Do you know what a dataset or data frame is? They are terms widely used when it comes to BigData work, and understanding these concepts is essential in the world of programming in general.
However, if you are a lover of software development in the area of Big Data, this information is not only important but necessary.
What is Big Data?
To understand the concept of Big Data, it is necessary to understand the term as a data set that can also be a combination of several data sets whose size, complexity and growth rate are exponential.
The complexity and massive growth of information and data are such that it is necessary to implement methods or study tools capable of analyzing such information. This is where programmers come into play, who develop such tools capable of analyzing and producing results in Big Data sets.
This is because, by conventional means, it would be an almost impossible task for a human to be able to analyze a large amount of information.
What is Big Data for?
Big Data is not just a set or several sets of meaningless data and information. The purpose of big data is to store information about an aspect that you want to know, for example, the number of users interested in a product.
This information is collected, and with a Big Data analysis tool, we obtain results that will help us make better strategic decisions to act accordingly.
What is a dataset?
A dataset could be defined as one of the parts that make up Big Data, but in what form? This is built around its own concept, being that the translation of a dataset is a set of data.
Now, this data represents a particular set of information, represented in a kind of table or analysis matrix. The table is made up of columns, with each column representing a data variable and the rows representing a specific data set.
In other words, the rows could be considered as the categories of the data, and the columns as the particular variables that make up the data. This combination of columns and rows is what is known and defined as the dataset.
What is a data frame?
The data frame could be defined through a possible non-literal translation as a data sheet or data matrix. This type of matrix is used in R programming development.
When you are studying various objects in programming, and you need a statistic, the data frame provides the means or tool to analyze the objects in a data sample. This, too, is made up of rows and columns, with the rows representing each object in the sample and the column representing the variables.
While it is true that a data frame is like an analysis matrix, there is an important difference. While a matrix only supports numeric data, a data frame supports alphanumeric data.
What are the uses of datasets?
Datasets function as a store of information that is used in a project to obtain a specific statistic. Such use can be defined through the different types of datasets that exist. For example:
File
A type of dataset that is characterized by being secure, fast and efficient by making a set of data available in an automatic filing cabinet. At the time of processing, the corresponding file cabinet is accessed.
Folder
Several datasets, i.e., a large amount of information, are stored here, which in turn are interconnected with each other. These data must be stored in the same format in order to be compatible, which enables mass data analysis.
Datasets
These datasets are used in specific programs and applications, depending on the type of format the data is in. They work very much like the Archive dataset type.
Web
Data that is stored on a web page and is usually represented in URLs, which contain all the information on the site.
What is the difference between a dataset and a data frame?
Basically, datasets and data frames are very similar in structure. However, the difference is that the data frame uses a matrix organization, which supports alphanumeric data, and the information is structured in respectively identified columns.
Thanks to the storage structure and the ability to use alphanumeric data in data frames, querying and modifying information in the datasheet is much easier.
Where to find datasets?
There are many places on the internet where different types of datasets with relevant information can be accessed. The best thing about it is that access to such websites is free, so you can easily research and better understand how datasets work.
UN Data is owned by the United Nations. On this website, you can obtain all the public data that this institution has to its credit.
On the other hand, Worldbank is the dataset of the World Bank, and you can find information on the economy, health, education and technological development.
Google Public Data not only has its own data but also collects information from other datasets. And just like many others, including from the governments of each country.
Do you want to dedicate yourself to the world of Big Data and datasets?
If you want to work in the field of Big Data, you should know that it is necessary to have knowledge in mathematics, know about methodologies such as Data scraping, master programming languages such as Python and be updated in disciplines such as Machine Learning.
In short, professionals in this field have mixed profiles. You can be a Data Scientist, Data Analyst, Python Developer or Artificial Intelligence Engineer – the important thing is that your passion for data stands out!