Top Business Intelligence Trends for 2021

Every day each of us produces an enormous amount of data. From the moment we open our eyes and first check our social media feeds for new messages and likes. Creating a route to work via a new coffee shop. Buying coffee and a bun, we use a credit card for payment. Even if you won’t use the Internet on your devices, even the data about your inactivity will also be produced and analyzed. Numerous sensors, surveillance cameras, and satellites will create your data profile.

On average, every person generates at least 1.7 MB of data per second. And the number of Internet users grows day by day, which means more and more data. For example, 2020 brought us 319 million new internet users besides 4.66 billion already active internet users. 

Increased uses of social media, messengers, cloud data, machine learning data, IoT devices that are used now in households, manufacturers, labs, and hospitals. Soon we will easily operate on terms like zettabytes and yottabytes, which contain twenty zeros in its figure.

So how can BI meet your business needs? We want to tell you about the newest business intelligence trends and how with their help receive valuable information from the data your business is generating right now. To boost business growth and improve its performance, in the modern world it is inevitable to root business strategy on customer data. Otherwise, standing out from competitors will be a much more difficult task. What your customers want, how they want, and when they want it. Analyzing real data for answering those questions may save you time and money on conducting the wrong advertising campaigns, warehouse logistics, and targeted sales.

BI reports do not only reveal true problems of your customers, that you can solve and gain profit, but they can also help to optimize your inner business processes, eliminate unnecessary costs and improve the productivity of your team. Creating useful reports requires previously pinpointing the most significant metrics. BI systems help accurately determine which of them you need by a given query. 

Data from many sources may arrive in different formats, sometimes such data comes in not the usual format. We call it raw if it is unsuitable for any insights until it is arranged. Arranging it is a complex process and may include such stages as extracting, transforming, and loading. Allow data scientists, analytics, and engineers team to handle it or lay it on self-service BI tools, it’s up to you. But first read about BI trends to learn the difference. 

BI in Cloud

What’s new in it? Recently, cloud computing became one of the most cutting-edge technologies that changed all the traditional concepts. For example, cloud computing made it possible to autoscale services like data storage and data operation, meaning they can scale up and down resources needed to process the ongoing request. 

Also, unlike traditional on-premise hosting, the cloud doesn’t require substantial hardware and is not limited to its capacity. Constant updating of hardware resources, its support staff, and facilities maintenance may be costing a fortune and the absence of timely updating may lead to a crash of the system and data loss. The future of business intelligence looks very optimistic because of the affordability of the cloud even for small and medium businesses. 

Benefits for business: Cloud computing may extend the possibilities of business intelligence trends and the newest BI tools to small and medium businesses that can’t afford self-contained terabytes of data warehouse and management systems. 

Besides the reduced costs of implementing and maintaining, the cloud lowers risks of malware and makes it easier to deploy BI tools. Also, it is a great opportunity for remote teams, as queries and reports can be accessed from any device. 

Real-world example: Reddit is one of the most popular websites in the US and its 430 million users per month all over the world obviously generate a vast amount of data. Moving to cloud BI and giving real-time access to the Reddit sales team, made it possible for them to monitor any brand mentions in thousands of hundreds of communities and naturally enter the discussion about the brand. 

Another example, Norway’s Oslo University Hospital with the help of Cloud BI could improve its operational efficiency. Numerous healthcare practices that were scattered out were able to share data in real-time to the common database in the cloud. Hospital CEO, doctor Eli Marie Sager mentions “We can understand what is happening in the departments in a few hours, rather than after months”.

Augmented Analytics

What’s new in it? Natural language processing is a part of Augmented Analytics and it allows querying data using our native language. That’s how any person, without special skills for creating SQL queries may be admitted to business insights in a readily used format. NLP also allows the output of data to be received in plain language for better understanding. 

Benefits for business: AI technologies take an active part in business intelligence trends formation. They can help to perform extensive data manipulation, which is impossible for humans. Augmented Analytics uses Machine Learning and Natural Language Processing to perform hours of data science teamwork in several seconds. That’s how implementing AI into BI processes allows people to leave all the routine work of transforming meaningless figures into valuable analysis and reports to machines. Meanwhile, people can spend their time generating policies and strategies to improve business profitability.

Real-world example:: Low-cost airline Ryanair uses customer information and Augmented Analytics to offer customers targeted services in the manner of Amazon. For example, when a registered customer book a hotel room for a whole family with three children, then he will be suggested to hire a minivan or SUV from the airport of their destination. It doesn’t only increase Ryanair’s profit by selling extra services but also improves customer satisfaction from dealing with the company. 

