IB Digital Society Topic 3.1F Big Data and Data Analytics Revision Notes (SL/HL)

IB Digital Society Topic 3.1F Big Data and Data Analytics Revision Notes (SL/HL) | RevisionDojo

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3.1F Big Data and Data Analytics

What Makes Data Big

The scale of big data goes beyond sheer size. It arrives in such quantity, at such speed, and in so many forms that ordinary tools cannot store or process it. Handling it needs specialised systems spread across many machines.
Scale changes the stakes. It opens up things that were possible only with huge datasets, like tracking a whole population in real time. It also magnifies mistakes: a single error can repeat billions of times.
The classic description is the four Vs. Volume is the sheer amount (billions of records). Velocity is the speed new data streams in, often real time from sensors, clicks, and transactions.
Variety is the mix of forms (tidy tables plus messy text, images, audio, video) that older databases were never built to hold together.
The fourth V, veracity, asks how trustworthy the data is. Noisy, incomplete, or biased data is not reliable just because there is a lot of it; it is the V most often forgotten.

Analytics: Extracting Insight at Scale

Data analytics examines raw data to find patterns and turn them into something a person can act on; at big-data scale this is done by machines that sift more than any human could read.
The work moves through stages: messy data is cleaned of errors and gaps, then analysed for patterns, and only then does a pattern become an insight guiding a decision.

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Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

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3.1F Big Data and Data Analytics

What Makes Data Big

The scale of big data goes beyond sheer size. It arrives in such quantity, at such speed, and in so many forms that ordinary tools cannot store or process it. Handling it needs specialised systems spread across many machines.
Scale changes the stakes. It opens up things that were possible only with huge datasets, like tracking a whole population in real time. It also magnifies mistakes: a single error can repeat billions of times.
The classic description is the four Vs. Volume is the sheer amount (billions of records). Velocity is the speed new data streams in, often real time from sensors, clicks, and transactions.
Variety is the mix of forms (tidy tables plus messy text, images, audio, video) that older databases were never built to hold together.
The fourth V, veracity, asks how trustworthy the data is. Noisy, incomplete, or biased data is not reliable just because there is a lot of it; it is the V most often forgotten.

Analytics: Extracting Insight at Scale

Data analytics examines raw data to find patterns and turn them into something a person can act on; at big-data scale this is done by machines that sift more than any human could read.
The work moves through stages: messy data is cleaned of errors and gaps, then analysed for patterns, and only then does a pattern become an insight guiding a decision.

Definition

Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Note

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam quis nostrud exercitation.

Excepteur sint occaecat cupidatat non proident

Tip

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

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Topic 1 - Introduction - Digital Society1 subtopic

Topic 2 - Concepts - Digital Society7 subtopics

Topic 3 - Content - Digital Society7 subtopics

Topic 4 - Contexts - Digital Society7 subtopics

Topic 5 - Challenges and Interventions - Digital Society (HL)3 subtopics

IB Digital Society 3.1F Big Data and Data Analytics Notes

Topic 1 - Introduction - Digital Society1 subtopic

Topic 2 - Concepts - Digital Society7 subtopics

Topic 3 - Content - Digital Society7 subtopics

Topic 4 - Contexts - Digital Society7 subtopics

Topic 5 - Challenges and Interventions - Digital Society (HL)3 subtopics

3.1F Big Data and Data Analytics

What Makes Data Big

Analytics: Extracting Insight at Scale

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account

3.1F Big Data and Data Analytics

What Makes Data Big

Analytics: Extracting Insight at Scale

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account