Data never stops, and neither does business. Despite a rough two years disrupted by the worldwide COVID-19 pandemic, business intelligence is more important now than ever for enterprises to make data-informed decisions. BI tools and analytics platforms have come a long way with business intelligence trends like artificial intelligence, the cloud and mobility.
What’s in store for the industry in 2022? This article will look at the key business intelligence trends for this year and the near future.
Top Trends
- SaaS and Cloud Adoption
The COVID-19 pandemic put companies and industries in emergency mode as they scrambled to make sense of the situation. With on-premise solutions unable to measure up to the challenge of a largely remote workforce, many businesses were forced to look hard at their current BI strategies. More organizations seek to migrate to cloud-based BI this year, whether on a private or public cloud or SaaS solution.
Many companies are realigning their budgets post-pandemic to make room for adopting cloud infrastructure in the move towards remote and disparate workforces. Gartner predicts that by 2023, 40% of all enterprise workloads will be deployed in the cloud, up from 20% in 2020. Businesses now consider analytics a mission-critical capability, and companies aren’t shying away from adopting data solutions.
Mike Brody, CEO for Exago, a software vendor for embedded BI for SaaS providers, said their company adapted quickly to the transition to remote work; in fact, it’s thriving.
- Data Literacy
Companies are beginning to understand the importance of implementing data analytics throughout their organization. Instead of separating analysis and decision-making, businesses are now looking to put insights first. They want data to inform their every decision, from setting goals to developing strategies and finally taking action.
But to do so, they have first to establish and build up a firm foundation of data literacy. What is data literacy? According to Gartner, it’s the ability to read, write and communicate data in context – to put it simply, the ability to “speak data.” It’s key to increasing user adoption and maximizing the effectiveness of BI tools. Data literacy is important for all individuals, irrespective of their work profile and businesses.
Being able to interpret data, discover insights and ask the right questions are skills that can drive change in any role at any level of any organization. Data-driven business owners have to eliminate the data literacy gap between data analysts and non-technical users, a process known as data democratization.
Businesses must promote a data-first culture to drive data literacy and encourage employees to prioritize data. Teams across organizations need to learn how to analyze data and apply insights to their tasks through training and initiatives.
While it can be time consuming and difficult, investing in upskilling employees pays off. A study from the Data Literacy Index states that improving corporate data skills resulted in $320 million – $534 million higher enterprise value over organizations with lower data literacy rates. The question is no longer about whether data literacy is important but whether or not companies will make it their priority in 2022.
- Data Visualization and Storytelling
Storytelling and intuitive visuals are engaging ways to help clients understand critical insights. Data visualization turns business information into graphics and charts that users find easier to understand than blocks of text and numbers. Data storytelling puts data into context by building a narrative around critical metrics, whether through dashboards, interactive reports or beautiful visuals.
Dashboard software is evolving from simple KPI monitoring to in-depth data analysis through interactivity and augmented analytics.
According to data scientist and Chief Science Officer at DataPrime, Dr. Kirk Borne,
With AI-ML, users can request information in natural language and view the results in an easy-to-understand format. They can associate data with context to identify where to focus at any given moment and create alerts for changes in data. Collaboration enables information producers and consumers, and external stakeholders to work together in a single, centralized hub.
As such, BI software vendors will be focusing on how to help their users tell data narratives most effectively through visualizations and dashboards.
- The API Economy and Automation
Though building a software solution seems more cost-effective than purchasing one, enterprises often struggle with development logistics. Add in the pressure to pull information from on-premise platforms, the cloud, streaming applications and more, and it becomes overwhelmingly complex. Business applications should integrate seamlessly across interfaces, networks and clouds for faster time to insight.
Businesses can extend software’s functionality by integrating it with other applications. Application integration is ubiquitous; we use it even now, for instance, when we move from Facebook to an eCommerce site without exiting the application. It’s the API economy at work, and it’s shaping the present and future of analytics, with BI solutions bringing insights to users within their business applications.
According to a study, by 2023, 60% of organizations will be able to build tailored business solutions by integrating components from three or more disparate analytics solutions. Applications in a business ecosystem can also trigger workflows based on data changes through another trend in business intelligence – automation.
