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The growing repository of information in the present times gives an account of the volume and velocity at which data is growing. There are a large number of data sources in the present times ranging from social media to imaging technologies. Different types of smart devices and sensors process information in real-time by collecting large amounts of data. The ocean of information that is before us is an opportunity to transform our business into data-driven entities.
The increasing volumes of information have given rise to a fundamental question. If data is the oil, currency, and oxygen of the 21st century, then various institutions need to adapt accordingly to facilitate the seamless processing of data. Reacting to the growing streams of data from various sources, major businesses have started training in data-related projects. In the present times, the best data science courses form a part and parcel of training for employees that have to deal with data-driven projects.
Data sources and data attributes
The sources of data are indeed numerous. We highlight the prime sources of data that are prioritized according to the volume of data generated. A lot of data is generated by credit card companies as the number of transactions as well as the customer data are constantly growing in the present time. The processing of millions of transactions generates loads of data that can easily be stored in a data lake. The companies that are involved in the business of telecommunication analyze the calls and messages of customers that are indeed voluminous. Another important source of data includes the social media platforms that contain very intricate details related to the profile of millions of customers.
The most important attribute of data in the present times is its voluminous capacity. Another important attribute that is associated with data types is their complexity. In addition to this, the size and structure of data in the present times is also an attribute that is in the limelight.
The prime contributors of the data league
The prime contributors of the data league are those applications and domains that generate data of the order of 2.5 quintillion bytes in a single day. The first main contributor in this data league is the mobile sensors and all those wearables and smart devices that are dependent upon them. The next important contributors of the data league are the social media platforms which generate data more than that generated by hundreds of orthodox web platforms put together. The data generated by video surveillance platforms is also gigantic given the range of information that it covers. Another important source of data in the present times is the smart grids that are being constantly installed in various cities. The geophysical exploration that is being carried out with the help of modern devices also generates large quantities of data which is difficult to process using the traditional means. Finally, the last prime contributor of the data league is the medical industry. The data generated by medical imaging and gene sequencing is also contributing to the growing streams of big data by leaps and bounds.
The structural pyramid of data
The structural pyramid of data can be compartmentalized into four main entities. The entity which is at the bottom of the pyramid is unstructured data and this is the most abundant form of data that we see around us. The quasi-structured data forms the second last layer of the data pyramid. While the unstructured data lacks any form of inherent structure, the quasi-structured data may come with some form of defined structure. It needs to be noted at this point in time that quasi-structured data may be formatted with the available tools but it takes a lot of time. To exemplify this, clickstream data has a lot of inconsistencies but it can be processed and formatted with the range of tools that are available to us. The second layer of the data pyramid is called semi-structured data. This type of data is relatively less abundant as compared to unstructured data. Semi-structured data usually comprises large textual data files that are easy to process and format. The topmost layer of the data pyramid comprises structured data sets. This type of data is highly ordered in nature and form but is least abundant. This type of data can readily be used for online data processing and analytical outputs.
This article serves as a useful first guide for understanding sources, attributes, and the structural pyramid of data.