision-making and presents opportunities for monetizing data assets. By embedding analytics into customer-facing applications, businesses can deliver data-driven insights, strengthening the value proposition of their products or services.

This opens avenues for new revenue streams and strengthens customer loyalty. According to a study by Aberdeen Group, organizations with embedded analytics in customer-facing applications have experienced a 170% increase in customer retention and a 25% increase in average deal size.

According to Allied Market Research, the global embedded analytics market is expected to reach $77.48 billion by 2027, growing at a CAGR of 16.8% from 2020 to 2027. Embedded analytics is poised to revolutionize the future of Business Intelligence by seamlessly integrating analytical capabilities into existing applications and workflows. It empowers users with real-time insights, enhances user experience, and enables self-service analytics, ultimately driving faster and better decision-making.


Data processing in business operations


6. Real-time access to data – cloud based BI

The outbreak of the COVID-19 pandemic contributed to the popularity of another Business Intelligence trend – the use of the connected cloud strategy and real-time access to key company data.

With the advent of the pandemic, data needed to be accessible to employees working remotely from various locations, using more than just company computers. Many companies, therefore, decided to move databases to the cloud and deploy new BI solutions on the platforms. The benefits of this in data storage are so great that the trend is still continuing, and more and more organizations are implementing it. So without a doubt, this is the future of Business Intelligence.

This is because access to real-time data enables organizations to make informed decisions quickly. Instead of relying on outdated or batch-processed data, decision-makers can use up-to-date information to respond promptly to market changes, customer preferences, and operational challenges.

According to a Forbes survey, 75% of executives believe that access to real-time data improves their decision-making capabilities. According to IDC, by 2025, nearly 30% of the world’s data will require real-time processing, indicating a growing demand for real-time data access capabilities.

For example, real-time data can enable predictive maintenance in the manufacturing industry, minimizing downtime and maximizing productivity. A McKinsey study found that companies that use real-time data in their operations achieve 10% to 20% productivity gains.

The same applies to the financial industry or travel industry. Access to real-time data not only streamlines operations but also increases profitability. For this reason, the digital transformation in the finance sector through BI is going much more smoothly, improving the quality of services provided. On the other hand, BI tools accelerate digital transformation in tourism by adopting various types of applications for flight and hotel reservations, customer preferences, and service providers’ assets or travel search engines.

Equally important, in today’s customer-centric landscape, delivering personalized experiences is critical to business success. Access to real-time data enables organizations to gain deep insights into customer behavior, preferences, and interactions, allowing them to customize offers and interactions in real-time

This can lead to increased customer satisfaction, customer loyalty, and, ultimately, increased revenue

According to a Gartner report, organizations that use real-time analytics for personalized marketing will see a 15% increase in revenue by 2023.

[Read also: 12 Types of Healthcare Software]


data culture in business processes


7. Revolutionary advancements in collaborative BI and integrative BI

In the upcoming years, we will witness a remarkable shift toward the widespread adoption of collaborative and integrative BI. Gone are the days when standalone BI tools must be acquired and implemented separately. Instead, most enterprise systems will incorporate built-in BI capabilities, empowering users to uncover invaluable insights and make informed decisions without leaving the platform.

For example, this trend in Business Intelligence can be seen in the giants’ actions. Microsoft Fabric is an excellent example of combining several BI tools under one brand umbrella.

The next generation of BI systems will cater to a more extensive user base and establish deeper connections with expansive enterprise systems. These cutting-edge systems will continually retrieve data from necessary sources, consolidate and analyze it, and present users with real-time insights. Furthermore, these systems will be able to notify users of relevant data changes by sending alerts, ensuring that they stay up-to-date.

An example of this use of BI tools can be found in the medical sector, where the digitization of healthcare, healthcare software development, and healthcare software solutions are expanding rapidly thanks to modern technologies and the ability to rely on actual data.

By seamlessly integrating into existing and future workflows, these systems will enable teams of employees to effortlessly carry out their daily operations and make data-driven decisions in real-time. Moreover, besides facilitating data analysis within current plans, they will seamlessly integrate with third-party systems, paving the way for a data-centric culture throughout the enterprise.


machine learning models in BI - collect all the data


Important Business Intelligence trends in 2023 – conclusion

The future of the Business Intelligence industry in 2023 is marked by several emerging trends that revolutionize how organizations collect, analyze, and interpret data for informed decision-making.

In the ever-changing business intelligence (BI) landscape, we witness a constant evolution that seems to accelerate. Gone are the days when IT solely drove BI delivery. Instead, we are now seeing a rapid transition towards self-service analytics, empowering individuals to harness the power of data on their terms. But that’s not all. There’s an exciting new trend on the horizon – embedded analytics.

Embedded analytics is the latest major trend sweeping through the BI world. It goes beyond the traditional notion of a separate BI environment and embraces integration with a line of business systems. Imagine having the ability to access powerful analytics tools seamlessly integrated within your core operational systems. It’s like having a hidden gem, a treasure trove of valuable insights waiting to be discovered.


historical data and current data


This convergence of BI software and advanced analytics with operational systems brings tangible benefits. Imagine a sales team analyzing customer data within their CRM software, enabling them to identify patterns, anticipate needs, and make data-driven decisions. Picture a manufacturing plant utilizing modern BI tools to optimize production processes, reducing costs and increasing efficiency.

These are just a few examples of how the marriage between BI and operational systems can unlock a world of possibilities.

But, it’s essential to acknowledge the inherent complexity of this shift. It requires a balance of technical prowess, business acumen, and a deep understanding of data insights. Organizations must ensure they have the right tools, infrastructure, and expertise to embark on this analytics journey successfully. Only in this way will digital transformation, with the help of BI, become effective and viable for implementation.

Stay caught up – seize the moment and embark on this digital transformation journey toward a data-driven future. Buckle up because the ride is just beginning, and the possibilities are endless.


We are Stratoflow, a custom software development company. We firmly believe that software craftsmanship, collaboration and effective communication is key in delivering complex software projects. This allows us to build advanced high-performance Java applications capable of processing vast amounts of data in a short time. We also provide our clients with an option to outsource and hire Java developers to extend their teams with experienced professionals. As a result, our Java software development services contribute to our clients’ business growth. We specialize in travel software, ecommerce software, and fintech software development. In addition, we are taking low-code to a new level with our Open-Source Low-Code Platform.

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