Top 10 Analytics And Business Intelligence Trends For 2021

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. We all gained access to the cloud. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts.

2020 was a particularly major year for the business intelligence industry. The trends we presented last year will continue to play out through 2021. But the BI landscape is evolving and the future of business intelligence is played now, with emerging trends to keep an eye on. In 2021, BI tools and strategies will become increasingly customized. Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics, but what is the best BI solution for their specific business.

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story, especially with the help of modern BI dashboard software. 2021 will be the year of data security and data discovery: clean and secure data combined with a simple and powerful presentation. It will also be a year of collaborative BI and artificial intelligence. We are excited to see what this new year will bring. Read on to see our top 10 business intelligence trends for 2021!

Let’s Discuss These 10 Business Intelligence Trends

1) Artificial Intelligence

We will start our analysis of what is new in business intelligence with AI. This is one of the major trends chosen by Gartner in their Strategic Technology Trends report, combining AI with engineering and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. Artificial intelligence (AI) is the science aiming to make machines execute what is usually done by complex human intelligence. Often seen as the highest foe-friend of the human race in movies (Skynet in Terminator, The Machines of Matrix, or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite of the legit warnings of some reputed scientists and tech-entrepreneurs.

While we work on programs to avoid such inconvenience, AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account. The fact is that it is and will affect our lives, whether we like it or not.

Businesses are evolving from static, passive reports of things that have already happened to proactive analytics with dashboards that help businesses to see what is happening at every second and give alerts when something is not how it should be. Solutions such as an AI algorithm based on the most advanced neural networks provide high accuracy in anomaly detection as it learns from historical trends and patterns. That way, any unexpected event will be immediately registered and the system will notify the user.

Another feature that AI has on offer in BI solutions is the upscaled insights capability. It basically fully analyzes your dataset automatically without needing an effort on your end. You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on. Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis. That is an incredible time gain as what is usually handled by a data scientist will be performed by a tool, providing business users with access to high-quality insights and a better understanding of their information, even without a strong IT background.

Time gain is also present in the form of AI assistants. Tools have started to develop artificial intelligence features that enable users to communicate with the software in plain language – the user types a question or request, and the AI generates the best possible answer.

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote statistical analysis and management at the top of the priorities list. However, businesses today want to go further and predictive analytics is another trend to be closely monitored.

Another increasing factor in the future of business intelligence is testing AI in a duel. To illustrate, one AI will create a realistic image, and the other will try to determine whether the image is artificial or not. This concept is called generative adversarial networks (GANs) and can be used in online verification processes, like CAPTCHA technology. When the dueling happens several times, the AI can become smarter to evaluate and break that kind of online security systems. Tech giants use AI in many different ways that will alternate the machine learning process and we should keep an eye on this process in 2021.

2) Data Security

Data and information security have been on everyone’s lips in 2020, and it will continue to buzz the world in 2021. The implementation of privacy regulations such as the GDPR (General Data Protection Regulation) in the EU and the CCPA (California Consumer Privacy Act) in the USA have set building blocks for data security and management of users’ personal information.

Moreover, the recent overturn by the European Court of Justice of the legal framework called Data Privacy Shield hasn’t made software companies’ life much easier. The Shield was a legal framework that enabled companies to transfer data from the EU to the USA but, with recent legal developments causing the invalidation of the process, companies that have their headquarters in the US don’t have the right to transfer any of the EU data subjects. Actually, a similar situation we had already in 2015 when the EU and the USA had also no legally valid agreement for a while. Many US-based (software) companies argue that they use European servers, and there is no data transfer to the US at all. However, from a legal perspective, even this solution is questionable, as, in theory, the US judiciary could force US-based companies to reveal even data from EU-based servers. In essence, the data that is located in the EU needs to stay in the EU. In practice, that means that EU-based businesses that use in the current situation US-based software vendors that store any kind of data for them are taking hazards as they operate in a legal grey area. For companies such as datapine, this doesn’t represent a big issue since the registration, business, and servers are located in the EU.

No matter the developments, worldwide spending on information security products and services will increase by 2.4% in comparison to last year (and reach $123.8 billion). Although the pandemic has affected the growth, it certainly didn’t completely stop it. Gartner underlines the main drivers to global security spending (see the table below):

• Privacy regulations
• The need to address digital business risks
• Focus on building detection and response capabilities

Since data breaches have been regularly in the news, buzzing industries, and average users, the demand for security products and services is understandable.

