A new version of this article, featuring the latest data and statistics is available. Check out our report on Business Intelligence Software Trends for 2022/2023.
There is no doubt, business intelligence (BI) has become an indispensable asset to organizations, big and small. Everyone wants to leverage every bit of available information and extrapolate possible future results to make on-the-spot decisions that increase revenue, improve productivity, and accelerate growth. But, with so many business intelligence trends shifting the ground, the BI industry is destined for a significant makeover, even with the challenging business climate that the COVID-19 pandemic has brought upon virtually all industries.
This means you’ll need to stay abreast of the latest industry developments for future business success. In this post, we’ll discuss the latest trends that are shaping the future of the BI industry. Whether you’ve installed the business intelligence software tools or your plan to do so, understanding these trends is vital. With this information at your disposal, you can make the most out of the latest BI approaches and cope with the disruptive forces of BI digitalization.
Business intelligence has all the qualities of a requisite software solution for businesses of all sizes and types. However, BI has not always been a province of every business. Not long ago, business intelligence was a treasure reserved only for large enterprises with deep pockets to procure computing power and sophisticated data collection centers.
Fortunately, technologies like cloud computing delivered affordable data analysis tools that ushered small businesses into the BI revolution. The technological advancements brought the benefits of BI to the proximity of small and midsized companies. The fear of missing out on these benefits has prompted many to jump on the bandwagon. It’s hardly surprising, then, that in 2018, small businesses with less than 100 employees had the highest BI adoption rate (Forbes).
With its benefits, BI will take a central role in business operations, just like the internet did. Remember, the flow of raw data is only going to increase. Though the COVID-19 pandemic has hampered the creation of new data, increasing consumption of replicated data will only make the global data sphere continue to grow (IDC). In fact, by 2025, experts estimate that nearly 1.75 zettabytes of data will be generated every year (Seagate, 2019). So, we can safely say that the potential that this data holds is infinite. Therefore, as its volume grows, the demand for BI tools that can gather, sift through, analyze, and present actionable information will also increase.
Lastly, major cloud BI providers are making solutions to meet the growing demands for advanced BI tools. According to 60% of cloud BI services adopters, Amazon Web Services (AWS) is the best provider. Other leading cloud providers include Microsoft Azure (43%), Google Cloud (40%), and IBM Bluemix (12%) (Forbes, 2019).
Source: ForbesDesigned by
If you’re new to BI software, you can read our guide to understand the purpose of business intelligence in business.
Analyzing data is one thing; interpreting it for business is another. There’s no doubt; data analytics help users uncover insights. And, using these insights to guide decision-making is the endgame of the business intelligence process.
However, putting insights into action is easier said than done. It requires analysts to convey information to business leaders in a way that is reasonable and actionable. Most importantly, it requires analysts to describe how data metamorphosed into insights. These skills converge to a process known as data storytelling.
In the modern data-driven world where businesses are fostering a culture of analytics, data storytelling is increasingly becoming pivotal. Storytelling adds a dash of context to statistics and provides the narrative needed to put insights into action. After all, of what use is an affordable business intelligence platform for a startup, if the figures it spews out are not interpreted into meaningful takeaways?
Businesses have realized that dashboards figures alone make no sense if they are not accurately contextualized and interpreted. For this reason, many have gone all out to adopt principles of storytelling to nurture conversations around data. Besides, there are massive data literacy campaigns aimed at making everyone understand data and contribute to the analytical conversation.
Data storytelling will continue to shape the business intelligence arena in 2021. Notably, the trend will progressively change the way businesses use data to engage, acquaint, and try new ideas. More businesses will leverage this approach to make insights more applicable to their scenarios.
According to one BI-Survey report, businesses rated the importance of data governance with a score of 6.9 out of 10 (BARC, 2021). Data governance is, without a doubt, important to any business that wants to get significant returns from its business intelligence investments. Interestingly, most organizations have a form of data governance in place, although many have not entirely standardized it.
So, what is data governance?
