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Business Intelligence and Analytics: What’s the Difference?

In today’s data-driven business landscape, organizations need to rise to the challenge of effectively harnessing their data. Two related disciplines — business intelligence and business analytics — have emerged as the primary practices for extracting and applying insights from big data. While it’s common to hear the terms used interchangeably, business intelligence and business analytics are distinct practice areas with separate goals, tools, and practitioners.

Let’s look at the key differences between business intelligence and analytics, and why leading enterprises are investing in the tools and talent necessary to practice both effectively.

What Is Business Intelligence?

Business intelligence is an umbrella term for the processes, tools, and technologies used to gather, analyze, and present data to support business decision-making. The data that companies collect and generate on a day-to-day basis is stored in disparate source systems and formats, so it involves extracting historical data from those various sources and transforming it into a consistent format, enabling organizations to extract strategic and actionable insights that would have otherwise been unobtainable.

Key characteristics of business intelligence include:

  • Historical focus: it primarily deals with historical data to understand past trends and performance.
  • Reporting and visualization: its tools often generate static reports, dashboards, and visualizations for easier consumption.
  • Key performance indicators (KPIs): it emphasizes monitoring and measuring predefined KPIs to assess performance against goals.

So, what does business intelligence look like in practice? A healthcare organization, for example, might use it on several fronts: enhancing patient care, optimizing operational efficiencies, and improving financial performance.

On the patient care side, the organization can use business intelligence tools to amass and analyze patient data (such as electronic health records and lab results) to generate insights into treatment effectiveness, patient outcomes, and population health trends. Business intelligence for healthcare operations, on the other hand, would look at resource allocation, staffing, and facility utilization data to improve efficiency and streamline operations.

Business intelligence tools span data integration, data management, analytics, and reporting. However, the specific set of tools a company uses varies depending on its unique business needs, data sources, and technical requirements.

What Is Business Analytics?

Business analytics takes traditional data analytics and focuses it to a business context. It uses data analysis to solve business problems, drive strategic planning, and streamline operational improvements. To address business-related challenges and drive informed decision-making within organizations, it uses a range of techniques — including descriptive, diagnostic, predictive, and prescriptive analytics.

The ultimate goal of business analytics is to understand why certain events occurred and to predict future outcomes based on historical data patterns.

Key characteristics of business analytics include:

  • Forward-looking focus: it explores historical data to predict future trends and make informed decisions.
  • Data exploration and discovery: it involves in-depth exploration and discovery of data to identify patterns, correlations, and hidden insights that can drive business strategy.
  • Loading...Advanced analytics techniques: practitioners use techniques such as data mining, Loading...machine learning, and predictive modeling to uncover patterns and make predictions.

Consider how business analytics comes into play for a technology company whose primary product is an app with a large user base. The company can optimize their business analytics and uncover new insights into user engagement and retention metrics. This enables developers to identify areas for improvement in the app’s features, user experience, and algorithm, as well as new data monetization opportunities.

Business analytics tools, such as an analytics database, optimize data analysis, visualization, and decision-making. These applications enable users to perform statistical analyses, visualize data through charts and graphs, and use advanced analytics techniques such as predictive modeling and machine learning. As with business intelligence, the range of tools a company selects will of course be tailored to its individual requirements, goals, and technology.

What’s the Difference Between Business Intelligence and Analytics?

In the simplest of terms, business intelligence is focused on the present day, while business analytics looks to the future. Business intelligence concentrates on reporting and visualizing historical and current data to provide a comprehensive view of current business operations. Business analytics goes beyond that by using advanced analytical techniques to make predictions and optimize decision-making. Other key differentiators include:

Descriptive vs. Predictive

Business intelligence is descriptive: It focuses on describing past trends and performance by answering questions like “What happened?” and “Why did it happen?”

Business analytics are predictive analytics: It uses statistical modeling, forecasting, and optimization techniques to predict future outcomes, answering the question “What will happen?”

Reporting vs. Applying

Because business intelligence is primarily descriptive, it centers around reporting on existing data, providing stakeholders with a clear overview of past and current performance as measured by KPIs. Conversely, business analytics involves deeper statistical analysis to uncover underlying patterns and insights. Leaders apply these insights as they develop new business strategies and plans.

Structured vs. Unstructured Data

Business intelligence primarily relies on structured data, which is organized and formatted in a predefined way – usually in a structured database or spreadsheet. However, business analytics tools, like Exasol’s database, also have the capacity to analyze unstructured and semi-structured data, which have less rigid formats and organization properties. Examples include text documents, videos, and social media posts.

Managers vs. Analysts

Though the two disciplines are closely related, business intelligence and business analytics require separate skill sets. Business intelligence is primarily practiced by managers who are accountable for KPI tracking and decision-making. Analysts work in the realm of business analytics and focus on answering questions and creating reports to support managers in the decision-making process.

Get the Best of Business Intelligence and Analytics with Exasol

The bottom line: Business intelligence and business analytics are foundational components of modern business strategy. Together, these disciplines enable you to make data-backed decisions, enhance operational efficiency, improve strategic planning — and ultimately achieve your goals.

Exasol offers a high-performance analytics database that supports both practices. The speed of its query performance and the flexibility of choice it offers for deployment, coupled with its powerful predictive and advanced analytics features, make Exasol the best choice for organizations looking to use their data more effectively and turn their business intelligence into better insights.

Start your free trial today.