How Data Analytics Differs from Business Intelligence
Data is big business, but only if you know how to use it properly. The past few years have seen software tools advancing to handle data, both to analyse past performance and determine future trends. The prevailing data collection tools are Business Intelligence (BI) and Data or Business Analytics (BA). Here’s a look at how the two differ.
What is Business Intelligence (BI)?
This is where the software analyses past data in order to help you make much more informed business decisions. BI is a broad term that encompasses Data Analytics as well as other reporting tools to make decisions based on historical data.
What is Data / Business Analytics?
Data Analytics software uses specific algorithms with predictive capabilities to determine the relationship between business data. It asks the right questions of the data which BI then translates into accessible language for business.
What are the differences between BI and Data Analytics?
Both technologies are impactful for business operations, both using data to extract insights that inform customer needs and boost productivity. But enough about the similarities of these two technologies – here’s what you need to know about how they differ, bringing their own set of data insights.
The size of your business will often determine whether BI or BA is best for you. BI tools, while once marketed for larger organisations, are actually great for smaller companies where the workforce doesn’t have a significant background in data science.
Age of the business
If your business is just starting out, then it’s likely you’re going to look at business analytics to give predictions of business trends rather than past performance. However, for established businesses looking to change things up, then BI might be more fitting.
BI uses a variety of tools for data analysis including data reporting, mapping analysis, real-time analysis, processing and dashboarding – among others. Data Analytics incorporates various phases within the analyses, such as predictive modelling, SWOT analysis, data modelling and requirement analysis – among others.
Level of sophistication
BI will provide a basic analysis of existing data, whereas Data Analytics takes the BI reports, processes the information, and then visually displays them in a more sophisticated manner. Data analytics requires more software application knowledge to carry out the required tasks.
Where BI uses data in one format, Data Analytics will transform existing data into different formats as a way to extract relevant information. Analytics provides solutions to challenges by enabling technology and converting raw data in a practical manner.
BI is generally used to improve the effectiveness of ongoing operations while Data Analytics seeks to change current operations to make the business more productive. It’s an important way of future-proofing your business – vital in this ever-changing economy.
BI is applied to structured data within an enterprise, such as ERP (enterprise resource planning) and financial software systems, thereby accessing data from supply chain and operations. With Data Analytics, both structured and semi-structured data can be transformed into meaningful data.
Age of data
BI uses both current and past data for insight whereas Data Analytics uses solely past data as a way to obtain insights that can be used to drive future business.
If you’re still not clear on whether Business Intelligence or Business Analytics software is right for your business, it’s best to consult industry experts, Canvas Intelligence. They provide superior business intelligence solutions that give you access to real-time visual data on mobile, PC or tablet, as well as ongoing support for all customers.
Pingback: What is the difference in reporting, insight analytics and intelligence? | Business IntelligenceAugust 27, 2021
Sorry, the comment form is closed at this time.