AI and Machine Learning Fuel Current Business Analytics Trends
Data now drives the business world, a shift that has made business analytics necessary for organizational leaders seeking to stay competitive and make informed decisions. Whether it’s predicting market trends, optimizing operations, or improving customer experiences, interpreting and analyzing data is a skill in high demand across all industries.
Professionals with business analytics expertise find data insights that lead to better strategic decisions. The field offers a dynamic and exciting career path for those considering a degree in business analytics. Part of working in this field is understanding the latest business analytics trends, especially those involving artificial intelligence (AI) and machine learning.
AI is making business analytics an increasingly essential component of business intelligence, a fast-growing space in the business world. The business intelligence market is expected to reach nearly $64 billion by 2032. This growth has led to more business analytics-related jobs. For example, the federal government anticipates an 11% increase in the number of management analysts alone.
Some of the Biggest Business Analytics Trends
Business analytics constantly evolves as new technologies, tools, and methodologies emerge to help organizations make data-driven decisions. While business analytics trends can change frequently, they typically involve AI and machine learning.
AI and machine learning are increasingly integrated into business analytics to automate processes. They can also enhance predictive capabilities and improve decision-making. AI’s speed and accuracy allow businesses to analyze large datasets, uncover patterns, and make predictions in ways that were not possible before.
Companies employ AI for tasks such as customer segmentation, demand forecasting, fraud detection, and supply chain optimization. AI impacts every trend in business analytics.
Using AI For Augmented Analytics
Augmented analytics simplifies analyzing complex data, enabling business users without deep technical expertise to derive meaningful insights. AI and machine learning handle data preparation, generate insights, and provide data visualization. This democratization of data allows more employees to participate in data-driven decision-making. It’s considered a “self-service” area of business intelligence that can speed up the data analysis and decision-making processes.
Augmented analytics also supports better data visualization and storytelling, which has become more critical with the increasing volume of data. AI-driven tools make creating interactive dashboards and visualizations that can be shared across teams easier.
Real-Time Analytics With AI
As businesses move faster, real-time analytics is becoming more crucial. Companies now require up-to-the-minute data insights to respond to changes in the market, customer behavior, or operational performance. Real-time analytics uses streaming data from sources like Internet of Things (IoT) devices, social media, and transactional systems to provide insights as events happen, enabling businesses to act proactively rather than reactively.
Business analysts work toward better real-time analytics and seek to improve predictive analytics that forecast future trends based on historical data. They also focus on prescriptive analytics, which recommends the best actions based on the predictions. This shift towards real-time and forward-looking analytics helps companies anticipate challenges and opportunities.
Improving Data Privacy, Security and Quality
As data becomes more valuable, it’s also becoming more heavily regulated. Data privacy and security are a top priority in business analytics. Companies must ensure that their analytics processes comply with legal requirements and protect sensitive data. This trend reflects the rise of privacy-preserving analytics techniques like differential privacy, which allows businesses to gain insights from data while minimizing the risk of exposing individual information.
While maintaining data security, companies must also focus on its quality, which requires strong data governance and quality management. Poor data quality can lead to incorrect insights and flawed decision-making. As a result, businesses invest in robust data governance frameworks to ensure that data is accurate, consistent, and accessible. Effective data management practices, including data lineage tracking and master data management, are becoming standard.
Natural Language Processing (NLP)
NLP is gaining traction in business analytics as companies strive to make data more accessible and actionable. By enabling AI-driven systems to understand and interpret human language, NLP allows users to interact with data using natural language queries rather than complex coding or formulas. This trend is another way analytics tools are becoming more user-friendly and helping non-technical users extract valuable insights from large datasets.
Customer-Centric Analytics
As customer experience becomes a key differentiator, businesses use analytics to gain deeper insights into customer behavior, preferences, and sentiment. Customer-centric analytics focuses on understanding the full customer journey, enabling companies to deliver personalized experiences and improve customer retention. Combining data from various touch points — including social media, e-commerce platforms, and CRM systems — allows businesses to better understand customers’ needs.
The MS in Business Analytics From Touro University Worldwide
Touro University Worldwide offers an online Master of Science in Business Analytics program that gives graduates expertise in applying business analytics to provide value to their organizations. They learn from professors who are practitioner-scholars and understand the practical application of theory in real-world situations.
Students in the program choose between a management concentration or a marketing concentration. Graduates emerge with the skills needed for many business analytics careers, including:
- Business Analytics Manager
- Data Science Manager
- Operations Analyst Manager
- Marketing Analytics Manager
- Financial Analytics Manager
- Supply Chain Analytics Manager
- Customer Insights Analyst/Manager
- Brand Analyst/Manager
- Market Research Analyst/Manager
Business analytics is undergoing a transformative period driven by technological advancements, increasing data volumes, and the growing demand for data-driven decision-making. As AI and machine learning become integral parts of the field, businesses must stay agile and continuously adapt to trends to remain competitive. Professionals with expertise in these areas are highly valued in the job market.