Data governance is a process that stipulates the blueprints for managing corporate data assets, including process, operational infrastructure, and architecture. Put simply; it forms the sturdy foundation upon which organization-wide data management happens. It enables companies to harness the power of technologies, processes, and people involved in the management of data assets to deliver complete, trustworthy, secure, and understandable data.
This impacts the operational, strategic, and tactical levels in an organization. As a result, many have institutionalized data governance programs to make the efficient use of accurate data possible. The urge to instill confidence in business leaders and make business intelligence worthwhile, are some of the reasons driving the data governance trend.
Also, the passage of the General Data Protection and Regulation (GDPR) in 2018 means that it’s now more important than ever for businesses to implement proper data governance programs. Companies that have not started using data governance will be forced to do so in 2021 to remain compliant with the relevant laws. With the enactment of the California Consumer Protection Act, it is expected that more countries will enact data privacy laws of their own. Companies are expected to spend more of their budgets on data security to avoid fines related to non-compliance. The restrictions on personal data brought about by data privacy laws may mark a return to traditional marketing and an increase in sites that require users to sign up for memberships and subscriptions (Varonis, 2020).
As more and more small businesses continue to show interest in business intelligence, digital assistants are finding increased prominence. Remember, small business owners and workers had to access benchmark reports, visual workflows, and data visualization dashboards on their own.
However, with AI and NLP at the helm, things are taking a turn for the better. Modern business intelligence tools are now equipped with digital assistants that simplify the BI process. The emergence of voice-activated assistants has renewed hope for the BI industry. The new assistants are anticipated to start transcribing voice and converting into reliable data that can be analyzed to derive insights.
Anyone in the business arena can attest to one fact: virtually every business tool is moving to the cloud. Additionally, cloud business intelligence is also becoming a dominant force in big data and analytics. These latest developments mean that the future of business is in the cloud. Consequently, all the BI elements, including data models, data sources, computing power, data storage, and analytics models, are all destined for the cloud.
This leaves all businesses with no choice but to adopt cloud analytics. Working with disparate systems in the cloud brings speed, complexity, risk, and costs into the picture. All these factors, combined, make it difficult to find a one size fits all BI solution for every business’ needs.
This is where the connected cloud strategy comes in. A connected cloud strategy is an excellent option that brings flexibility and reduces the risks involved in analytics. However, before you invest in this strategy, you should first look into the different challenges that come with implementing it.
In Turbonomic’s 2021 State of Multi-Cloud, they revealed that many IT experts are concerned as to the extent of freedom that multi-cloud can provide. For starters, 18% say ensuring workload security across platforms is one of the barriers to moving freely between different deployment platforms (Turbonomic, 2021). Moreover, some experts feel that many applications and datasets don’t have the ability to be completely portable.
These challenges aside, we expect that connected cloud trends will continue to create ripples in 2021.
Source: Turbonomics, 2021
Collaborative business intelligence (BI) is not an entirely new trend. However, the ever-evolving business landscape, typified by managers and employees who need to interact differently, has continued to give this trend new impetus. Collaborative BI is a combination of BI tools and the best collaboration software, including web 2.0 and social technologies to streamline data-driven decision-making.
This trend has emerged in the wake of the need for increased collaboration in the business environment. What happens is that with collaborative BI, the sharing of analytics and reporting is simplified, thus, supporting efficient decision-making.
Thanks to collaborative BI, people are now involved in the decision-making process, and no longer need to reach conclusions on an individual level. Instead, collaborative BI emphasizes collaborative problem-solving. As a result, it encourages users to analyze information and share analytics and ideas via web 2.0 tools to reach common ground. As early as 2020, experts predict that the onset of web 3.0 or the semantic web is upon us which will allow businesses to use data from sensors and the Internet of Things to tap into their operational data (Deloitte, 2020).
Owing to its benefits to the modern workplace, collaborative BI will continue to gain popularity. Let us see how this business intelligence trend pans out in the near future, particularly amid the pandemic.
Big data analysis is an intricate process: one that requires the substantial involvement of professional data scientists. Fortunately, with the advent of self-service BI (SSBI), the approach to data analytics is changing and fast.
