APCSP Unit 10 - Big Data

Big Data

extremely large and ever-growing amounts of data, both structured and unstructured, that are too large or complex to be dealt with by traditional data-processing application software

structured data

data that resides in a fixed field within a spreadsheet or relational database; data that has been intentionally collected in a organized manner

unstructured data

data that is not stored in a predefined way; it is not structured or categorized

The Five V’s of Big Data

volume, velocity, variety, veracity, value

data center

a physical room, building, or facility that houses the equipment necessary for storing data and hosting applications and services

data compression

a reduction in the number of bits needed to represent data

lossy compression

a non-reversible process that reduces the number of bits in a digital file by discarding some of the data and information

lossless compression

a reversible process that reduces the number of bits in a digital file without losing any data

byte

a group of 8 bits

kilobyte

one thousand bytes

megabyte

one million bytes (or one thousand kilobytes)

gigabyte

one billion bytes (or one thousand megabytes)

terabyte

one trillion bytes (or one thousand gigabytes)

cleaning data

a process that makes data uniform without changing its meaning

bias

prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair

COPPA

Children’s Online Privacy Protection Act

data

raw facts and statistics collected together for reference or analysis

information

data that has been processed, interpreted, analyzed, organized, or structured to make it more meaningful or useful

extraction

retrieving data, processing it, and placing it in a structure that can be analyzed

filtering

temporarily removing or hiding unwanted data

sorting

arranging data in alphabetical or numerical order

data mining

the practice of analyzing large databases in order to generate new information

trend analysis

the practice of attempting to spot a pattern in data

pattern

consistencies/repetitions in data; useful for predicting future behavior or events

visualization

the presentation of data in a pictorial or graphical form; allows decision makers to grasp a difficult concept or identify new patterns

causation

proof that one event or condition directly led to another event or condition

correlation

how closely related two or more events or condition are; just because trend graphs look similar does not mean that one trend caused another trend

model

a physical or virtual representation of an object, concept, or idea

simulation

a method for testing a hypothesis of a situation using a model