Self-Service BI 

What’s new in it? Traditional BI solutions are controlled by a team of data scientists. Only they have access to data and can operate with it. Not all companies can afford their own BI team. That’s why small and medium businesses are more attached to self-service BI. 

Self-service BI tools make data accessible to a larger public. Business intelligence trends require from tools an intuitive interface that allows people without technical expertise to work with data dashboards. That’s how all authorized users can find an answer to their queries in real-time. 

Among the most popular BI tools now are Microsoft Power BI and Tableau Desktop, both having easy-to-comprehend drag-and-drop interfaces. 

Benefits for business: The sales team can better and more quickly understand customer’s needs based on all the gathered data and its analysis. The finance team can immediately access data on previous expenses, see its comparison with the current situation and make professional forecasts. Moreover, the expensive time of the IT team does not spread over numerous requests, they free up for other tasks that require their attention. The faster your team makes decisions, the faster your business may develop. 

Real-world example: Coca-Cola company implemented self-service BI tools that provided the sales team with well-timed reports on all the purchases and deliveries taking place. Such a solution helped the Coca-Cola company offload the analytics team. Thus, they perform more complex tasks such as enterprise data management.

There is another example, with Ibotta company, that allows users to get cashback on their online purchases. They used to provide their 200 main clients—online stores with manual reports in Excel. Nowadays, when their client base is significantly larger, they provide customers with access to self-service BI, so that they can see which of their offers is most popular in the selected state or among the selected age. That allows managers to optimize current campaigns in a way to make more profit from them. 

Embedded Analytics

What’s new? While traditional BI systems gather data from numerous sources, embedded BI is integrated into business applications, websites, and portals. All the relevant data and reports are incorporated into the business software, with business specialist work on an ongoing basis. No need to switch to another product. 

Benefits for business: Employees using your business application can receive analytic insights right at the point of decision. Adopt BI insights to everyday workflow and make all business work on a data-driven basis. The ability to create an amazing analytical experience for your customers can also be used for deeper customer engagement. Or be an additional revenue stream in your software by itself.

Real-world example: The New York Times online publication uses embedded analytics to let users stay aware of constantly changing information. For example, at the beginning of the COVID-19 pandemic, people were very thrilled by monitoring new infection cases. The New York Times chart gives the ability to overview and query concrete regions, time periods, and the proportion of recovered/dead cases, number of vaccinated people, and other reports. 

Data Security

What’s new? Data loss is a nightmare for any business owner. Managing the data security for BI tools includes several rules.

First of all, make sure all the registered users signed policies that prosecute and appropriately punish those involved in illegal data disclosure. In some regions and business fields, specific privacy policies must be taken into consideration, for example, in FinTech, healthcare, social networks, or European GDPR. Such is HIPAA in healthcare.

Create users’ accounts with restricted access. Make sensitive information restricted for non-authorized and non-permitted users, and grant emergency access to several top managers in case the data warehouse is hacked. Protection of user login by two-factor authorization has become a regular practice to reduce cyber-attacks risks. 

For avoiding insecurity gaps, limit downloading data to any device and usage of public Wi-Fi networks. Separating data into different servers may become an additional way to protect your data. 

Benefits for business: A lot of huge companies break splashy stories announcing big data breaches, among them Facebook, Yahoo, eBay, and LinkedIn. Such gaps in cybersecurity affect millions of Internet users, revealing users’ personal data to hackers. Besides billions of dollars lost because of numerous scams and subsequent claims, regulatory fines, stock prices falling, and customers’ overall panic, the company may lose trustworthiness that can lead to company bankruptcy. 

Nowadays, according to the latest BI trends, data manipulations are available not only to BI developers but also to plenty of people involved in business, so the risk of data breaches grows significantly. In order to maintain public trust, you shouldn’t sacrifice data security in attempts to reduce the size of applications and simplify security solutions. The rapidity of implementing cyber-attacks prevention shouldn’t be a question either. According to IBM, the global average damage is $7 million for a breach. Though, in the case of one of the biggest data breaches on Yahoo, the company’s cost decreased by $350M of dollars. Data encryption may require extra expenses, but such a solution is worth the effort.