Self-service business intelligence has been on businesses’ wishlist for a long time. Business users were not comfortable with the complexity of rigid BI analytics tools. Besides, the need to bring data scientists to handle the analytics was inflating operation costs. Consequently, this induced the perpetual craving for self-service and flexibility in analysis and reporting.
Then, self-service business intelligence was born. This technology has proven to be a timely intervention. Statistics show that self-service BI is still a top priority for many businesses (BARC, 2021). The service enables business users to handle BI tasks on their own without involving data scientists or IT teams. So, it empowers users to filter, sort, and analyze corporate data without necessarily having technical data analytic skills.
Interestingly, it is predicted that going forward; self-service BI will produce more analytics than data scientists. This points to the growing importance of self-service BI. With more and more businesses planning to use BI to promote data-driven culture, the self-service business intelligence trend will only gain more traction.
Time and again, we have mentioned how important data can be to an organization. The benefits of having accurate, understandable, and complete data transcend better decision-making. All that said, leaving data unattended can dilute all these benefits and leave you counting losses.
Just look around, companies like TMobile, Facebook, and MyHeritage suffered shocking data security breaches in 2018. The cyberattacks dragged these companies through mud and left millions of their users exposed. Not only that, the companies’ market value dropped, resources drained, and the negative publicity affected clients’ trust.
In the modern era, there are millions of cyberattackers sniffing for an opportunity to strike. The worst is that they attack all types of businesses, big and small. There is always a chance of successful attacks for companies that have not implemented impervious security layers. The rampant cases of cybersecurity breaches underpin the importance of data security.
Data security trend picked up speed in 2019, and we predict that in 2021, businesses will continue to search for more secure solutions. Consumers are now fully aware of the value of personal information and are skeptical about sharing it online. In a bid to instill trust and collect the data they need, companies will continue to mend all loopholes for security breaches. Like data governance, security is one of the hottest business intelligence trends in healthcare and financial services.
Artificial intelligence (AI) has taken every business aspect by storm, and business intelligence is no exception. The outsized potential of this technology, promises to augment human intelligence by revolutionizing the way we interact with business data and analytics.
So, have we seen the best of AI in BI yet?
The answer is a big NO! However, there is a consensus that AI can process vast quantities of data faster than humans. Besides, the technology offers a unique perspective in business intelligence and makes it easy to unearth insights that have gone previously unnoticed.
Furthermore, the ability to clarify the relevance of bits of information on a granular level and understand how data metamorphoses into real business decisions seem too attractive to forego. As a result, organizations are in a rush to embrace the confluence of AI and BI in business. No one wants to play catchup later.
Of course, there are risks involved, and businesses are well aware of this fact. For example, many AI and machine learning systems are currently unable to “look under the hood” to glean the logic behind decisions. But the adage ‘necessity is the mother of invention” holds here. The need for increased transparency in AI-powered BI systems has given birth to explainable AI.
Explainable AI is an exercise of understanding and presenting clear-cut views into machine learning systems. With such developments cropping up, it won’t be long before AI can justify its decisions in an intelligible manner. We expect more critical developments to emerge in the coming year(s). All that said, we do not see the AI trend in BI going anywhere: its disruptive impact will be felt beyond 2021.
These days, data is the livelihood of any business. Data helps a company predict customer expectations, obtain competitor information, execute effective product management, and make informed top-down decisions. There is no doubt big data has a tremendous impact on the trajectory of any business.
However, there is one critical caveat – if the data is not accurate, up-to-date, consistent, and complete, it can destroy business value and deplete profitability. IBM intimates that, in the US alone, businesses lose $3.1 trillion every year because of poor data quality (IBM). Poor data quality is a problem that has long plagued enterprises of all sizes. Consequently, the problem is poised to worsen as data sources increasingly become interwoven.
The rise of the Data Quality Management (DQM) trend is a welcome relief for all businesses. Data quality management is an integral process that combines technology, process, the right people, and organizational culture to deliver data that is not only accurate but also useful. More importantly, data quality is not about being good or bad; its a range of metrics that measure the health of data used for analysis.
