Introduction

Gold, stock market, oil, water are now old. Now it is all about data. Data is the most valuable commodity today and organizations are collecting data to improve their business, target customers, and to increase their revenue. The entire process of data gathering is established and there have been many companies that had started to collect data even before they were aware of how they were going to use it. They knew that the data was indispensable. Today, be it a big or a small firm, they extract data to get valuable insights for their business.

This is where come in the efforts of business intelligence and data science. Those who work in this field leverage the date. Data is increasing in velocity, volume, and complexity and there are new data sources created that need to integrate with the on-premise legacy. The data are both structured as well as unstructured and the analysis needs to be quick to make real-time decisions with the data by intaking and processing it fast.

This is a challenge that data scientists and business intelligence aim to tackle. They analyze together using tools to work seamlessly with the same set of data.

However, both the job profiles are not the same. To understand the differences in job responsibilities let us first understand what data science and business intelligence mean.

  1. Business Intelligence
  2. Data Science
  3. Difference Between Business Intelligence and Data Science

1. Business Intelligence

Business intelligence involves a set of techniques, applications, and processes that are used by companies and businesses to analyze business data. It is used to convert raw data into information that makes sense. The information is used to make business decisions and to take some profitable actions. Business intelligence skills deal with the analysis of structured as well as unstructured data which lets the business look at new and other profitable opportunities.

It helps the business to make decisions that are backed by facts rather than just assuming to make decisions. Business intelligence impacts business decisions directly. The business intelligence tools help to understand how a business can enter into a new market as well as to understand what their marketing efforts are.

2. Data Science

Here is the answer to what is data science definition. Data science is the field that uses data to extract knowledge and information using various kinds of scientific methods, processes, and algorithms. It uses various kinds of mathematical tools, statistics, algorithms, and machine learning techniques which are used to find various hidden patterns and get insights from the data. This helps to make decisions.

Data science also deals with structured and unstructured data. This is related to data mining as well as Big Data. Data science involves studying various historic trends and then drawing conclusions to redefine what is the present trend. They then use this information to predict what could be the future trend.

3. Difference Between Business Intelligence and Data Science

Now that we understand what data science and business intelligence are let us understand business intelligence vs data science. Knowing the difference between the two will help to select the correct solution. In simple terms, data science is the future and business intelligence is the present. Data science does a predictive analysis and perspective analysis. Business intelligence on the other hand deals with descriptive analysis. Let us delve into the detailed differences between the two.

A) The Kind of Analysis

Data science is about the probability of future conditions and events. The predictive analysis makes use of any historical data that is used to forecast the trend in business, customer behavior, and for the success of the product. Data science tries to answer the question about what could happen in the future. The perspective analysis in data science tries to find an answer to the solutions to any particular business problem.

Business intelligence sees what has already happened. It makes use of descriptive analysis to present the historical data to the business that makes it easy for them to understand and visualize the data. Business intelligence is used to generate reports that help to accurately and correctly communicate the present state of the business.

B) The Scope of Work

Data science is used to predict conditions and events and this is done with a special hypothesis or idea. Data science determines if the hypothesis is true or not. Then a predictive analysis is done on that particular hypothesis. After all data science is a science.

Business intelligence has a general scope. They develop a descriptive analysis that allows any of the business units to generate reports that they may need. The data could be used by a product manager to evaluate the latest project’s success. The data may be presented to the sales director who would want to study his quarterly result.

C) The Difference in Skillset    

Data science is the data scientist’s domain. Data science however cannot be done without reason. The data scientist needs to have some set skills but they need help with the operations, IT, finance, and business units.

Business intelligence is associated with business analysts and they have the necessary skill set for the same. The business users are the ones who benefit and need business intelligence the most. Business intelligence tools offer self-service capabilities. Without business intelligence business insights will not be available to the users of the business.

  • Business intelligence deals with the data analysis on the business platform but data science consist of many data operations in different domains.
  • Business intelligence analyses past data where data science uses past data to make future predictions.
  • Business intelligence handles structured and statistical data whereas data science uses structured as well as unstructured dynamic data.
  • Business intelligence stores data in a warehouse whereas in data science, data that is utilized is distributed in the cluster in real-time.
  • Business intelligence helps companies to solve their problems whereas data science curates as well as solves the questions.
  • Business intelligence makes use of tools like MS Excel, Microstrategy, Sisene, and SAS BI whereas data science makes use of Python, Spark, Hadoop, and TensorFlow.

Business intelligence and data science are recurring terminologies that are present in this digital era. Both of these make use of data but they are different from each other. Data science is like a big pool that contains a lot of information and business intelligence gives a bigger picture.  This is the difference between data science and business analytics.

Conclusion

Business intelligence vs data science has always been debated on but they have always had and will continue to have a great relationship. They both serve the same general role of offering data-driven and meaningful insight. Data Science looks forward to the future and business intelligence looks at history. This does not mean that one is better than the other. Business needs both historical data and future productions to perform well and to solve various problems.

If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional. 

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