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Top 10 Business Intelligence Trends to Look for in 2023

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Read on for the top 10 business intelligence trends to look out for in 2023!

Business intelligence (BI) combines business analytics, data mining, data visualization, data and infrastructure tools, and best practices to help organizations make more data-driven decisions. We hope that these business intelligence trends will help prepare your company to meet a more expansive, connected, and data-driven global market in the next few years. The business intelligence landscape is evolving and the future of business intelligence is now in play, with emerging trends to watch. Read on for the top 10 business intelligence trends for 2023!

Artificial intelligence: Artificial intelligence (AI) is the science that aims to get machines to do what complex human intelligence normally does. Artificial intelligence and machine learning are revolutionizing the way we interact with our analytics and manage data. This concept is known as ethical AI and aims to ensure that organizations use AI systems in a way that does not break the law.

Data Security: In the business intelligence ecosystem, we will see further advances in AI defense in the form of security. Already, we see continued development in proactive analytics that lend advanced BI neural networks that detect anomalies in the system before any problems occur.

Natural Language Processing (NLP): NLP bridges the gap between computers and humans by eliminating the need for any programming language. By integrating this capability with voice-activated digital assistants on mobile devices, software vendors are making data discovery much easier to use. It outputs the basic results of data visualization in conversational language, facilitating quick insight interpretation.

Analytics as a Service (AaaS): AaaS provides companies with end-to-end big data analytics, from data collection to cleaning, organizing, and processing large and disparate online data sets that fit business specifications. Meanwhile, more companies are expected to rely on the AaaS business model if its predecessor, Software as a Service, has any indication, as users only pay when they use the service.

Knowing the data: Data literacy is key to increasing user adoption and increasing the effectiveness of business intelligence tools. Data literacy is important to all individuals, regardless of their personal and business profile. Data driven business owners need to eliminate the data knowledge gap between data analysts and non-technical users.

Visual display of information: Data visualization allows companies to keep all relevant stakeholders engaged with data by enabling them to analyze and process information intuitively and extract actionable insights. It requires understanding the relationship between data in the form of data preparation and advanced guided analytics.

Real-time data and analytics: Accessing data in real time is becoming a norm in everyday life, not just for businesses. Moreover, the live dashboards application will help companies to have instant access to relevant information related to their business and to interact if any potential issues arise.

Data Quality Management: With so much information being produced every second, the use of quality data when performing analysis has become a critical component. Essentially, data quality management ensures that companies can make the right data-driven decisions using the right data for analytical purposes.

Data Monitoring: Data management ensures the quality of business assets through role-based access, authentication and auditing protocols. When data is accurate, unique, and up-to-date, users trust the reliability of the insights, which boosts revenue and reputation.

Data automation: No business intelligence topics would be complete without data automation (analysis). This new trend refers to the procedure in which companies automate as many processes as possible using multiple tools and technologies such as artificial intelligence, machine learning, low-code tools, no-code tools, and others.

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