Every day, businesses generate vast amounts of data. To make smarter decisions, identify problems, and increase profitability, they need tools to transform this data into actionable insights. Business intelligence (BI) and its subsets – business analytics (BA) and data analytics – are data management solutions that help understand historical and contemporary data to create insights. But what differentiates these solutions, and which one is right for your business needs? Although the terms are often used interchangeably, they have subtle distinctions. Let’s clarify these differences, starting with some basic definitions.
What is Business Intelligence?
Business intelligence is an infrastructure that aids in collecting, storing, and analyzing data from business operations. BI provides comprehensive business metrics in near real-time, supporting better decision-making. With BI, you can create performance benchmarks, spot market trends, increase compliance, and improve almost every aspect of your business.
What is Business Analytics?
A subset of BI, business analytics involves taking your company’s raw data and turning it into useful information. This includes identifying trends, predicting outcomes, and more. Common methodologies in business analytics include:
- Data Mining: Sorting through large amounts of data to identify patterns and trends.
- Aggregation: Gathering and organizing data prior to analysis.
- Forecasting: Analyzing historical data to estimate future outcomes.
- Predictive Modeling: Extracting information from datasets to identify patterns and estimate future trends.
- Data Visualization: Creating visual representations of data analysis, such as charts, tables, or graphs.
What is Data Analytics?
Data analytics is the technical process of mining, cleaning, transforming data, and building systems to manage data. Data analytics takes large quantities of data to find trends and solve problems. Unlike business analytics, data analytics is not confined to business applications and is used across various disciplines, from government to science.
Key Differences: Business Intelligence vs. Business Analytics
The main difference between business intelligence and business analytics lies in the questions they answer:
Business Intelligence
BI focuses on descriptive analytics, which provides a summary of historical and present data to show what has happened or what is currently happening. BI answers the questions “what” and “how,” enabling businesses to replicate successes and rectify failures.
Business Analytics
BA, on the other hand, prioritizes predictive analytics. This involves using data mining, modeling, and machine learning to determine the likelihood of future outcomes. BA answers the question “why,” helping businesses make educated predictions about what will happen and prepare accordingly.
Real-World Applications of BI and BA
Imagine you sell handmade stationery via an online store. Business intelligence could provide reports on past and current business states, such as sales spikes of recycled paper notebooks in Utah over the past three weeks. Based on this information, you decide to produce more recycled paper notebooks to meet demand.
Business analytics would ask, “Why did sales of recycled paper notebooks spike in Utah?” By mining website data, you might discover that a Salt Lake City sustainable lifestyle blogger recently posted about your notebooks, driving traffic and sales. This insight could lead you to send complimentary notebooks to other prominent bloggers in the sustainability space, anticipate future demand, and adjust your inventory accordingly.
Business Analytics vs. Data Analytics
The distinction between business analytics and data analytics is more subtle. Data analytics is a broad term for finding insights in data, whether in a spreadsheet, database, or app. It aims to uncover trends, identify anomalies, or measure performance. Data analysts might manage subscriber databases or calculate investment yields, often requiring additional mathematics or IT skills.
However, analytics focuses on operational insights. A business analyst deals less with technical analysis and more with practical applications of data insights, such as streamlining workflows or selecting the best vendors.
Applying BA and Data Analytics in Real Life
Returning to the stationery store example, a data analyst would examine how users interact with your website, identify traffic trends, analyze visitor demographics, and possibly develop a system to track customer navigation through different pages. A business analyst would use this data to make decisions about purchasing ads, creating new products, and updating your website.
Determining Your Business Intelligence and Analytics Needs
Instead of deciding between business intelligence or business analytics, it’s more beneficial to recognize that businesses need both – descriptive and predictive analytics – to thrive. When choosing technology, tools, and talent, focus on what you need the data system to accomplish and who will be using it. Developing a business intelligence strategy involves asking key questions like:
- Who are the key stakeholders? Who will use this system?
- Which departments need business intelligence, and what will be measured?
- What support do content authors and information consumers need?
By addressing these questions, you can implement a solution tailored to your business needs.