Big data can be in three forms:

Structured data.

Unstructured data.

Semi-structured data.

These forms are characterized by storage in a data warehouse system.

Semi-structured compilation

Can be proportionate to semi-protected compilation. Let's say, for example, that the definition contains the definition of type. An example of a semi-structured compilation is an XML.

Unstructured data

Datasets with unknown size or structure fall under the heading of unstructured data. Apart from the fact that the size is huge, unstructured data causes many challenges to data management with regards to extracting additional value from the data. There is a right sample of unstructured data and a heterogeneous data source consisting of a combination of identical text files, images, videos, etc. There are organizations that have huge amount of data, but unfortunately do not know how the data can be used for them This data has an accurate or unstructured form. We also refer to the discovery and correction of such data.

Structured Data

We refer to all data that we can store, consult and process as 'structured' data in a certain format. Over time, there have been many breakthroughs in computer science in developing techniques for smart brains to work with this kind of data (where the format is already known). They were successful in making it profitable for the customer. Today one sees data management problems arising from the volume of such data sets. The high rate of growth sometimes leads to a size of several zettabytes.

With volume figures like this, it's easy to understand where the name 'Big Data' comes from. OLTP systems are designed to work with structured data in which the data and their relationships are stored in tables. If you Know about and buy Apex Server Hosting then I will also written on this topic. 

What are advantages and disadvantages of big Data

Organizations can apply outside knowledge when making decisions

Organizations can access social data from search engines and sites like Facebook and Twitter to improve business strategies.

Better customer service

Traditional customer feedback systems are being replaced by new systems using 'Big Data' technologies. In this systems we use techniques based on Big Data and its natural language. This way we can read and evaluate consumer responses.

Early identification of risk for product/services

Better operating Efficiency

With new applications, we can use 'Big Data' techniques for the temporary storage of new data before we even know what data we want to contain in the data warehouse. In addition, integration of business applications with 'Big Data' technologies and data warehouse solutions can help load the 'real-time data' that we store there.

If you want to do course in big data analytics and all details about it like what is big data analytics, big data analytics and big data analytics syllabus, scope and job and what is salary after doing it, all these things are in detail from has been well covered in this post. Now you know understand that what is big data. let's now know about What is the meaning of big data analytics.

What is Big Data Analytics And What is the meaning of big data analytics?

Nowadays, with the advancement of technology, data can be analyzed using some advanced analytical techniques which include the study of structured, unstructured and semi-structured data. Big data is a term used to refer to data sets that are huge and cannot be handled with traditional analysis databases.

Since data analysis helps firms and businesses to make fast, efficient and thoughtful decisions, it has become a sought-after career by firms and businesses.

In today's time there are ample opportunities to work in the field of data analysis both private and government. Big data analytics is a growing field with a growing number of businesses and firms, but fewer people to fill these positions. Because very few people have the skills of Big Data Analytics.

Companies are ready to offer a very good salary for Big Data Analytics to those who have the right skill set and experience in the Big Data Analytics field.