The data generated by the various and the vast number of activities such as online transactions, files, text documents, logs, social media activities, weblogs, web activities are enormous and cannot be handled by simple tools. Ranging in Petabytes and Exabytes of data approximately, it is present mainly in raw form. It is obvious that such a huge amount of data present is neither uniform nor corresponds to a well-defined format. Some of these are in the form of heaps of data, whereas some are sorted in a logical and structured format.
As data is present in such an enigmatic form, and that too, in an unexpectedly large quantity, it was essential to classify the data into certain types. There are mainly three types in which the data have been classified, which are:
- Structured Data: The type of data which can be represented in terms of rows and columns. In other words, it can be treated as an organized data format with a fixed schema. For example, online transactions, social security numbers, zip codes, etc.
- Unstructured Data: Random heap of data which is not organized in a tabular format (in rows and columns) and neither stored nor processed in a database. It is an unorganized set of data with an unknown schema. For example, PDF, Word files, Media logs, texts, etc.
- Semi-Structured Data: The combination of structured and unstructured data is semi-structured data. It can be stored, but cannot be processed in a database. It is a partially organized data which does not have a fixed format. For example, XML data, emails, etc.
The significance of Big Data and Data Science
When it comes to the handling of humongous data efficiently, big data is what comes into play. Big data take care of the huge volume of data effectively by using traditional tools or software that exists. Often, people compare big data with data science but big data is not equivalent to data science. In fact, big data can be treated as part of data science. Generally, big data combined with data science are often termed as big data science which seems more legitimate. It is the unstructured data that cannot be analyzed and processed with simple and traditional tools and methods which we call as Big Data today.
As a field of study, big data has discovered many applications and uses in the modern world. It has opened a kind of a new dimension of data, wherein so many opportunities are available for almost all types of businesses and associations. Apart from analyzing data format and processing it into a readable format, it has its scope over customer requirements, making more advanced and smarter machines (using AI and ML) in order to deliver more accurate information on or about the data.
The scope and future of Big Data are infinite, and in the modern world, the requirements of a data analyst are increasing surprisingly. So, to settle in this field, getting a data science certification would be a great step to enter into the world of Data Science.
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