It is not uncommon for new technological concepts to appear every day in the industry, which sometimes tend to confuse people about their true meaning. That is why in this article we will review what Business Intelligence (BI) is, what the meaning of Data Science (DS) is, and how these terms differ from the analytical area.
Business Intelligence
We will begin by talking about BI, which is defined as the ability to transform data into information and this in turn convert it into knowledge, in order to optimize decision making in business. It is related to control panels, management, organization and production of information from data. BI tries to answer questions that do not seem so obvious in a business unit. It helps to see the relationships between various variables, but does not predict them exactly.
Data Science
Data Science is more complex than BI and can be summed up as an interdisciplinary field that analyses various sources of data, structured or unstructured, to extract conclusions and useful information that will serve a company’s decision-making. It is a technology that emerged as a response to the millions of data that each organization has and does not know how to use.
Until now, the contrasts may not be clearly appreciated, however, what unites both concepts is, without a doubt, data, which has become a fundamental part of companies.
And what are the differences?
- Business Intelligence operates on records stored in databases, thus helping to interpret past figures. It is mainly used for descriptive reporting or analysis. Data Science, on the other hand, looks forward: it analyses past data, such as trends or patterns, to make future predictions, and is mainly used for predictive analysis or prescriptive analysis.
- BI data sources are usually pre-planned and added gradually. Data Science is much more flexible, as its sources can be added along the way as needed.
- Business Intelligence uses internal company data to a greater extent, whereas DS processes internal and external data.
- BI provides detailed reports, KPIs and trends, but it does not reveal what this data will look like in the future. DS does this in the form of patterns and through experimentation.
- BI systems tend to be stockpiled and stacked, making it difficult to deploy solutions based on them in the business. Data Science data can be distributed in real time.
- BI provides a single version of the truth, while DS offers accuracy, confidence level, and broader possibilities with its findings.
- Business Intelligence works with commercial data, such as sales, marketing, customer service, and employee and company data.
On the other hand, Data Science is based on documents, statistics, and social media elements such as emails, photographs, audios, videos, among others.
In conclusion, we can say that both technologies are mutually facilitating and that Data Science is best done in conjunction with BI. While the latter is the logical first step, DS follows to gain deeper insight into business trends.
