Data Science and Business intelligence are popular terms in every business domain these days. Though both have data as the fundamental aspect, their uses, and operations vary. For an organization, it is essential to know the difference between business intelligence and data science to make fair use of both and ensure significant growth.
Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data.
Business Intelligence vs Data Science Table
Candidates planning to pursue a career in the analytics domain should know about these roles in detail. Many people make a choice by skimping on the research part only to face disappointments in the future. So, before you choose a field, it is essential to go for Business Intelligence and Visualization online certification and learn to turn data into opportunities with BI and visualization.
The analytics domain gets classified into three categories, with data analytics being the broader term. However, instead of comparing business intelligence v/s data analytics v/s data science, knowing the difference between business intelligence and data science would be enough.
Let us compare business intelligence and data science on the basis of the functions, tools, and other factors. The business intelligence v/s data science table below will give you a better idea of which field it is about what.
Parameters
| Data Science
| Business Intelligence
|
|---|
Purpose
| It is a field in which professionals use different tools to gather and sort data to fetch meaningful information from it.
| It is a set of tools and technologies that help enterprises with excellent business data analysis.
|
Data Usage
| It stores the data in a sorted manner for future use.
| It uses data from the past and present to make decisions related to future growth.
|
Data Type
| Data science deals with both structured and unstructured data.
| Business Intelligence only deals with structured data.
|
Flexibility
| It is much more flexible because the data sources can be added according to the needs.
| It is not as flexible as BI data sources always have to be pre-planned.
|
Complexity
| Data Science is a complex operation, as large volumes of raw data have to get sorted. It becomes more complex because the data keeps adding on a large scale.
| It is simpler than data science, as BI analysts only deal with sorted data forms.
|
Technologies Used
| Technologies like Hadoop are available for effective data science operations, and many other tools and techniques are rapidly launching in the market.
| The popular tools for BI analysis are Klipfolio, Spotfire, and Cyfe, and the list is never-ending.
|
Business Intelligence vs Data Science
The table above gives a fair understanding of business intelligence and data science difference. Let us dig deeper and discuss different parameters on which these two fields are different from one other.
Business Intelligence v/s Data Science: Perspective
When you ask what is the difference between business intelligence and data science? The first thing you will notice is the perspective. Data Science emphasizes the future and forecasts the possible scenarios in business that might occur. On the other hand, Business Intelligence has a responsive course of action. The professionals in this domain use historical data to study what has happened in the past. Moving further, they use it to plan growth strategies.
Business Intelligence v/s Data Science: Data Types
Another parameter in business intelligence versus data science comparison is the data type. Data science professionals deal with structured and unstructured data. This field is primarily related to sorting the raw, unstructured data into a sorted and structured format. Business intelligence deals with deals only with structured data. The BI analysts only use the sorted data sets to study patterns that can help make significant business decisions.
Business Intelligence v/s Data Science: Process
The process that each domain follows is different from that of others. Business intelligence uses the descriptive analytics format to set the stage for future predictions. The BI analysts study the data patterns thoroughly to understand the ways in which their business performed previously. In the last step, they use this information to launch new products or plan upgrades in the existing system. For example, they wouldn’t run a sale or launch a product merely on the basis of guesswork! They would analyze consumer behavior and data patterns to make fool-proof decisions.
Data scientists use Exploratory methods. Before making the data available for business analysis, it studies it through hypothesis testing or other exploration trends. Data scientists focus on finding a solution to an already existing problem, but their work scope keeps evolving as they proceed in their investigations.
Business Intelligence v/s Data Science: Deliverables
Another answer you get when you ask what is the difference between data science and business intelligence is their deliverables. Business Intelligence is all about generating all kinds of reports. The professionals working in this domain focus on building elaborate dashboards that explain the trends and patterns of different data sets.
Data science also provides sorted reports of data patterns, but their focus is on long-term and forward-looking projects. Unlike business intelligence, data science doesn’t use visualization tools to generate reports or final documents.
Business Intelligence v/s Data Science: Process Complexity
Data science acquires a broader picture and has large data sets in raw format to manage. Thus, it uses advanced tools and techniques to create predictive models that help give error-free deliverables. All of this requires much more precision, and that is what makes data science a complex process.
On the other hand, Business intelligence is not very complex. This domain is limited to the business domain. It emphasizes building dashboards and creating business insights that can help businesses grow. These tasks require precision and expertise but are not as complex as data science.
Business Intelligence v/s Data Science: Salary
The comparison is incomplete if we do not consider business intelligence v/s data science salary. Though both fields are promising and have excellent monetary perks, the data scientist makes a little more money.
Business Intelligence analysts can start from around $ 45000. With time, the salary can go up to $ 1,40,000. Hence, the average salary of a BI analyst is $ 87000.
Data scientists can start from around $ 66000. With time, the salary can go up to $ 134000. Hence, the average salary of a BI analyst is $ 96, 100.
Business Intelligence v/s Data Science: Skill Requirement
You will know there is a difference between these job roles as you compare data science v/s data analytics v/s business intelligence. Hence, the skills required for each domain would also be different.
To work in the Business Intelligence domain, one must be:
- highly proficient in SQL data extraction
- good at communication and presenting themselves in front of others
- well-versed with data analysis skills to make fruitful business decisions.
- aware of the ETL (extract, transform, load) tools that are helpful during the process.
Apart from these skills, a BI analyst should have excellent problem-solving skills, and their predictive instincts should also be good.
To work in the Data Science domain, one must be:
- highly proficient in SQL and NoSQL
- well versed in machine learning algorithm knowledge
- comfortable with using big data tools, such as Hadoop and Spark
- able to work comfortably with structured and non-structured data
- skilled enough to perform complex statistical data analysis.
Apart from these fundamental skills, data scientists should have a fair understanding of Python, R, SAS, and other latest technologies.
How Business Intelligence and Data Science are Similar?
After checking details about Business Intelligence vs Data Science, you may still wonder if there are any similarities. However, if you wonder, is business intelligence part of data science? The answer would be NO. The most significant similarity between business intelligence and data science is data! Both these domains use data in their operations, but how they use it and what tools they use to manage data is entirely different.
The second similarity between business intelligence and data science is their intent. Both domains provide data-driven information and tell the experts about patterns or trends seen in their business. Using this information, the businesses frame or upgrade their strategies and ensure exponential growth. Thus, the second similarity between the two domains is their focus on organizational success.
What Should You Choose Between Business Intelligence and Data Science?
Both business intelligence and data science are promising fields with high demand and excellent salary packages. However, you would have to consider your interest and skill set to decide which field would be apt. So, while making this decision, keep in mind the following factors:
- The interest and inclination you have towards each field.
- Your educational qualifications comply with which of the two?
- Do you have a specialization in any of these two fields?
- Are you well-versed with the latest tools and techniques of the field you plan to choose?
Basically, you can choose the domain based on your interests and expertise. Choosing something with no idea of what you will be expected to do is a decision that is only going to end up in disappointment. So, make well-researched and calculated decision and rest assured that you will enjoy a fruitful career ahead. Once you have decided which field to join, you can choose a data science and business intelligence course to brush up your skills and make the most of your professional career.
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Conclusion
Business Intelligence and data science are the two significant domains of analytics that are crucial for every organization. The demand for both is high, and the salary packages that experts in these domains get are also promising. Thus, it is a fruitful decision to choose any of these fields as per your interest and explore the career opportunities in them. Detailed information about business intelligence or data science can help you with decision-making. Once you have decided on the field, you must find your way to excel in it. Drive business decisions and get ready to land the most in-demand data jobs by going for KnowledgeHut Business Intelligence and Visualization online certification courses.
