What is Data?

Data can be many things.

With Machine Learning, data is collections of facts:

Type	Examples
Numbers	Prices. Dates.
Measurements	Size. Height. Weight.
Words	Names and Places.
Observations	Counting Cars.
Descriptions	It is cold.

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Intelligence Needs Data

Human intelligence needs data:

A real estate broker needs data about sold houses to estimate prices.

Artificial Intelligence also needs data:

A Machine Learning program needs data to estimate prices.

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Healthcare

Healthcare and life sciences collect public health data and patient data to learn how to improve patient care and save lives.

Business

The most successful companies in many sectors are data driven. They use sophisticated data analytics to learn how the company can perform better.

Finance

Banks and insurance companies collect and evaluate data about customers, loans and deposits to support strategic decision-making.

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Storing Data

The most common data to collect are Numbers and Measurements.

Often data are stored in arrays representing the relationship between values.

This table contains house prices versus size:

Price	7	8	8	9	9	9	10	11	14	14	15
Size	50	60	70	80	90	100	110	120	130	140	150

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Quantitative vs. Qualitative

Quantitative data are numerical:

• 55 cars
• 15 meters
• 35 children

Qualitative data are descriptive:

• It is cold
• It is long
• It was fun

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Census or Sampling

A Census is when we collect data for every member of a group.

A Sample is when we collect data for some members of a group.

If we wanted to know how many Americans smoke cigarettes, we could ask every person in the US (a census), or we could ask 10 000 people (a sample).

A census is Accurate, but hard to do. A sample is Inaccurate, but is easier to do.

Sampling Terms

A Population is group of individuals (objects) we want to collect information from.

A Census is information about every individual in a population.

A Sample is information about a part of the population (In order to represent all).

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Random Samples

In order for a sample to represent a population, it must be collected randomly.

A Random Sample, is a sample where every member of the population has an equal chance to appear in the sample.

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Sampling Bias

A Sampling Bias (Error) occurs when samples are collected in such a way that some individuals are less (or more) likely to be included in the sample.

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Big Data

Big data is data that is impossible for humans to process without the assistance of advanced machines.

Big data does not have any definition in terms of size, but datasets are becoming larger and larger as we continously collect more and more data and store data at a lower and lower cost.

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Data Mining

With big data comes complicated data structures.

A huge part of big data processing is refining data.