The nature of data, their Heterogeneous sources of structured, semi-structured and unstructured data.Diversity of Data Distribution. Can lead to different Interpretations. May call for Specialization and Standardization.Covid Examples: The correlation of various Age Factors and Pre-existing health conditions affecting the spread.

Variety

Refers to the Huge Volumes of Data.An abundance, an explosion of Data.Covid Examples:The number of people getting infected through the peaks of the pandemic.The number of people getting tested versus testing positive.

Volume

Big Data can be thought of as having 5 distinct dimensions. <ul><li>Volume</li><li>Velocity</li><li>Variety</li><li>Variability</li><li>Value</li></ul>

The 5 Vs of Big Data

The speed at which new data is created,and the need for the new data to be considered and analyzed.The speed at which the data is generated and processed to meet the expectations.Covid Examples:The speed at which the pandemic was spreading to new geographies.The pace at which the new variants and their infections were spreading.

Velocity

How the data is put to work?Can lead to informed decisions and measurable improvements based on the data being collected, analyzed, researched, and interpreted at a global-scale.Covid Examples:Leading to informed decisions like -<ul><li>Governments imposing restrictions like lockdowns travel bans, etc.,</li><li>Pharma companies planned on scaling up vaccine production, etc.</li><li>Temporary testing, healthcare, and vaccination centers sprung across, to cater to pandemic needs</li></ul>

Value

Inconsistencies and Uncertainties in Data.Depends on factors of data, like - sampling methods, mode of capture, place, time, intervals, parameters, accuracy, completeness, etc.Can lead to variations in meaning, interpretation, processes, and challenges involved.Covid Examples:Completeness, Correctness of data relating to symptoms and pre-existing conditions. And their interpretations.Experience of personnel recording the data.Types of equipment and tools used to record and capture.

Variability (or Veracity)

Data is a critical tool for today's fast-paced world. Covid pandemic has proved that recently. The fight against covid has highlighted how we can use an intensely data-driven approach for the future of our existence.

I recently spoke with Mark Masselli and Margaret Flinter for an episode of their “Conversations on Health Care” radio show, explaining how IBM Watson’s Explorys platform leveraged the power of advanced processing and analytics to turn data from disparate sources into actionable information. My hosts wanted to know what this data actually looks like. And how, they wondered, are the characteristics of big data relevant to healthcare organizations in particular? As it turns out, data scientists almost always describe “big data” as having at least three distinct dimensions: volume, velocity, and variety. Some then go on to add more Vs to the list, to also include—in my case—variability and value. Here’s how I define the “five Vs of big data”, and what I told Mark and Margaret about their impact on patient care. Volume Big data first and foremost has to be “big,” and size in this case is measured as volume. From clinical data associated with…

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Variety

The 5 V's of big data (and their examples correlating to covid!)

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Variety

The 5 V's of big data (and their examples correlating to covid!)

IDEA ABOUT

MORE LIKE THIS

The 5 V's of big data - Watson Health Perspectives

The 6 Elements of Truly Transformative Business Models

The Democratization of Data Science

It's time to

READ

LIKE

A PRO!

Bite-sized knowledge
to upgrade
your career