Databases
Well-thought-out collections of computer files, the most important of which are called tables.
Tables
Holds the data for a database.
... [Show More] Consists of records and fields that can be queried.
Big Data
Data that is collected from all over the internet, including smartphone metadata, internet usage records, social media activity, computer usage records, and countless other data sources.
Data Mining
The examination of huge sets of data to find patterns and connections and identify outliers and hidden relationships.
Structured Data
Resides in a fixed format. It is typically well labeled and often with traditional fields and records of common data tables.
Unstructured Data
unorganized data that cannot be easily read or processed by a computer because it is not stored in rows and columns like traditional data tables.
Semi-Structured Data
lands somewhere in-between structured and unstructured data. It can possibly be converted into structured data, but not without a lot of work.
Extract, Transform, and Load (ETL)
tools that are used to standardize data across systems and allow the data to be queried
Data Management Processes
acquiring data, making sure the data are valid, and then storing and processing the data into usable information for a business
Structured Query Language (SQL)
Language (SQL)The most widely used standard computer language for relational databases, as it allows a programmer to manipulate and query data.
Business Analytics
Attempts to make connections between data so organizations can try to predict future trends that may give them a competitive advantage.
Data Mining
The examination of huge sets of data to find patterns and connections and identify outliers and hidden relationships.
Topic Analytics
tries to catalog phrases of an organization's customer feedback into relevant topics
Text Analytics
sometimes called text-mining, hunts through unstructured text data to look for useful patterns such as whether their customers on Facebook or Instagram are unsatisfied with the organization's products or services.
Descriptive Analytics
the baseline that other types of analytics are built upon.
Predictive Analytics
attempts to reveal future patterns in a marketplace, essentially trying to predict the future by looking for data correlations between one thing and any other things that pertain to it.
Decision Analytics
builds on predictive analysis to make decisions about future industries and marketplaces. [Show Less]