3) Data Discovery/Visualization

Data discovery has increased its impact in the last year. A survey conducted by the Business Application Research Center listed data discovery in the top 2 business intelligence trends by the importance hierarchy. BI practitioners steadily show that the empowerment of business users is a strong and consistent trend.

*Source: Business Application Research Center*

An essential element to consider is that data discovery tools depend upon a process, and then, the generated findings will bring business value. It requires understanding the relationship between data in the form of data preparation, visual analysis, and guided advanced analytics. “The high demand for data discovery tools reflects a huge shift in the BI world towards increased data usage and the extraction of insights,” the Research Center emphasizes. Using online data visualization tools to perform those actions is becoming an invaluable resource to produce relevant insights and create a sustainable decision-making process. That being said, business users require software that is:

• Easy to use
• Agile and flexible
• Reduces time to insight
• Allows easy handling of a high volume and variety of data

Discovering trends in business operations that you didn’t even know were there or enabling immediate actions when a business anomaly occurs have become invaluable tools in effectively managing businesses of all sizes.

Data visualization has evolved into a state-of-the-art solution to present and interact with numerous graphics on a single screen, whether it’s focused on developing sales charts, or comprehensive interactive reports. The point is that data discovery is a process that enables decision-makers to reveal insights and by using visualizations, teams have the chance to spot trends and major outliers within minutes.

Since humans process visual data better, the data discovery trend will find increment as one of the most important BI trends in 2021.

4) SaaS BI

One of the business intelligence technologies that has seen a great shift in the last year, and will continue to shape how we perform business tasks is, of course, SaaS. The future of business analytics lays in the possibility to perform own analysis, with tools that are accessible no matter the location, and can adjust to current and future working conditions.

The pandemic has shown that remote working is becoming a norm, especially for companies that don’t rely on daily human contact to perform their regular tasks. Many businesses have turned to SaaS BI in order to gain more flexibility and access the data on the cloud, from any device. Such technologies, that enable data movement and access from multiple places will continue to rise as one of the most important business intelligence trends in 2021. We will certainly keep an eye on it since the shift from traditional settings to remote business opportunities enable people to access their analytics with the help of SaaS, and pushed the market, again, in the center stage of business management and development.

SaaS is becoming a best friend to remote and disparate teams that need solutions that will help them to optimize their business processes and ensure there are no bottlenecks by working remotely. In fact, if we take a closer look at the Forbes’ Cloud 100 list, we can see that capital is flowing into shares of SaaS, databases, automation tools, and fintech companies.

We can say that this is not a surprise in the current environment. A well-developed business intelligence technology can help companies in many ways, and ensure sustainable growth, which we certainly need in these uncertain times.

5) Predictive And Prescriptive Analytics Tools

Business analytics of tomorrow is focused on the future and tries to answer the questions: what will happen? How can we make it happen? Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. It’s an extension of data mining which refers only to past data. Predictive analytics includes estimated future data and therefore always includes the possibility of errors from its definition, although those errors steadily decrease as software that manages large volumes of data today becomes smarter and more efficient. Predictive analytics indicates what might happen in the future with an acceptable level of reliability, including a few alternative scenarios and risk assessment. Applied to business, predictive analytics is used to analyze current data and historical facts in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Industries harness predictive analytics in different ways. Airlines use it to decide how many tickets to sell at each price for a flight. Hotels try to predict the number of guests they can expect on any given night in order to adjust prices to maximize occupancy and increase revenue. Marketers determine customer responses or purchases and set up cross-sell opportunities, whereas bankers use it to generate a credit score – the number generated by a predictive model that incorporates all of the data relevant to a person’s creditworthiness. There are plenty of big data examples used in real life, shaping our world, be it in the buying experience or managing customers’ data.

Predictive analytics must also become accessible for everyone, and in the year 2021, we will witness even more relevance that will cater to that notion. Self-service analytical possibilities are becoming a criterion for BI vendors and companies alike; both can profit from it and bring more value to their businesses. The predictive models, in practice, use mathematical models to predict future happenings, in other words, forecast engines. Users simply select past data points, and the software automatically calculates predictions based on historical and current data, as shown in the example:

**click to enlarge**

Among different predictive analytics methods, two are quite popular among data scientists: artificial neural networks (ANN) and autoregressive integrated moving average (ARIMA).