Data quality management (DQM) provides insights into data pumping through a business. It improves the data governance framework and enforces data standardization, ensuring that data used for analysis can provide a clear picture of the day-to-day business operations. As a result, business leaders can make accurate decisions that drive the business forward.
Data Quality Management (DQM) was one of the hottest business intelligence trends in 2019. Today, every business wants to implement data quality processes to enhance its ability to utilize business intelligence. Going by the significance it has gained, this trend is set to continue to cause ripples in 2021.
Actionable analytics is one of the hottest analytics and business intelligence trends in 2020 and it is bound to continue in 2021 and beyond. Traditionally, business intelligence data and insights were not consumed in the same place. However, in a bid to stay on top of business workflows and processes, businesses are no longer interested in analyzing data in one silo and taking action in another.
Luckily, modern BI tools have evolved to put corporate data where users want to take action. The platforms are merging with critical business processes and workflow through features like embedded analytics, dashboard extensions, and APIs. As a result, it’s now easy to implement actionable analytics to expedite the decision-making process.
What happens is that with these capabilities, business users can work on data, derive actionable insights, and implement them all in one place. Additionally, modern BI tools feature mobile analytics to deliver unique capabilities where the user is. Moreover, putting actionable analytics in context helps customize insights to the specific department, business, or industry. Even though this is one of the emerging trends in business intelligence, its popularity is already widespread.
Already, several frontrunners are trailblazing the way for this trend. For example, Looker is one of the most well-known embedded analytics software driving the trend forward. On the other hand, Sisense has plans to invent new analytics delivery models. Lastly, SharePoint is providing internal portals to enable organizations to embed analytics.
Since 2017, data discovery has been one of the most important business intelligence trends. Data discovery is a business user-centric process of collecting data from multiple silos and databases and assembling them into a unified source to simplify analysis.
So, why is data discovery important? It’s no secret, today, businesses can easily collect information regarding customer buying patterns, supply management, customer feedback, and more. However, even with the vast amount of data, many are unable to draw actual value from every bit of information. Why?
This is because of the mismatch that exists between people who prepare corporate information for analysis and people who perform the analysis and consume the insights.
Interestingly, data discovery systems help businesses get around this problem. It makes it easy for people with no IT skills to access and drill down into data to derive the information they need. This way, non-tech users can explore corporate information and obtain actionable insights to make fast, informed decisions based on their discoveries.
More importantly, with data discovery, it’s easy to find specific patterns and trends in a data set. Using robust data visualization tools makes this process intuitive, fun, and fast. Data visualization is way better than the usual static reports.
Data visualization has advanced to include heat maps, pivot-tables, and geographical maps. As a result, businesses can now create high-fidelity presentations of their discoveries. The data discovery trend is poised to persist as one of the most critical business intelligence trends in the coming years.
There you have it, our compilation of the hottest business intelligence trends that will shape the industry in 2021 and beyond. It’s hard to accurately tell the direction the BI industry will take. Thankfully, with these trends, we have an inkling of the exciting things to expect in the coming years.
Currently, there is overwhelming pressure for industry players to implement strategies like storytelling, data discovery, data quality management, and collaborative BI. On the other hand, emerging technologies such as AI and NLP, are playing a significant role in driving the industry forward. Most importantly, data governance and security have become critical to business intelligence.
Even with the challenges brought about by the pandemic, the BI landscape is rapidly shifting. As a result, to remain relevant and competitive, businesses must implement robust business intelligence tools and keep close tabs on these trends. But more importantly, you should have the right business intelligence analytics skills to make the most out of your tools. You can read one of our posts to understand the business intelligence skills you should have.
FinancesOnline is available for free for all business professionals interested in an efficient way to find top-notch SaaS solutions. We are able to keep our service free of charge thanks to cooperation with some of the vendors, who are willing to pay us for traffic and sales opportunities provided by our website. Please note, that FinancesOnline lists all vendors, we’re not limited only to the ones that pay us, and all software providers have an equal opportunity to get featured in our rankings and comparisons, win awards, gather user reviews, all in our effort to give you reliable advice that will enable you to make well-informed purchase decisions.