What is Business Intelligence (BI)?

Business Intelligence (BI) involves strategies and technology. Businesses use BI for data analysis. It helps manage crucial business information. This data informs key business strategies and operations. Common BI functions include reporting, analytics, and dashboard creation. BI also covers data mining and predictive analytics. These tools process large amounts of data effectively. This data can be structured or unstructured.

How BI Creates Strategic Value

Organizations use BI to find new strategic opportunities. BI helps make big data easy to understand. Finding new opportunities is crucial for growth. Effective strategies based on these insights give businesses a competitive edge. BI supports long-term stability and informs strategic decisions. It ranges from daily operations to high-level strategy planning.

Applications of Business Intelligence

Enterprises use BI to support many business decisions. Operational decisions cover things like product positioning or pricing. Strategic decisions set broad company goals and direction. BI works best when it combines internal and external data. External data comes from the market environment. Internal data includes financial and operational records. Combining this data creates true ‘intelligence.’ This comprehensive view is impossible using only one data source. BI tools help organizations understand new markets. They assess product demand. They also accurately measure marketing campaign effectiveness.

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BI History and Evolution

The term “business intelligence” first appeared in 1865. Richard Millar Devens used it then. He described how banker Sir Henry Furnese profited from fast information. Furnese acted quickly on news before his competitors. Devens argued that collecting and acting on information is central to BI. Later, in 1958, IBM’s Hans Peter Luhn used the term. He defined intelligence as “the ability to apprehend the interrelationships of presented facts.”

In 1989, Howard Dresner proposed a broader definition. He called BI an umbrella term. It described methods that improve decisions using fact-based support systems. This modern usage became widespread in the late 1990s. Today, BI uses methodologies, processes, and technologies. They turn raw data into useful information. This enables effective strategic and operational decisions.

BI vs. Related Fields

People often confuse Business Intelligence and Competitive Intelligence. BI primarily analyzes internal, structured data. Competitive Intelligence focuses on competitors and external data. Competitive Intelligence is typically a subset of BI. Some also confuse BI and Business Analytics (BA). Thomas Davenport separates these terms. He says BI includes querying, reporting, and Online Analytical Processing (OLAP). BA is the subset focusing on statistics, prediction, and optimization.

Dealing with Unstructured Data

Business operations create huge amounts of unstructured data. This includes emails, chats, and presentations. More than 85% of all business information exists this way. Managing semi-structured data remains a key challenge. Organizations must accommodate this data when designing BI solutions. We need metadata to improve data searchability. Metadata adds context, such as author or topic summary. Technologies like automatic categorization help generate this metadata.

Generative BI

Generative BI uses generative AI techniques. Large language models are key here. This approach makes data analysis easier for everyone. Users interact with data using natural language queries. This helps generate actionable insights quickly. For example, Microsoft integrated Copilot into Power BI.

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Reference: Inspired by content from https://en.wikipedia.com/wiki/Business_intelligence.