The future of business intelligence is the thing that interests all ambitious companies because good data is crucial to a company’s success. Nevertheless, the best outcomes from data can be achieved only with the usage of special sets of technological processes and this is when business intelligence comes to help.
Business intelligence gathers, organizes, and examines organizational data. This process uncovers insights that guide and enhance business strategies and operations. As a result, a company gains diverse advantages, including clearer reporting, consolidated data, and enhanced employee and customer satisfaction.
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Two decades ago data warehouse consulting was enough to find a business intelligence solution that will work. Now the market is more complicated because of a bigger amount of data and increased competition. A company that wants to be successful must constantly contemplate the latest technologies to install them in its work and, this way, keep the business in high demand.
According to statistics, by 2032, the value of the BI market will reach USD 63.76 billion, which is why it’s essential to constantly check the updates in the sphere of business intelligence services.
Key trends in business intelligence
The next generation of BI will allow any member of an organization to easily comprehend the power of data to find successful solutions regardless of technical knowledge. Keep reading to discover an example of this in action.
Trend 1: Self-service business intelligence
The self-service BI market is projected to rise to USD 27.32 billion by 2032 from USD 6.73 billion in 2024. This tool is popular because it allows data analysis without technical teams.
Working with technical personnel can sometimes be a real bottleneck in business intelligence processes. At the same time, with self-service BI tools, almost anyone can be a data scientist and have access to the needed data everywhere.
Trend 2: Data security, data governance
Nowadays, Big data development is the most significant resource for any work. It’s impossible to imagine business excellence without data quality management. Companies do their utmost to classify data so they know where it comes from, who has access to it, and how they use it. As a consequence, data governance has become an indispensable part of business intelligence and a top priority for companies of any size.
An accurate data governance strategy not only provides a delicate balance between data transparency and consistency but also boosts ROI from BI investments. This, consequently, will lay the groundwork for informed, ethical, and evidence-based decision-making.
Data governance helps companies to comprehend the information needs of the business. Such actions protect data from unauthorized use and ensure confidentiality and privacy which further leads to the improved quality of data and information.
It will enable companies to apply appropriate data to guide well-informed business intelligence BI decisions, ultimately enhancing business results. It will also guarantee that data is securely obtained from authorized sources, processed for its intended use, shared with approved personnel, and disposed of according to a predetermined schedule.
Trend 3: Embedded analytics
Embedded analytics refers to the incorporation of business intelligence capabilities within other applications. This tool is very useful for bolstering real-time decisions as it provides business users with actionable insights directly within their operational workflows, eliminating the need to switch to a separate analytics application.
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As data analytics components are incorporated into familiar applications, it fosters user adoption of analytics and lessens the need for particular BI training. Installing BI components like reports or visualizations into users’ applications and workflow has several advantages:
Ease of adoption: Rather than spending money and time developing new workflows to incorporate BI, it can be brought to the existing ones with the use of embedded analytics. With it, BI elements can be easily transported to familiar apps and workplace environments.
Promotion of collaboration: Integrating analytics into core business applications can make Big data analytics and business intelligence accessible to all stakeholders, facilitating seamless sharing of insights and fostering data-driven discussions.
Productivity to value: the possibility of developing BI insights from commonly used software improves comprehension and efficiency, facilitates the learning curve, and reduces the time needed to achieve value.
Trend 4: Data quality management
A BI solution’s success hinges entirely on the condition of its data to deliver precise insights for making well-informed decisions, that’s why the future of business intelligence is very much about it. In 202, the data quality market was estimated at USD 2.71 billion and is predicted to come to USD 4.15 billion by 2031.
Even if a company has a highly demanded business intelligence and data insights solution, it can lose all its prospects because of bad data. Here are some consequences a team may meet if developers neglect data quality:
- Data quality and data analytics are interconnected: if the initial data is bad, then the analytics will be the same. As a result, a company makes wrong decisions that corrupt business strategy.
- A company simply wastes its money and time on solutions that won’t work.
- The future of artificial intelligence in business is very promising: by embedding AI into the workflow, a company may eventually have good revenue. To make it possible, a company should be very careful with data quality, otherwise, the development may lose its decision intelligence and effectiveness.
