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Introduction to Business Intelligence and Analytics

07 Aug
Businessman using tablet for analyzing data in monitoring room with team.

Strategic decision-making is crucial for any organization seeking a competitive edge, and data is the driving force behind strategy. The demand for skilled professionals who can harness the power of data and transform it into actionable insights has never been greater.1

This article will drive home the importance of business intelligence (BI). We’ll look into business intelligence basics, explore data analytics techniques, and dive into various benefits and best practices.

What is business intelligence?

Put simply, BI combines technology, processes, and strategies to transform raw data into meaningful insights,1 helping individuals and organizations make informed decisions and drive business success.

BI is not to be confused with business analytics. Business intelligence takes a descriptive approach to give clear insight into how a business is performing. Business analytics, on the other hand, is a predictive effort to describe what an organization might do to achieve greater outcomes.

BI is a useful compass for organizations, as it can guide people through enormous amounts of data and help them achieve their business goals. It empowers business leaders, executives, and analysts to gather, analyze, and interpret data from sources across the enterprise for a comprehensive view of operations, customers, market trends, and more.

The Importance of BI: Improving Return on Investment

Business intelligence is a powerful tool with which organizations can improve their return on investment (ROI). Applying appropriate BI concepts increases ROI in three essential ways:1

1. Revealing Operational Inefficiencies and Opportunities for Enhancement

BI gives a comprehensive view of an organization’s business operations, allowing leaders to flag inefficiencies and possible areas for improvement. After thorough data analysis and review of performance metrics, professionals within each company can go on to streamline processes, optimize resource allocation, reduce operational costs, and more. When used effectively, business intelligence can help people eliminate workflow bottlenecks, enhance productivity, and maximize efficiency.

2. Uncovering Valuable Customer Insights

The customer is king! The importance of understanding customer preferences and behavior in today's competitive market can't be overstated. BI tools analyze information such as customer data, purchase history, and interactions to reveal valuable insights.

A customer's purchasing history, for example, holds a wealth of knowledge. By studying past transactions, business analysts can gain a better understanding of what products or services resonate with their customers the most. This knowledge enables businesses to optimize their product offerings, fine-tune marketing strategies, and even develop personalized recommendations for each customer, leading to increased customer satisfaction and loyalty.

Similarly, information gathered from customer interactions with a company is crucial. It allows companies to assess the quality of customer service, identify pain points, and uncover opportunities for improvement. Understanding how customers engage with a company's products or services helps businesses to better meet customer needs, ensuring a positive and seamless customer experience.

3. Identifying Needs for New Products or Services

BI insights can spark new ideas. When analyzing market trends and consumer demand, business analysts and their colleagues often identify gaps in the market and opportunities for new products or services. Using BI, they can confidently develop offerings that align with customer needs, ensuring a greater chance of success. The ability to innovate and offer products or services that cater to specific market demands is a valuable means toward boosting revenue and contributing significantly to ROI.

The Relationship Between Artificial Intelligence and Business Intelligence

Artificial intelligence (AI) enhances BI best practices on multiple fronts. AI is a broad category encompassing technologies that mimic human intelligence. It includes machine learning–a common AI application used in BI2natural language processing, predictive analytics, and more.

Through machine learning capabilities, AI continuously refines data analysis to make BI outputs more accurate and efficient over time. Natural language processing offers user-friendly interactions with BI platforms, making data insights accessible to a wider audience within an enterprise. Predictive analytics enable BI systems to forecast trends, risks, and opportunities to improve strategic decision-making.

The marriage of AI and BI enables business leaders to make informed decisions, optimize operations, and stay ahead in an increasingly competitive landscape.

What do business intelligence analysts do?

Business intelligence analysts play a pivotal role in the data analysis process, driving everyday efforts that uncover valuable insights for organizations.3 By collaborating closely with executives and business users, analysts identify the specific data needed to address crucial questions and challenges.

They meticulously gather and consolidate data from various sources and use their expertise to create impactful data visualizations, comprehensive reports, and interactive dashboards. This enables other members of the organization to derive meaning and actionable insights from data sets. Business intelligence analysts empower their organizations to make informed decisions, discover opportunities, and navigate the complexities of today's data-driven landscape.

Data Analysis Techniques

Data analysis can take a variety of forms. Practices such as the following enable organizations to identify patterns, take advantage of opportunities, and solve challenges.

Descriptive Analysis

Descriptive analysis involves summarizing and presenting data in a meaningful way to provide a clear picture of past events or trends, enabling easy understanding of key patterns and insights.

Exploratory Analysis

This technique uncovers patterns or relationships in data through visualizations and initial investigation. The data is often used to generate hypotheses to be used in further analysis.

Diagnostic Analysis

Diagnostic analysis focuses on understanding the root causes behind specific outcomes or events by analyzing historical data. This helps organizations pinpoint reasons for successes or failures.

Predictive Analysis

By analyzing historical data and applying statistical algorithms, predictive analysis forecasts future trends and outcomes, assisting in proactive decision-making.

Prescriptive Analysis

This technique goes beyond predictive analysis, recommending specific actions or strategies to optimize future outcomes and drive business success.

Quantitative and Qualitative Analysis

Quantitative analysis involves using numerical data to identify patterns and uncover trends, while qualitative analysis involves interpreting non-numeric data, such as text or images, for deeper insights.

Statistical Analysis

Statistical analysis employs various statistical approaches to analyze data and draw meaningful conclusions. This technique helps organizations make data-driven decisions based on empirical evidence.

Benefits of Business Intelligence

The benefits of business intelligence are far-reaching; BI revolutionizes how organizations operate in the modern business landscape.4

Savvy use of many business intelligence tools empowers business leaders to make faster, more accurate decisions, ensuring improved productivity and streamlined operations. Business intelligence enables them to enhance customer service through a deeper understanding of customer behavior and preferences, leading to higher satisfaction and loyalty. With fast and accurate reporting, businesses gain a competitive advantage by staying agile and responsive to market changes. Moreover, BI eliminates guesswork, providing actionable intelligence that uncovers new opportunities and market trends.

Overall, the adoption of BI sets the stage for growth, innovation, and success in an increasingly data-centric world.

Conquer data-driven decision-making.

Learn to navigate a data-driven world with confidence. Santa Clara University’s Online Master of Science in Business Analytics (MSBA) program builds the expertise you need for the career you want. Whether you’re a seasoned professional looking to acquire new skills or an aspiring business leader seeking a strong career start, the Online MSBA curriculum will empower you to analyze complex data sets, quickly identify trends and opportunities, make informed decisions, and improve performance.

Learn more about the Leavey School of Business: the expert faculty, networking opportunities, and admissions process. Schedule a call with an admissions outreach advisor today.