Does big data include structured data?

Does big data include structured data?

Does big data contain structured data

Yes, big data contain structured data. Structured data account for only about 20 per cent to big data, but the organization and efficiency of structured data make it the backbone of big data.

Data, whether structured or unstructured, is indispensable to the business. The term big data is common in every type of industry, not just the tech industry in particular. It is not possible to specify big data as its definitions vary but deep down the line, common understanding of big data is that it means huge volume of data delivered at high velocity, making it difficult to collect, store, maintain, analyze and visualize.

What is structured data

Structured data is well organized having definite length and format for easy access. Data exist in a format created to be collected, stored, processed, organized and analyzed. Unstructured data exist without any format and include audio, video, images, social media posts, email. Data account for a whopping 80 per cent to big data. Semi-structured data is somewhat defined as a subset of structured data. It adds keywords, tags, metadata to data types that were once considered as unstructured data. Its examples are adding descriptive elements to pictures, email.

Structured data, unlike unstructured data, is more efficient for data mining process of traditional big data applications. Structured data are stored in the database, excel sheets having a fixed number of rows and columns with defined attributes. Data can be easily retrieved.

Structured data is usually managed by SQL (Structured Query Language) for organizing, querying and analyzing data that is stored in RDBMS (Relational Database Management System) and spreadsheets.

Example of Structured data

Examples of structured data are traditional Relational Database Management System (RDBMS), spreadsheets with neatly organized rows and columns and defined attributes such as name, age, gender, address, currency, billing information, date.

Characteristics of Structured data

  • Highly organized
  • Clearly defined
  • Easy to access
  • Easy to analyze

Sources of Structured data

Structured data is very reliable and with the evolution of technology, new sources of structured data are being produced.

Sources of structured data are:

  • Machine-Generated data data created by machine without involving human intervention.
  • Human-Generated data data produced by humans in interaction with computers.

Examples of Machine-Generated data are:

  • Financial data Many financial systems are based on a set of predefined rules that have automated processes. For example, Stock market trading data contain data such as the name of the company, company symbol.
  • Point of sale data In shopping complex at the payment counter, cashier scans bar code of the product and all details regarding product appears on a computer screen.
  • Sensor data include smart meters, id tags of radiofrequency, medical devices. Sensory data is used for inventory control, management of supply chain.
  • Weblog data servers, networks capture our activity and repeatedly show us data of our interest. It amounts to huge volumes of data from which useful data is extracted to deal with product marketing and selling, winner of political elections, etc.

Examples of Human-Generated data are:

  • Click-Stream data While searching for information on search engines, various links related to our search appear on the screen and as we click on the link, data is generated at high velocity.
  • Input data data that a user feeds in a computer, such as a name, address, age, etc. Data is useful to understand behavior of customers, change in needs and preferences.
  • Gaming data In-game, each and every move and can be recorded for analyzing. It can be used to understand how the user moves through in a gaming portfolio .