Business intelligence vs data analytics: 10 key differences

In today's data-driven business landscape, we often hear terms like "business intelligence" and "data analytics." While we know both utilize data to extract insights, where do they differ?
    
In this blog, we'll explore business intelligence and data analytics, and their unique characteristics, purposes, and applications. Understanding the distinctions between these two will help businesses choose the right approach based on their needs. 

Here's how we divided the blog:

• What is business intelligence?
• What is data analytics?
• Comparing business intelligence and data analytics
• Which one for your business: BI or data analytics?

What is business intelligence?

Business intelligence (BI) is all about putting your data to efficient use, so that you can make data-driven decisions. BI empowers organizations to make better decisions based on data, rather than assumptions. 
    
It's the process of transforming complex datasets into visually appealing and easily understandable formats, such as reports, charts, and dashboards, enabling businesses to make informed decisions.

BI answers the questions "what" and "why," using both historical and current data. Here's a simple example:
    
Let's say you're an ecommerce company selling multiple fashion products globally. You want to track your company's monthly sales per month and the source of sales. You can create a report for monthly sales by simply connecting your ecommerce store with BI software. The report would look like this:

Monthly sales trend report

In the report above, you can see that there's a steep increase in your company's sales. This report answers the "what," as in "what's happening?" Sales are increasing. Now, you'll want to understand "why" your sales are increasing. 

• Have you tried a different marketing strategy?
• Or have you introduced a new product?

It could be either of these reasons. To find out? Again, BI can help. To get the answer, you can analyze the sales trend by source. Here's the report:

Monthly sales trend by source

Looks like your email campaigns have performed really well, and that's the reason for improved sales. 

BI acts as a bridge between raw data and actionable insights with the help of data integration, reporting, visualization, and analysis. 

Business intelligence allows businesses to:

• Monitor performance: With data visualization and analysis, businesses can monitor and track their performance against goals and benchmarks. Like the example above, you can track the monthly sales, orders, profit, or any metric you want to track.
• Identify trends and patterns: BI can help you identify trends and patterns in large datasets. With trends, businesses can extract insights that lead to a deeper understanding of their performance, customer behavior, and more. 
• Make informed decisions: With the help of comprehensive reports and intuitive visualizations, business owners and executives can make data-driven decisions. From the example above, you learned your email campaigns performed well, and you might want to focus more on them by optimizing them. 

In total, BI enables businesses to stay ahead by leveraging data to extract insights and make proactive decisions. Although BI excels in reporting, visualization, and descriptive analysis, it's still lacking in terms of predictive and prescriptive analysis. This is where data analytics comes into the picture, which we'll explore in the next section.    

What is data analytics?

Data analytics is the process used to extract insights and valuable information from data, with the help of statistical analysis, machine learning algorithms, and computational methods. 

Data analytics can be classified into four different types:

• Descriptive analytics: Summarizes and visualizes historical data to understand "what has happened." Focuses on past performance, trends, and patterns. 
• Diagnostic analytics: Helps to understand "why something happened." That is, identifying the root cause of trends and patterns.
• Predictive analytics: With historical data and statistical techniques, forecasting future outcomes and events. It answers the question, "what is likely going to happen."
• Prescriptive analytics: Offers the course of action that needs to be taken to achieve a goal. Answers "what should we do" and enables businesses to make informed decisions to achieve desired outcomes.

Now, let's see how data analytics helps an organization. We'll take the same ecommerce company example above.

With business intelligence, the company identified increased sales due to recent email campaigns. Now, with data analytics, we'll find the answer to "how." 

So how did your email campaigns perform well?

It could be because you've: 

• Personalized the email by segmenting the audience
• Included good offers, customer reviews, and testimonials

With data analytics, you can even forecast your future performance. Like in the image below, you can forecast your sales for the next three months. With this insight, you can stock up on inventory, or if your sales are going to drop, you can increase your marketing spending and efforts.

Comparing business intelligence and data analytics

When trying to understand the differences between business intelligence and data analytics, it's also important to know their key similarities. Here are some areas where BI and data analytics overlap:

• Data utilization: Both BI and data analytics utilize data to extract insights from data.
• Decision-making support: Both disciplines provide valuable insights that guide strategic and operational decisions within organizations.
• Drives data-driven culture: BI and data analytics emphasizes the importance of leveraging data to drive business success. 

Despite their similarities, BI and data analytics have some key distinctions. Here's a table that summarizes these differences:

Now that you understand the similarities and differences between BI and data analytics, it's time to choose the approach that will help you grow your business.

Which one for your business: BI or data analytics?

When deciding between business intelligence and data analytics, it's important to understand your business needs, objectives, resources, and skill considerations. 
    
If you primarily focus on monitoring and tracking performance and have well-structured standardized data, you can go with business intelligence. However, if you need advanced analysis, predictive modeling, and optimization for strategic decision-making, and handle huge volumes of unstructured data, you should choose data analytics.

But you need to remember that BI and data analytics are not mutually exclusive. In fact, many organizations adopt a hybrid approach, leveraging both BI and data analytics to meet their requirements.
    
You also might wonder whether you'll need a lot of time and money to take the hybrid approach. Well, the truth is you don't. There are highly rated data analytics software available for you to take the next step towards your data-driven journey.

Zoho Analytics: A modern self-service BI & data analytics platform

When you decide to take a hybrid approach, your next step will be choosing a modern self-service BI and analytics platform—like Zoho Analytics. With Zoho Analytics, you can import and blend data from 250+ data sources, create more than 50 visualizations, extract meaningful insights, and much more.

A powerful business intelligence software like Zoho Analytics offers a perfect blend of BI and data analytics, through which you can both track and monitor performance and forecast future performance. In addition, with the help of advanced technologies such as AI, ML, and NLP/G, you can get meaningful insights automatically, in the form of narratives, with Zia Insights. Here's an example:

Sign up with Zoho Analytics for a free 15-day trial and start your BI & analytics journey today.

You can also reach out to our analytics experts for a free personalized demo or send us your questions at support@zohoanalytics.com