As analytics scales up to increasingly complex data volumes, automation is essential to eliminating manual data processes. Rapid data analysis and decision-making define business intelligence, and automation speeds up business processes, making it easier to get answers.
- Natural Language Processing (NLP)
The global NLP market, valued at $10.72 billion in 2020, is projected to grow to $48.46 billion by 2026, at a CAGR of 26.84%. NLP bridges the gap between computers and humans by eliminating the need for any programming language. It allows users to interact with data by asking questions in a conversational format, such as, “What was the revenue for the last quarter for Zone X?”
The next best thing after text-based queries is voice-based searches. By integrating this capability with voice-activated digital assistants on mobile devices, software vendors make data discovery even more user-friendly. Natural language generation (NLG) enables the software to generate answers that are easy to understand, irrespective of technical skills.
In business terms, NLG is one of the latest trends in business intelligence. It outputs the essential takeaways of a data visualization in conversational language, facilitating quick insight interpretation.
As NLP continues to mature and grow in the analytics space, it will keep breaking down technical barriers for non-skilled users, allowing them to use analytics insights.
- Autonomous BI
Self-service BI empowers users of all technical skills to access the data they need and utilize it effectively. Teams can sort and analyze data through ad hoc reporting, no need to wait for insights from the IT team. Out-of-the-box data connectors, intuitive interfaces and pre-designed workflows in enterprise BI tools let regular users do more with their data without technical help.
They can perform data science tasks like key driver analysis, what-if scenario simulation and predictive analytics through NLP. Data scientists can leverage ML-backed, low-code programming and interoperability to develop applications and integrate them with business platforms. Analytics and data science roles are overlapping now, thanks to greater autonomy being one of the most significant BI trends.
Brody said that Exago was founded on the concepts of data democratization and self-service reporting, though they never thought about it like that at the time. According to Brody, some of Exago’s clients have tens of thousands of end-users, each with the ability to create their own reports and control their data.
- Collaborative Insights
Two heads are better than one. How about two departments are better than one? Collaborative BI is emerging as a BI trend as connecting with others in real time to discuss and share insights becomes more critical than ever. With distributed teams becoming the norm, remote collaboration is here to stay.
Team members can interact with others within interactive reports and collaborative dashboards. Users can tag others, even clients, in comments and share data assets through links, email and Slack. Working together, teams can decide on the next steps, reducing the time-to-insight.
As organizations push towards data literacy, their users are able to work together to share business assets and tell visually engaging data stories.
- Data Governance
According to a Business Application Research Center survey, metadata and data quality management with information governance rank in the top significant BI trends for 2022. Data governance ensures the quality of business assets through role-based access, authentication protocols and auditing. When data is accurate, unique and up-to-date, users trust the insights are reliable, boosting revenue and reputation.
The global data governance market is projected to grow from $1.2 billion in 2016 to $4.9 billion in 2026 at a CAGR of 22.6%.
The General Data Protection Regulation (GDPR), designed to protect individual personal data, falls under the purview of data governance. It is especially true for healthcare and financial services that demand personal data confidentiality. Information governance compliance is a legal mandate now, and BI tools with built-in compliance will have the edge over those that don’t.
- Moving Towards Mobile
With shifting work patterns and business demands due to COVID-19, companies worldwide are looking to equip their remote workers with productivity-enhancing software. These include SaaS solutions for access to reports and dashboards at any time, anywhere. According to Mordor Intelligence, the mobile business intelligence market is expected to grow by a CAGR of 22.4% by 2024.
While most internet users access the internet via mobile, market share isn’t the only reason to implement mobile BI. Users can opt to receive KPI-based alerts and react promptly to events as they happen. Mobile BI features a responsive, lite version of the main analytics platform, placing the power of insights directly in the user’s hands wherever they go.
This on-demand availability of information enables faster decision-making, shorter workflows and more effective internal communication. Though limited screen size and functionality can be restrictive, mobile analytics is a game-changing trend in business intelligence. Mobility is part of many software vendors’ offerings in response to companies’ BI requirements lists for 2022.