In artificial neural networks, data is being processed in a similar way as in biological neurons. Technology duplicates biology: information flows into the mathematical neuron, is processed by it and the results flow out. This single process becomes a mathematical formula that is repeated multiple times. As in the human brain, the power of neural networks lies in their capability to connect sets of neurons together in layers and create a multidimensional network. The input to the second layer is from the output of the first layer, and the situation repeats itself with every layer. This procedure allows for capturing associations or discovering regularities within a set of patterns with the considerable volume, number of variables, or diversity of the data. ARIMA is a model used for time series analysis that applies data from the past to model the existing data and make predictions about the future. The analysis includes inspection of the autocorrelations – comparing how the current data values depend on past values – especially choosing how many steps into the past should be taken into consideration when making predictions. Each part of ARIMA takes care of different sides of model creation – the autoregressive part (AR) tries to estimate the current value by considering the previous one. Any difference between predicted data and real value is used by the moving average (MA) part. We can check if these values are normal, random, and stationary – with constant variation. Any deviations in these points can bring insight into the data series behavior, predicting new anomalies, or helping to discover underlying patterns not visible by the bare eye. ARIMA techniques are complex and drawing conclusions from the results may not be as straightforward as for more basic statistical analysis approaches. But once the basic principles are grasped, the ARIMA provides a very powerful tool for predictive analysis.

Prescriptive analytics goes a step further into the future. It examines data or content to determine what decisions should be made and which steps taken to achieve an intended goal. It is characterized by techniques such as graph analysis, simulation, complex event processing, neural networks, recommendation engines, heuristics, and machine learning. Prescriptive analytics tries to see what the effect of future decisions will be in order to adjust the decisions before they are actually made. This improves decision-making a lot, as future outcomes are taken into consideration in the prediction. Prescriptive analytics can help you optimize scheduling, production, inventory, and supply chain design to deliver what your customers want in the most optimized way, and these are some of the trends in business intelligence 2021 that we will hear more about.

6) Real-time Data & Analytics

The need for real-time data has tremendously evolved this year and will continue to do so in 2021. We have seen since the pandemic arrived, that the needs for real-time and accurate updates are critical in developing proper strategies to respond in such unfortunate situations. Some countries have used data to make the best possible decisions, and companies followed to ensure survival in these uncertain times. Real-time access to data has become a norm in everyday life, not just for businesses, but the general public as well, where we could see press conferences filled with the most recent information, graphs, and statistics that have defined some of the strategies against the pandemic. But not only; creating ad hoc analysis has enabled businesses to stay on top of changes and adapt to immense challenges that this year has brought.

In business is similar: forecasting and alarms will inevitably become used much more in developing proper business responses and strategies for future endeavors with more variables brought into the equation. Moreover, implementing live dashboards will help companies to immediately access relevant information regarding their business and react if any potential issues arise. Up-to-date data is becoming more important than ever before, and since the world has changed, companies need to adapt as well. High gear for data access is becoming the norm and is one of the reasons why some companies can survive, and others not.

Analytics industry trends will certainly have real-time data as one of the main drivers in 2021 and we will, without a doubt, see more of it in action.

7) Collaborative Business Intelligence

Today, managers and workers need to interact differently as they face an always-more competitive environment. More and more, we see a new kind of business intelligence rising: the collaborative BI. It is a combination of collaboration tools, including social media and other 2.0 technologies, with online BI tools. This is developed in a context of enhanced collaboration addressing the new challenges the fast-track business provides, where more analyses are done and reports edited. When talking about collaborative BI, the term “self-service BI” quickly pops up in the sense that those self-service tools do not require an IT team to access, interpret, and understand all the data.

These BI tools make sharing easier in generating automated reports that can be scheduled at specific times and to specific people. For instance; they enable you to set up business intelligence alerts, share public or embedded dashboards with a flexible level of interactivity. All these possibilities are accessible on all devices which enhances the decision-making and problem-solving processes, critical for today’s ever-changing environment.

Collaborative information, information enhancement, and collaborative decision-making are the key focus of new BI solutions. But collaborative BI does not only remain around some documents’ exchanges or updates. It has to track the various progress of meetings, calls, e-mails exchanges, and ideas collection. More recent insights predict that collaborative business intelligence will become more connected to greater systems and larger sets of users. The team’s performance will be affected, and the decision-making process will thrive in this new concept. Let’s see how it will be developed in the business intelligence trends topics of 2021.

