What is Big Data?
Big data generally refers to a large and diverse set of information that expands at ever increasing speed. The term “Big Data” includes the volume of the information, the pace of speed at which it is collected or created, and the scope of the data points being covered. Big data provides the raw information used in data mining.
How Big Data Works
Big data is a wider term that includes different forms of information. It can be classed into three primary types: structured, unstructured, and semi-structured.
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Structured data is highly organized and typically resides in databases or spreadsheets, often consisting of numerical information.
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Unstructured data lacks a predefined format and is more qualitative in nature. Examples include text, social media posts, and IoT sensor data.
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Semi-structured data falls between these two, exhibiting characteristics of both.
Data is collected from numerous sources, including surveys, online purchases, check-ins, and user interactions with electronic devices. Once collected, it is often stored electronically in data warehouses or data lakes. Analyzing such vast and complex datasets requires specialized software, with many cloud-based solutions available to manage the process.
Advantages and Disadvantages of Big Data
The ever-increasing use of data is both a blessing and a curse. Collecting more data on users helps companies tailor products and services based on what customer actually wants and eventually benefits both producers and the customers.
Although advanced analytics offer significant advantages, the sheer volume of big data can create information overload and hinder decision-making. Organizations face the challenge of sifting through vast datasets to extract meaningful insights. Proactively determining which data is likely to be relevant can streamline the analysis process and improve outcomes.
Moreover, the format of data significantly impacts its usability. Structured data, typically numerical, is easily organized and stored. However, unstructured data, such as emails, videos, and text documents, requires advanced techniques to extract value.