Blog > Which is better? Business intelligence or Data Analytics?
Which is better? Business intelligence or Data Analytics?
December 28th, 2022
Data driven industries often throw around the words Business Intelligence and Data Analytics, but as someone new to the industry do you truly know the difference between these terms? In today’s Blog we’re going to work out the differences between the two and once and for all settle the debate as to which is better - Business Intelligence or Data Science?
Starting with what is BI?
What is Business Intelligence?
To explain this simply, we can split the definition of Business Intelligence into 2 parts:
- The processes, tools, technologies used to gain valuable business insights from large amounts from raw data.
- The output of the process - the business insights themselves. Going forward let’s keep both the processes and the outcomes in mind when we talk about Business Intelligence.
When we talk about processes, we’re referring to the conversion of raw data into meaningful business insights. These are the techniques in order to achieve that:
- Real-time monitoring
- Dashboard development and reporting
- Implementation BI software, like Power BI
- Performance management
- Data and Text mining
How does Business Intelligence work?
We all know that in simple terms BI takes raw data and converts it into meaningful information, but how exactly is that achieved? Let’s take the above mentioned processes and explore them a little more.
- Real-time monitoring - It is the process of collecting and storing performance metrics (the set parameters tell you how well your campaign is doing) as and when it crosses your network.
- Dashboard development and reporting - A Dashboard portrays your data in the form of graphs, charts, etc. All your data is presented together visually, making it easy for you to catch-up faster.
- Benchmarking - It is the process of comparing the metrics you collected with the numbers present in the industry.
- Implementation of BI software - Softwares and tools like Power BI, SQL etc, will help you collect, clean and present data in the form of powerful visuals.
- Performance Management - The process of ensuring that certain goals at the start of a campaign are met.
- Data and Text Mining - It is the process of discovering patterns and information from large data sets. It makes use of machine learning, statistical analysis and more.
Examples of Business Intelligence
So where is Business Intelligence used? (Just about everywhere
BI can help you build a dashboard that shows you all customer interactions across all platforms. This can help you get a complete picture of the service you’re providing without having to manually go through every platform.
Business Intelligence can help you effectively track website traffic.
What is Data Analytics?
Data Analytics is a process of collecting, cleaning, inspecting, transforming, storing and modelling. In truth you can say that Data Analytics is a tool used in Business Intelligence to make informed decisions, however Data Analytics is used in many many more fields to find valuable insights. Other than Businesses, Data Analytics is used by:
- The Medical Industry
- The Government
- The Education System
So what is the difference between Data Analytics and Business Intelligence? Let’s find out!
The differences between Business Intelligence and Data Analytics
To further elaborate on the broad differences between BI and Data Analytics, we have put together a list of different concepts or techniques the two use.
Using insights vs. creating insights
- BI uses insights to make informed decisions.
- Data Analytics, uses various analytical tools and techniques to to find these insights in the first place
Backward-looking vs. Forward-looking
- Business Intelligence mainly focuses on looking at historical data to discover trends and make better decisions.
- Data Analysis on the other hand, uses historical data to discover patterns and trends that can be used for forecasting or Predictive Analysis.
Structured vs. Unstructured data
- Business Intelligence makes use of structured data, collected from data warehouses.
- Data Analytics on the other hand, starts off with the process of cleaning, sorting and storing unstructured data.
Non-technical users vs. Technical users
- BI is used primarily by non-technical users like Business heads, Finance heads or CEO’s etc.
- Data Analytics is used by Data Scientists, computer programmers etc.
Clean vs Slightly Messy
- BI makes use of highly organised dashboards and reports to derive insights.
- Data Analytics involves data mining, making of algorithms, data modelling and more.
Curious about a career in Data Analytics?
If you’re curious about a career in Data Analytics, upGrad Campus has got the perfect stepping stone that can help you cross over to the world of Data Analytics! Check out our Data Science and Analytics course. With our course you’ll get hands-on experience with Python, Kaggle, SQL, Excel and Tableau. If you want to know more about our course you can head over to our website and get in touch with our learning consultants for a free career consultation!
To sum this entire article up, remember this - Business Intelligence and Analytics are used to help businesses - Data Analytics on its own is used by all industries and does not use business intelligence. The terms are often used interchangeably because some of the techniques used overlap. But the key difference is the purpose these two analytical methods are used and which industry they’re being used by.
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