Trend 5: Mobile BI
One of the biggest business intelligence market trends is the development of mobile BI, and it’s no surprise due to the rapidly growing BYOD (bring your own device) policy and the ubiquity of modern phones.
The opportunity to access essential data and insights on the move has made mobile BI a highly demanded technology and has become the driving force for its rapid development. Its real-time access to data allows businesses to advance operational efficiency and enforce organizational collaboration.
Furthermore, mobile BI can bring even greater success if combined with other technologies. By mixing mobile BI technologies with machine learning and artificial intelligence, your team can get impressive data analysis and predictive analytics. Cloud computing is also well integrated with mobile BI, providing cost-effective and scalable solutions.
All in all, this trend has already proved itself in healthcare, BFSI, and government, where mobile applications facilitate the working process a lot, but it is not limited to these industries only. It is estimated that in the period from 2025 to 2030, the mobile business intelligence market will grow at a CAGR of 22.43%, so this trend is worth paying attention to.
Trend 6: Business Intelligence-as-a-Service
XaaS (Anything as a Service) has already proved itself to be a good way to deliver various tools and services through the cloud. This process can bring companies various benefits, including agility and convenience, optimized processes, and faster business growth. The sphere of business intelligence is also a great example of XaaS’ impressive work.
Many companies resort to BI-as-a-service options if they want to find Big data analytics solutions that will make their business grow. With the straightforwardness and convenience of cloud-based deployment, this model offers the comprehensive advantages of a complete, end-to-end BI solution that will speed up data analytics.
BI-as-a-service favors companies to implement BI solutions in the shortest possible time and also to free the IT staff from doing complex analysis tasks. Consequently, this model provides organizations with immediate access to skilled BI consultants and data architects who excel in data management and governance, leading to improved business results at significantly reduced costs.
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With BI-as-a-service, experts can smoothly analyze and organize the growing volume of data, extract it from numerous sources and convey insights to users through user-friendly dashboards and reports. The end-to-end service will make their work more effective and possible to overcome difficulties connected with a small number of employees. and will also enable ordinary users to establish reports and dashboards on their own.
Trend 7: Augmented analytics
It’s impressive how artificial intelligence will change the future of business, especially the future of business intelligence, where the integration of machine learning and AI are gradually becoming a table stake for a BI tool.
There are a lot of advantages of integrating AI into BI, such as supporting data-driven decisions by enhancing, analyzing, automating, and sharing BI data. Here are some popular examples of how AI applications can make business intelligence use cases more effective:
- Data processing and preparation
Nowadays, companies have enormous volumes of raw data to analyze, integrate, and standardize to extract the highest possible value from their BI platform. AI can conserve serious amounts of time and effort by automating these processes and providing relevant and precisely formatted data. AI can also help extract newly revealed insights from formerly untapped unstructured data (for example, contracts, free text fields, and emails) and load them into the BI model.
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- Personalized BI insights
AI-powered BI solutions can personalize insights based on particular user preferences. By estimating user behaviour and previous data interactions, AI emphasizes essential metrics, customizes relevant reports, and compiles insights uniquely for each user. As a result, it advances the process with contextual information. - Predictive analytics
- Prescriptive analytics
Prescriptive analytics, due to its precision, elevates AI’s involvement in decision-making to a new level. Predictive analytics can help presume what may happen, while prescriptive analytics suggests what a team should do to meet the target, using the same business context and big data points. - Natural language processing (NLP)
NLP is a branch of artificial intelligence that allows computers to comprehend human language. Nowadays, this technology plays a crucial role in any business development and BI is not an exception. Business intelligence makes business data accessible to more employees, providing insights to a broader range of the organization.NLP enables us to drive this process to a whole new level by making this information understandable for non-technical employees. Natural language processing for BI provides a user-friendly experience that allows individuals to handle detailed data analysis by communicating business intelligence platforms utilizing everyday language. In this process, the NLP interface performs the analysis, comprehends the query, and delivers the desired results. As a consequence, it brings a seamless path to uncovering insights by extracting the need for technical knowledge to query a BI database.
Trend 8: Data storytelling
Data storytelling is a methodical way to communicate data insights that include data, narratives, and visuals. The future of business intelligence greatly depends on this means of distributing considerable business intelligence decisions because almost all major BI platforms have data storytelling extensions.