8) Mobile BI

Mobile business intelligence is becoming more incorporated into BI solutions and next year the trend will certainly not lose its importance. In fact, it is one of the most prominent emerging trends in business intelligence identified by almost 3000 professionals in the industry by the research we mentioned in our 3rd point of this article.

A few years ago, mobile BI was considered a huge swirl in the BI and analytics community. The market penetration is still growing, although slowly, but next year we will see even more vendors and BI solutions that will have this option within their software such as modern mobile dashboards. But not just vendors, companies will also implement mobile solutions and actively use them since it will provide them with numerous benefits: accessing your information at any time, and any place – while riding on a train or relaxing on a beach. Physical presence at an office site is less necessary each year and this is certainly affecting the BI industry as well. Mobile BI enables companies to have access to their data also in real-time, ensuring faster reactions to any business occurrences and giving more freedom to users that are currently not in the office but need to access critical business information on-the-go.

This is one of the business intelligence market trends that is not going to vanish anytime soon. Since it has been evaluated at USD 6.18 BN in 2018, it is also predicted to grow with a CAGR rate of 22.43% by reaching 2024. While there are challenges that are affecting companies’ decisions to implement mobile BI such as limited screen size and design of the interface to ensure the best possible usability, mobile is undoubtedly going to stay as one of the trends that will be considered by companies in 2021.

9) Data Automation

Business intelligence topics wouldn’t be complete without data (analysis) automation. In the last decade, we saw so much data produced, stored, and ready to process that companies and organizations were seriously looking for modern data automation solutions to tackle massive volumes of information that has been collected. A survey by KDNuggets predicts that in the next decade, data science tasks will be automated, hence, this is one of the trends in business intelligence that we need to keep an eye on since we don’t know when it will exactly happen.

Dozens of tools and disparate sources are still part of the bottleneck that businesses are facing today. BI has come to the solution to enable users to consolidate all the data that a company manages and provides methods to discover, analyze, measure, monitor, and evaluate large scale data. We have mentioned hyperautomation in our article for the top 10 IT buzzwords which Gartner predicts will explode in the next year, and we certainly agree.

Business intelligence has brought many automation possibilities and in 2021, we will see even more. Long-standing barriers between data scientists and business users are being slowly mixed into a one-stop-shop for any data requirement a company might have – from collecting, analyzing, monitoring, and reporting on findings. A scenario might include intelligent reporting – predictive analytics and automated reports increase the business users’ capabilities to automate data on their own, without the help of the IT department. On the other hand, data scientists still will manage complex analysis where manual scripting and coding is necessary.

Let’s now tackle the last of our BI and analytics trends 2021!

10) Embedded Analytics

When data analytics occurs within a user’s natural workflow, embedded analytics is the name of the game. Businesses have recognized the potential of embedding various BI solutions such as KPI dashboards or reports into their own application and thus improving their decision-making processes and increasing productivity. Formerly strangled by spreadsheets, companies have realized how utilizing embedded BI enables them to provide higher value within their own applications. In fact, according to Allied Market research, the embedded analytics market is projected to reach $60.28 BN by 2023, with a CAGR of 13.6% from 2017, and this is one of the business analytics topics we will hear even more in 2021.

Whether you need to create a sales report or send multiple dashboards to clients, embedded analytics is becoming a standard in business operations, and in 2021, we will see even more companies adopting it. Departments and company owners are looking for professional solutions to present their data without the need to build their own software. By simply white labeling the chosen application, organizations can achieve a polished presentation and reporting which they can offer to consumers. This is one of the trends in analytics that can be implemented immediately since many vendors already offer this opportunity and ensure that the application works seamlessly and without much complexity.

What Are The Analytics & Business Intelligence Trends For 2021?

We’ve summed up in this article what the close future of business intelligence looks like for us. Here are the top 10 analytics and business intelligence trends we will talk about in 2021:

1. Artificial Intelligence
2. Data Security
3. Data Discovery/Visualization
4. SaaS BI
5. Predictive And Prescriptive Analytics Tools
6. Real-time Data And Analytics
7. Collaborative Business Intelligence
8. Mobile BI
9. Data Automation
10. Embedded Analytics

Become Data-driven In 2021!

Being data-driven is no longer an ideal; it is an expectation in the modern business world. 2021 will be an exciting year of looking past all the hype and moving towards to extract the maximum value from state-of-the-art online business intelligence software.

If you’re ready to start your business intelligence journey, or keep up with the 2021 trends, trying our software for a 14-day trial will do the trick! And it’s completely free!

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