Business Intelligence (BI) or Data Analytics (DA) has long become a useful tool to support organizations and companies in the process of reading and understanding the simplest data to support increased sales.
In this article, we will guide you through the benefits of reading data in business for growth, but first, let’s clearly distinguish the two concepts mentioned above that many people often confuse.
What is BI – Business Intelligence?
Business Intelligence (BI) combines business analytics, data mining, data visualization, data infrastructure and tools, and best practices to help organizations make informed decisions. more data.
Business intelligence takes a holistic view of your organization’s data and uses that data to drive change, eliminate inefficiencies, and quickly adapt to changes. market or supply changes.
What is DA – Data Analytics?
In short, data analysis or data analysis involves the process of sifting through data and finding and gathering important information through a very large amount of information chaos.
Data Analytics (data analysis) is a part of data science (Data Science), a rather dry subject but very helpful for business growth.
Simply put, Data Analytics can be seen as a “subset” within BI. Many organizations use big data analytics solutions to understand existing problems in their day-to-day operations or make forecasts for the future.
And BI includes all the tools from collecting, converting, to analyzing data and displaying analysis results (turning results, forecasting models in analysis into easy-to-see reports and tables).
Data Analyst is a job that focuses on collecting, exploiting, and processing data sets to make observations, comments, and reports on a specific problem. This is a meaningful and important job for any organization or business.
If you want to become a Data Analyst in a company, you need to learn a lot of things to hone your skills. Currently, there are many Data Analytic training online courses that you can refer to, there are many promotions, discount codes, coupons for beginners.
Business Intelligence Benefits
Business Intelligence (BI) is used to capture and detect business problems in data thanks to:
- Business Intelligence learns on its own from data and proceeds to offer specific solutions for the business or business product.
- Business Intelligence helps managers check whether sales and marketing strategies, plans are working well or not
- Always monitor throughout the implementation process to timely make optimal decisions or suggestions from the data report.
Why Business Intelligence is important for businesses
Business intelligence can help companies make better decisions by displaying current and historical data in the context of their business. Analysts can leverage BI to provide performance and competitor benchmarks to help the organization run more smoothly and efficiently. Analysts can also easily spot market trends to increase sales or revenue. Used effectively, the right data can help with everything from compliance to recruitment efforts. So, what are you waiting for without buying yourself BI system software, with the benefits and importance that it brings to businesses will help a lot. You should use discount codes, coupons on holidays when buying software that will help you save some money.
Some of the ways business intelligence can help companies make smarter, data-driven decisions:
- Identify ways to increase profits
- Analyze customer behavior
- Compare data with competitors
- Performance tracking
- Operation Optimization
- Prediction success
- Spot Market Trends
- Discover problems or problems
Data analytics Benefits
Data Analytics gives us a detailed understanding of how companies collect data from the beginning and analyze it to get Insights – the inner values of the data:
- Data analytics helps us to collect customer data.
- Clean necessary data.
- Understanding and connecting customers.
- Data analytics helps to overcome the weaknesses of the business.
- Future business direction.
Key differences between Business Intelligence and Data Analytics
Many people will mistakenly think that Business Intelligence is the same as Data Analytics because both are about turning raw data into meaningful information. The question is: In what ways is Business Intelligence different from Data Analytics? So we need to distinguish between Business intelligence and Data analytics.
Purpose – Meaning
- Business intelligence is the analysis of information needed to increase efficiency for business decision making
- Data analytics is the process of transforming raw data into forms that can be understood by users
Function
- Business intelligence has the main purpose of assisting businesses in making decisions. From there, help develop the business organization
- The main purpose of data analytics is to model, clean, predict, and transform data according to the needs of the business.
Application
- Business intelligence can be applied using BI tools in the market. BI only uses past data stored in the data warehouse
- Data analytics can be applied to use by many different data storage tools on the market. Data analysis can also be done on BI tools, but it depends on the individual approach and strategy of each organization.
For organizational structure
- Business intelligence does not affect the current business model, but the main purpose is to help businesses achieve their goals, help users identify gaps in data management, and offer effective solutions. most fruitful.
- Data analytics helps businesses change their models, by analyzing past data, current data and predicting future trends
As you can see, modern BI tools are all equipped with options for data analysis and it is up to businesses to make the best choice based on their situation.
Conclusion
Above is an overview of Business Intelligence and Data Analytics, two powerful data processing system models that businesses are interested in applying to build a competitive advantage. Hopefully, through this article, you will be able to understand more about the nature and benefits of BI and DA in the business and distinguish them, thereby considering implementing your own similar models. Good luck!
