The landscape of analytics and business intelligence is in a constant state of evolution, driven by technological advancements. Organizations stand to benefit greatly from these trends by automating operations, optimizing processes, and identifying areas for growth. The analysis of data enables enhanced workflow, bottleneck identification, and more strategic resource allocation, ultimately boosting productivity and efficiency. According to Gartner’s projection in June 2020, by the close of 2024, approximately 75% of organizations will transition from AI piloting to operationalizing AI, leading to a substantial upsurge in streaming data and analytics infrastructures. Here are the top ten trends to watch for in analytics and business intelligence for 2024:
- Enhanced Data Discovery: Cutting-edge technologies like machine learning and natural language processing (NLP) will simplify and enhance data discovery, enabling organizations to uncover valuable insights and hidden trends.
- AI-Powered Analytics: Artificial intelligence (AI) will continue to revolutionize data gathering, analysis, and utilization, with AI-driven analytics solutions becoming more sophisticated and accessible, facilitating quicker and smarter decision-making.
- Collaborative BI: Organizations will move away from siloed data environments, embracing collaborative business intelligence tools that allow employees across the company to collaborate on data, leading to improved decision-making.
- Data Literacy Training: In a data-driven world, businesses will invest in data literacy training programs to equip their workforce with the skills needed to gather, analyze, and leverage data effectively.
- Data Automation Expansion: Automation of data-related tasks will become more widespread, enabling employees to focus on strategic work while automating processes like data collection, cleaning, and analysis.
- Heightened Data Security: With data’s increasing value, organizations will intensify their efforts and investments in data security to safeguard against unauthorized access.
- Predictive and Prescriptive Analytics: To gain a competitive edge, businesses will rely more on predictive and prescriptive analytics, which offer insights and recommendations for improving business outcomes.
- Expanded Embedded Analytics: As organizations seek to provide greater access to data for their employees, embedded analytics will proliferate, making it easier for employers to access and utilize data within their business systems.
- Natural Language Processing Integration: Analytics and business intelligence applications will increasingly incorporate natural language processing (NLP), enabling insights to be extracted from a wider range of data sources, including unstructured text and speech data.
- Widespread Data Automation: Companies will continue to adopt data automation solutions, enabling efficiency gains by automating processes such as data collection, cleaning, and analysis.