No organization can function without data. In recent years, big data has gained more importance due to changing world dynamics amid COVID 19 pandemic. It helps streamline business operations, optimize workflow processes, understand consumer behavior, improve marketing techniques, accelerate sales, boost employee satisfaction, make personalization possible and enable your company to embrace change. Moreover, it provides predictive maintenance and analytics to identify problems and opportunities that occur in real-time. 

For the most part, big data drives business intelligence software solutions, allowing businesses to stay competitive in the age of digital transformation.  

Big data empowers value-added business intelligence

BI has drastically changed the way people and businesses view, use and implement data. It has evolved the concept, strategy, and use cases across different industries. Specifically, with the emergence and evolution of modern technologies like cloud, quantum and edge computing, Internet of Things, artificial intelligence, and data science, BI data has become more prevalent for enterprises to understand their operational potential and customers better.

What’s trending in BI?

According to Beroe Inc., “the global BI market share is forecasted to grow at 12.6% CAGR and is expected to hit $30.9 billion by 2022.”

Let’s take a closer look at some current BI trends that will continue growing in 2022 and beyond.

Data Literacy and Management 

Global businesses have started prioritizing data-driven cultures and data literacy programs with the increasing BI adoption rate. They have realized the value-added benefits of data empowered actionable intelligence, enabling business users to make well-informed decisions without depending on IT or data science teams.

Data literacy plays a crucial role in developing data-driven cultures in organizations. Besides, enterprises prioritize data quality management (DQM) as part of their corporate strategy to guarantee compliance with global data governance and data quality standards.

Data Quality StandardsCore Aspects of Data Governance Plugged into Corporate Strategy for Enterprise Success

Data Quality is essential for accurate analytic and business insights because it can cost enterprises millions. Bad data means inaccurate insights, resulting in poor business decisions. This makes DQM a major differentiator of a good BI platform. So, in 2022, data literacy initiatives and investments in DQM tools will receive significant attention.  

AI Integration in Mainstream BI

Modern technologies like AI and BI are taking a great shape in the age of digital transformation and automation. In the past couple of years, AI has gained significant momentum that will continue to grow this year, with enterprises combining it with BI for deeper insights and improved decisions.

A PwC survey on AI as a mainstream technology found that 86% of businesses envision rolling out AI across the enterprise. Although AI and BI are both transformative technologies growing at a rapid pace, when combined will help speed up the data analysis process with efficiency and accuracy.

As they parse big data, Enterprises are more likely to focus their AI efforts to optimize complex processes through a better understanding of relationships across business entities and data points.  

PwC 2021AI Predictions Source: PwC 2021 AI Predictions

This AI adoption at every facet of an organization will help move its digital operations with end-to-end dynamic modeling, integrated business planning, and intelligent solutions.

Widespread Cloud Adoption

COVID-19 has pushed the world to adopt hybrid solutions – from hybrid work models to hybrid cloud. This resulted in a drastic surge of Cloud BI. As a result, a significant percentage of businesses migrated to public cloud or hybrid cloud, and many subscribed to SaaS (Software as a Service) to outsource their BI services – while ensuring scalability and flexibility of services.

With this expansion of Cloud-SaaS adoption, the concept of cloud BI significantly increases in importance that 54% of enterprises consider it a ‘critical’ to ‘very important’ element of their current and future business strategies.   

Cloud BI

Source: Dresner Advisory Services; 2020 Cloud Computing and Business Intelligence Market Study

Several businesses, including manufacturing, supply chain, BFSI, etc., are most likely to adopt Cloud BI technology this year.  

Automation Unlocking BI Potential

In recent years the amount of data enterprises collects, store and analyze has increased exponentially. This highlights the importance of automated business intelligence and data analysis – delivering quick computation and avoiding data noise and analysis paralysis.

When AI-powered BI, analytics, and automation become unified, it increases the enterprise’s ability to build a data-driven culture, monetize data, and reduce risk.

A Harvard Business Review (HBR) report states that 86% of enterprise respondents consider extracting new value and insights from existing data as “very important.” And, for 75% of the respondents, an enterprise’s ability to deliver customized and actionable intelligence effectively to employees is critical to becoming truly agile, innovative, and competitive.

This makes automation vital for data-driven intelligent enterprises. Again, AI can best automate data analysis – benefitting the organizations with quick data processing and augmented analytics that will eventually help transform the BI workflow.

Automation in BI delivers analytics maturity and actionable intelligence, which is mission-critical for most organizations to outperform in the data-driven future.  

Embedded Data Analytics

Embedded analytics, a consumer-facing BI tool, is fast becoming a trend. It facilitates speedy data collection and report sharing, allowing businesses to make the decision-making process swift and error-free. The real-time data combined with predictive analytics help organizations react proactively to important business events predicted. In addition, it helps protect their business from sudden changes and unexpected risks.

Embedded analytics market size is projected to grow at 13.6% CAGR and is expected to hit $60,281million by 2023, according to Allied Market Research Report on Global Opportunity Analysis and Industry Forecast, 2016-2023.

Global Embedded Analytics

Source: Allied Market Research Report  

Embedded analytics pertains to integrating data analytics capabilities within cloud native applications like CRM, ERP, marketing automation, and financial systems, ensuring quick data analysis without moving data from one software environment to other.   

NLP-Driven BI

NLP (Natural Language Processing) has dramatically transformed the way humans interact with data by eliminating the need for a translator. Integrating NLP in BI systems as many enterprises did in recent years, BI vendors can simply converse with their data without requiring a decoder between human language and machine language.  

NLP-powered BI solutions are more accessible and understandable to non-technical business users. They can inquire about anything in plain English, and the system will respond in conversational language – enabling BI tools to user-required information in clear and comprehensible language.

In 2022, NLP will continue evolving the core communication in enterprise-grade BI solutions.

Future of Business Intelligence & Analytics

Considering the current shifts in business intelligence software trends, we can safely assume that NLP, AI, DQM, and virtual analytics will experience massive growth and strengthen their foothold in the next few years.