Big Data: what is it, what are its advantages and how to use it in your company?
Posted: Sun Jan 19, 2025 8:04 am
Big Data is becoming increasingly important for business management. It has evolved significantly in recent years and is playing a fundamental role in large organizations. This methodology is ideal for generating insights that generate a lot of value for the business and the most diverse benefits for the growth of your company.
In this article, we will define the concept of Big Data, what its characteristics are and the beginning of its history, at NASA, until its full development today, being highly requested in innovation management .
We will also detail its potential to optimize costs and improve business profits, as well as tips on how your company can apply the techniques. Follow along here!
What is Big Data?
There is no exact definition of what Big Data is, as it can kenya telegram lead have very different purposes and uses among business professionals, marketing and project professionals, and IT specialists. After all, they use this tool in very different ways.
But there is a consensus in which we can understand that it is a general term to define a set of strategies and technologies necessary to gather, organize, process and extract information about a large set of data.
This data provides a basis for extracting insights, which aid in decision-making and leverage several advantages that we will detail in another topic.
Looking back at the history of Big Data, its initial idea was created in the 1990s by NASA, which intended to cross-reference all types of information across all of the organization's existing databases. Although there was no technology for its effective implementation, the methodology began to be discussed and taught in academic circles.
Business-focused data modeling, such as DataWarehouse and methods such as CRM and BI, began to be developed, but there was still no viable processing capacity for handling a very large mass of data.
In the 2000s, Yahoo launched Hadoop, an open source for Apache (Linux) servers that managed to use the concept, condensing and importing data from different structures and sources, through APIs.
And around 2005, the use of Big Data finally became viable with the advancement of processing speed, immense storage capacities and the innovation of Cloud Computing (technology of data stored in the cloud).
Its development and resources have been further improved and, currently, we have several solutions created and supported by large companies, such as Microsoft, Oracle, Amazon, IBM and Google, as well as excellent companies and consultancies that are experts in these tools.
The basic requirements for working with Big Data are the same as for working with data sets of any size. However, the massive scale, the speed of importing and processing the data, and its characteristics mean that each stage of the process needs to be treated in a very specific way and solutions designed for each project.
The technical objective of most big data systems is to explore information and connections from a large volume of data with the most diverse origins, which would not be possible using conventional methods.
In this context, Big Data means a data set that is too large to process or store with traditional tools or on a single computer.
This means that the common scale of large data sets is constantly changing, and their content can vary significantly from organization to organization.
In this article, we will define the concept of Big Data, what its characteristics are and the beginning of its history, at NASA, until its full development today, being highly requested in innovation management .
We will also detail its potential to optimize costs and improve business profits, as well as tips on how your company can apply the techniques. Follow along here!
What is Big Data?
There is no exact definition of what Big Data is, as it can kenya telegram lead have very different purposes and uses among business professionals, marketing and project professionals, and IT specialists. After all, they use this tool in very different ways.
But there is a consensus in which we can understand that it is a general term to define a set of strategies and technologies necessary to gather, organize, process and extract information about a large set of data.
This data provides a basis for extracting insights, which aid in decision-making and leverage several advantages that we will detail in another topic.
Looking back at the history of Big Data, its initial idea was created in the 1990s by NASA, which intended to cross-reference all types of information across all of the organization's existing databases. Although there was no technology for its effective implementation, the methodology began to be discussed and taught in academic circles.
Business-focused data modeling, such as DataWarehouse and methods such as CRM and BI, began to be developed, but there was still no viable processing capacity for handling a very large mass of data.
In the 2000s, Yahoo launched Hadoop, an open source for Apache (Linux) servers that managed to use the concept, condensing and importing data from different structures and sources, through APIs.
And around 2005, the use of Big Data finally became viable with the advancement of processing speed, immense storage capacities and the innovation of Cloud Computing (technology of data stored in the cloud).
Its development and resources have been further improved and, currently, we have several solutions created and supported by large companies, such as Microsoft, Oracle, Amazon, IBM and Google, as well as excellent companies and consultancies that are experts in these tools.
The basic requirements for working with Big Data are the same as for working with data sets of any size. However, the massive scale, the speed of importing and processing the data, and its characteristics mean that each stage of the process needs to be treated in a very specific way and solutions designed for each project.
The technical objective of most big data systems is to explore information and connections from a large volume of data with the most diverse origins, which would not be possible using conventional methods.
In this context, Big Data means a data set that is too large to process or store with traditional tools or on a single computer.
This means that the common scale of large data sets is constantly changing, and their content can vary significantly from organization to organization.