In the BI environment, data storytelling is an enhanced form of BI reporting that integrates narrative structure and storytelling elements into BI visualizations, highlighting key insights and explaining what’s occurring and why. It creates a unified data story that connects visualizations, guiding audiences instead of leaving them to presuppose insights or causality on their own. This approach is especially beneficial for distributing data across diverse teams with varying expertise, ensuring the seriousness of trends is understood.
Trend 9: Decision intelligence
Decision intelligence is a data-driven approach to decision-making that uses machine learning, advanced analytics, and AI to provide actionable insights and automate decision-making processes.
Using previously mentioned technologies, DI handles big data and creates a set of rules and contexts to hat support predictive analytics, ultimately providing forward-looking insights to enhance an organization’s decision-making capabilities. This approach is so actively used that it is predicted that its market will grow from USD 13.3 billion in 2024 to USD 50.1 in 2030.
Trend 10: Process intelligence
Process intelligence is a combination of task analysis that provides suggestions for automating decision processes. It benefits BI specialists to comprehend what they have to do and optimize to reach their goals.
Process intelligence bolsters companies’ BI by providing process insights. This favors them to pinpoint processes that need improvement, uncover value opportunities in the data and respond effectively and smoothly. Watch a video to learn more about advanced data analytics, and how it can enhance your business workflows:
What is the future of business intelligence?
The business intelligence future is considered very promising as it plays a key role in helping companies make strategic decisions. No industry in today’s world can successfully exist without BI solutions.
For example, BI for chemical industry enables organizations to turn millions of data points from operations into insights that can eventually grow business. There are a lot of business intelligence industry trends, but the biggest ones are connected with data security and generative AI.
It’s undeniable that in a rapidly developing world full of technological advances, data is the most valuable resource any company may have. Modern companies pay attention not only to data quality but also to data security. The future of business intelligence is found in the security and integrity of the data that enhance privacy and result in great BI outputs.
BI future is also very interconnected with Machine Learning and generative AI. There are already a large number of artificial intelligence trends in business that make it more effective and lucrative.
Nowadays, a company’s profit will largely depend on the adoption of these trends to average users. As a result, every team member will get an opportunity to make data-driven decisions. The time when only professionals could search for needed information is coming to its end. Soon, it will be readily applicable to anyone to make informed decisions, and this is what makes BI’s future so bright.
FAQ
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BI future is packed with perspectives. In today’s world, it’s crucial to attach significant importance to data quality, which is why it is actively developing.
Modern business intelligence market trends are related to data governance, active combination with Artificial Intelligence and Machine Learning, embedded analytics, mobile BI development and so on. As a result, the new generation of BI is predicted to be approachable and accessible to anyone.
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Trend analysis in business intelligence is a method of gathering and analyzing historical data to determine patterns or trends over time. It allows businesses to foresee forthcoming movements, comprehend their performance, and make strategically correct choices.
Trend analysis is indispensable for businesses that want to keep abreast of the market and be profitable. By knowing and understanding trends, companies can anticipate changes more effectively and modify their strategies if necessary.
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The role of business analytics in modern enterprises is diverse and complex. It backs assessment risks, makes strategic choices, and optimizes processes. There are a great number of business analytics trends, but the biggest ones are big data analytics and advanced analytics.
Big data analytics allows examining extensive amounts of both structured and unstructured data to derive meaningful insight, while the use of advanced analytics techniques like machine learning, predictive analytics and prescriptive analytics help foresee future scenarios and advance a decision.
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AI is actively modifying the approach to BI in a good way. AI provides predictive analytics, data analysis, automated insights, and natural language processing and advances business processes. As a result, BI powered by AI brims with new possibilities for businesses to make better decisions and drive growth.
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Generative AI for business intelligence is transforming the way organizations examine data and make choices. AI can enhance decision-making, advance user experience, and speed up data analysis.
By integrating BI with AI, a company can not only analyze bigger amounts of data in the shortest time but also make big data explicit for people without a technical degree. To make it real, the best AI fields include Machine Learning, natural language processing, prescriptive analytics, and predictive analytics.
