Differences between big data and business intelligence
Both terms play an increasingly important role in today’s business operations, so let’s take a look at what they mean and see what the real difference is between big data and business intelligence, how they are used, and what their benefits are for businesses.
Big data
Big data is the information that organizations store, usually in large sets or volumes. In many cases, this information is very difficult or even impossible to manage effectively.
A clear example of what big data is is provided by chinese overseas africa database social networks: companies collect a lot of information on these platforms: impressions, click rates, customer engagement, etc. All these indicators add up to form the sets of information we call big data.
There is one basic thing we need to know when we talk about big data and business intelligence, and that is the difference between structured and unstructured data.
Structured data is what we would expect to find in formal databases, and is often identified as quantitative data. It can be found in spreadsheets, with carefully organized rows and columns that can be easily read and evaluated.
Unstructured data refers to virtually everything else and can be considered qualitative in nature. Examples of this type of data include videos, images, sensor information, call transcripts, and other forms of informal communication, such as the body text of an email.
What is the difference between Big Data and Business Intelligence?
Business Intelligence
What we call business intelligence encompasses the digital tools that are used to analyze data, both structured and unstructured , and convert it into actionable information that will then be taken into account for decision-making .
For most organisations, business intelligence is easier to achieve with structured data. However, advances in the use of AI and machine learning mean that unstructured information is being deciphered more effectively every day.
Business analytics and big data
And what is the impact of business analytics in this context? Is there any difference between it and business intelligence?
Business analytics , the most common abbreviation for which is BA, is fundamentally future-oriented . It is based on the use of predictive models to create a vision of the future development of a given company. Its function is therefore to help management make better decisions.
The difference between BA and BI is that the latter studies the company's internal data. Business analytics, on the other hand, takes into account data extracted from external sources . Some of these sources may be industry trends, demand behavior, or macroeconomic data over which we have no control, but whose knowledge we can use for our own benefit.
Ultimately, the fundamental difference between BA and BI is that, although both are dedicated to improving decision-making and company processes, business intelligence corrects current errors and business analytics is responsible for preventing such errors from being made in the future .
Neither of the two disciplines could perform its functions without data, which is why the three are often referred to in similar contexts and why the nomenclature creates some confusion.
As we can see, the three concepts are key to improving the strategy of any business organization. That is why it is necessary to know them: to fully understand the new digital context that affects all sectors of the global industrial fabric.