Real-world example: At the end of 2018, everyone was talking about the Marriott data breach. It was one of the most expensive lessons for business owners. The Marriott lost about 500 million guests’ data, including their passport information, phone numbers, credit card numbers, and their expiration dates. Investigation showed that the subsidiary company Starwood was contaminated with Remote Access Trojan long before the merger. That could happen via phishing email letters, so such a small mistake resulted in about $600 million losses.

DQM

What’s new? Data quality management (DQM) is a set of methods to prevent low-quality information flow processes. Not accurate data can badly affect BI, therefore data-driven decisions, and enterprise at all. To avoid such consequences, DQM identifies the poor-quality data, then cleans it up, and afterward makes its format usable for BI platforms. 

Moreover, it does not only clean low-fidelity data but also detects its flow to prevent entering poor-quality data into your database in the future. 

Benefits for business: If you are faced with doubt about the correctness of data your enterprise collects, then there are several problems DQM can solve. It can detect duplication of records and remove them, same as invalid data that enters your database. 

Also, DQM can deal with the identification of manual data entry. Thus, if your employees decide to edit the database with the data they collected on their own, DQM can detect it and it won’t permit imprecise data from being analyzed and reported along with data gathered from reliable sources. Money supply can also be distributed more reasonably, reducing costs on keeping and managing low-quality, useless data. 

Real-world example: Poor-quality data can have severe implications in fields like healthcare. Wrong data can lead to mistakes in treatment and in such a way can do irreparable damage to patients’ health and even death occurs for patients. There are numerous cases of medical errors related to mismatched test results or loss of important patients’ records. Hence, all the data must be taken very seriously. 

Collaborative BI

What’s new? Collaborative BI is also called Social BI because it helps to gather every of the team members’ thoughts on the data analysis in one place. It may be presented as the possibility to leave comments to dashboards, in the form of feedback or annotation. That form gains popularity as it is very convenient for remote teams to work with. 

Such BI solution also allows different subject experts to communicate over common information, contribute into expert areas, thus brainstorming over further business strategy and excluding the existence of conflicting decisions. 

Benefits for business: Creating simplified analytics and reports, available to all the departments of business, Collaborative BI increases collaboration within those departments. Knowledge sharing can directly impact the high speed of decision-making. 

Collaborative BI makes all the employees’ voices heard, in such a way giving workers additional motivation. All the employees can also clearly see how their conversations turn into decisions that are based on the data and the employees’ expertise in finding insights from it.

Real-world example: Clever uses Collaborative BI to create the most common single sign‑on platform for K–12 education. Engaging about 22 million students, parents, and teachers it is vitally important for Clever to get constant insights into how their users interact with their product. Clever created a special group of employees that have access to the BI tool and can share their reports, ideas, and advice with each other. Thus, the customer service team and their insights from support tickets can impact the developer team’s new feature implementation. That helps Clever to respond quickly to customers’ requests, and that’s how they stay on top.

Mobile BI

What’s new? The latest trends in business intelligence necessarily include Mobile BI that may be presented as an online web tool or, more often, as a mobile application. Modern device hardware has enough capability, that allows processing real-time queries to a database of any size. 

Benefits for business: Mobile BI gives access to data and possibilities to make real-time data queries to users from their mobile devices such as smartphones or tablets. It significantly facilitates the work of remote teams. Mobile BI can be as well used by the employees who work on the ground and who are in direct contact with a client, which allows businesses to be data-driven on every level. 

Real-world example: The FruitGuys company that sells fresh fruits started to use the Salesforce Desk.com Mobile BI solution, which helped them to connect with customers and their level of satisfaction of the service much quicker than via Gmail and helped to improve the customer experience. Besides customer service, the Mobile BI solution also helped FruitGuys receive insight into the optimization of their work with drivers, like what season requires more employers to hire and whether to hire for a part-time or full-day job. 

Conclusion

An increasing number of enterprises gather an enormous amount of data. To make data yield benefits, it should be properly collected, structured, and make sense to direct participants in the business. Hiring a BI team to maintain business analytics and generate reports may be complex, long-lasting, and expensive. Even huge companies such as Coca-Cola, Ryanair, and Clever prefer to implement user-friendly BI tools into their systems.

NIX is aware of all BI trends and knows how to make them work in your field. Don’t waste time and money on moves that won’t let you win the fanbase of customers. Bit all the competitors using data prediction and being far ahead. Get performance and customer analysis, budget reports, and the required data to make informed decisions on all levels of your business with NIX’s help.