Even though both use data, Business Intelligence and Data Science are not the same, although they are sometimes used as synonyms. In addition to their definition, they also differ in aspects such as type of data used, type of data required, and approach. For this reason, we will discuss the differences between one concept and the other.
First, it is essential to mention what Business Intelligence (BI) is all about. Through analysis, it aims to provide a clear understanding of an organization’s current and historical data; it involves processes and methods to analyze data or answer specific business questions, providing a complete picture of business information. Thus, it gives the necessary guidance for informed decision-making, considering areas for improvement. It even enables various users to visualize and understand business information quickly. All this leads to greater organizational efficiency and profitability.
On the other hand, Data Science is understood as an analysis of data derived from insights that allow companies to make informed decisions. It is a guide through which companies can predict, prepare and optimize their operations.
“Business Intelligence and Data Science are practices that complement each other.”
The truth is that both practices produce practical information for organizations, but rather than being the same thing, they are practices that complement each other. Here are some of their differences:
Approach
BI is retrospective and focuses on obtaining a course of action for the present with the help of historical data. It is based on current reports, trends, and KPIs. In contrast, Data Science focuses on predicting what might happen in the future based on patterns to establish business forecasting correlations.
Data used
Since BI is based on historical data, the data it uses must be precise and totally objective. This data is already structured at the time BI uses it. In addition, with BI, companies need to plan and prepare adequately, so combining sources and data provides the information they are looking for.
Data Science deals with probability and performs predictive and prescriptive analytics. Data Science creates data on the fly using the sources at hand to obtain information from data. Although they use structured data, they tend to work more with unstructured or semi-structured data, so they must spend more time cleaning the data.
Process
The planning time required for Business Intelligence is long, as it is a descriptive and statistical process that must be planned weekly, biweekly, monthly or bimonthly; it can be manual or automated. In the case of Data Science, it is an exploratory process, but it also requires time to prepare, analyze and experiment.
Business Intelligence and Data Science differ in the type of analysis performed, range, data integration, and skill set.
Knowing the differences between Business Intelligence and Data Science, you can make better decisions for companies. At XalDigital, we help you take advantage of your data to get relevant information and thus enhance your business.
