https://en.wikipedia.org/wiki/Data_structureshivajikobardan said:I am really confused at this.
They are not the same thing. I know about data structure. They are structured, semi-structured and unstructured fyi...I got it just now.Baluncore said:
Oh, I was about to post the same link that @Baluncore did before he beat me to it. The term "data structure" has a specific meaning in computer science (as explained in the Wikipedia article), so if your class is using terms very similar to it to mean other things, that's a bit confusing. Glad you figured out what they wanted, though.shivajikobardan said:They are not the same thing. I know about data structure. They are structured, semi-structured and unstructured fyi...I got it just now.
The structures of big data refer to the ways in which large volumes of data are organized, stored, and processed in order to extract meaningful insights and information.
The main types of structures used in big data are structured, semi-structured, and unstructured data. Structured data is organized and easily searchable, while semi-structured data has some organization but also contains unstructured elements. Unstructured data has no predefined structure and can include text, images, videos, and audio files.
Big data structures differ from traditional data structures in terms of volume, velocity, and variety. Big data structures are designed to handle large volumes of data at high speeds, and they can also accommodate a wide variety of data types, including unstructured data.
Some common tools and technologies used to manage big data structures include Hadoop, Spark, NoSQL databases, and data warehousing solutions. These tools and technologies help to store, process, and analyze large volumes of data in a scalable and efficient manner.
Big data structures can be used to drive insights and decision-making by allowing organizations to analyze and identify patterns and trends within large datasets. This can help inform business strategies, improve operations, and drive innovation.