As we enter 2023, it is a good time to explore the biggest data analytics and BI trends for this new year. This article will look at the top 12 trends in data analytics and BI, which collectively guide the education, health care, economic, and environment sectors. 

In a data-first business ecosystem, data and analytics are jointly transforming the commercial world, and all emerging data analytics and BI trends seem to suggest that the global commercial world is rapidly evolving toward data-centricity. All 12 trends indicate that businesses are quickly becoming data-centric to remain competitive and successful in the global business landscape.

In 2023, data will enable businesses to create superior products and services, streamline operations for cost savings, and understand customer needs and expectations. Till 2030, the worldwide data analytics market will continue to grow at a CAGR of nearly 30%, reaching over $329.8 billion. This forecast indicates that every business needs to extract the maximum benefit from data.

Data Analytics Trends Projected for 2023

Gartner reminded readers to keep a close watch on 12 data and analytics trends in 2022. Taking this as a starting point, here are major data analytics and BI trends that will continue to dominate in 2023:

• The rising adoption of cloud platforms for enterprise data-center activities are making real-time data monitoring and analysis possible. The cloud platform offers several advantages over in-house data centers: scalability, reduced operational costs, wider selection of analytics and BI resources, and zero in-house Data Management. Hybrid clouds are even better with their scalable, secure, and cost-friendly solutions. According to Gartner, 50% of business data will be created and processed outside the data center by 2025.

• The growing popularity of data fabric as a preferred data analytics architecture will continue in 2023 on a bigger scale. Data fabric not only integrates all distributed data points seamlessly, but also enables automated Data Management processes from data acquisition to data analysis.

• Thanks to cloud-based Data-as-a Service (DaaS), data from inside and outside the business can be combined for advanced BI tasks. Data-as-a-Service (DaaS) is a technology that incentivizes users to use and access digital assets through the internet. Using DaaS for big data analytics would streamline the task of reviewing corporate data for analysts, while making data sharing easier between departments and industries. 

• Augmented analytics is allowing sophisticated tools to replicate Data Science tasks like data collection, data preparation, data cleaning, and automated analytics ­– which were originally handled by human experts. Augmented analytics uses machine learning (ML) and natural language processing (NLP) to automate the data analytics process. Thus, advanced data technologies enable businesses to analyze data and extract insights much faster than manual processes, becoming increasingly better at their jobs. This trend is likely to see various developments over the next few years, playing an important role in the rise of BI platforms.

• Augmented Data Management is helping businesses collect, clean, and analyze data and report results much faster while easing Data Management tasks for human employees. 

• Adaptable AI, by using continuous, real-time feedback on data and tools, is churning out newer and better data analytics methods. Adaptable AI will soon make data analytics and BI truly democratic activities – by reducing manual labor, delivering accurate predictions, and empowering any business staff to make quick decisions, regardless of their role or technical skills.

• Edge computing (data processing at the edges of the network, closest to data sources) is a technology approach that has been growing in popularity within corporate circles in the past decade. IDC forecasts that by 2023, 50% of new IT practices will take place on the edge. As real-time analytics gain popularity due to IoT devices, 2023 may witness a sudden spike in edge computing, facilitating data analytics and AI very close to the origin of data. 

• The rise of “people analytics” in 2023 will help HR leaders transform employee data into insights for guiding strategic hiring decisions – something that is becoming more vital to organizations of all types. In 2023, companies will increasingly focus on people analytics to create better employee experiences and achieve better business outcomes. The final idea is to capture employee data to fulfill their expectations without threatening their privacy. 

• Energy-efficiency analytics is the new buzzword in the world of global business analytics, where energy-management software and AI collaboratively enable developers to create sustainable technologies, which in turn creates new business opportunities for business leaders. 

BI Trends Projected for 2023

The 2023 BI trends will be a combination of some 2022 trends and a few exciting opportunities opening up due to advancements in data technologies. Although Data Quality management is on top of most lists for 2023, data democratization, real-time BI, Data Governance, and data discovery are also common trends found across lists: 

• BI and data visualization: With data visualization gaining tremendous importance in the world of big data analytics, now is the time when global businesses need highly sophisticated dashboards and smart graphics tools for viewing, sharing, and presenting critical information.

• Data Quality management: In 2023, Data Quality management will mean combining a DQM strategy with a strong, enterprise-wide data culture. This approach will keep its focus on cloud technologies for Data Management, advanced AI/ML models for Data Quality management, building trust architectures and other Data Governance frameworks. 

• Self-Service business intelligence: Self-service BI has put power tools in the hands of ordinary business users and trusted them to discover their own trends, insights, and profit opportunities. So now, businesses of all shapes and sizes can dream big and empower their employees to become citizen data scientists or business analysts. The cloud platform offers an added advantage for self-service BI practice because most of the advanced technological capabilities are offered “as-a-service” models through the cloud.

What’s Next for Data Analytics and BI?

In 2023, edge computing will bring these business benefits: more real-time analytics, accelerated analytics, and bigger big data analytics. Enterprise BI is gradually transforming into a revenue center. In 2023, don’t be surprised if you find at least a third of big companies are practicing BI as a service. Lastly, natural language processing will gain more importance in tracking competitive market intelligence.

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