Big Data: A broad term for data sets so large or complex that traditional data processing applications are inadequate.
Business Analytics: Refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.
Business Intelligence: The set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes.
Data, