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Showing posts from May, 2026

Understanding Traditional Data Analytics

What is Traditional Data? Traditional data analytics is rooted in environments where information is highly structured, stable, and captured through well-defined operational systems. Its strength lies in applying established analytical logic to  datasets  governed by consistent rules and formats. Its defining characteristics include: Traditional Data Benefits Organizations rely on traditional analytics when accuracy, data lineage, and consistency are essential to operational and regulatory processes. Because this approach focuses on controlled datasets, it supports decision-making that depends on precision and reproducibility. Key benefits include: Challenges of Processing Traditional Data Traditional analytics becomes less effective as  data ecosystems  expand beyond structured sources or accelerate beyond scheduled reporting cycles. These limitations can restrict the scope of analysis and slow response times in more dynamic contexts. The primary challenges include: ...

Implications of big data for individuals and society

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https://floyden.home.blog/2019/04/16/implications-of-big-data-for-individuals-and-society/

the VS of big data

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  Big data definitions may vary slightly, but it will always be described in terms of volume, velocity, and variety. These big data characteristics are often referred to as the “3 Vs of big data” and were first defined by Gartner in 2001. Volume As its name suggests, the most common characteristic associated with big data is its high volume. This describes the enormous amount of data that is available for collection and produced from a variety of sources and devices on a continuous basis. Velocity Big data velocity refers to the speed at which data is generated. Today, data is often produced in real time or near real time, and therefore, it must also be processed, accessed, and analysed at the same rate to have any meaningful impact.  Variety Data is heterogeneous, meaning it can come from many different sources and can be structured, unstructured, or semi-structured. More traditional structured data (such as data in spreadsheets or relational databases) is now supplemented by...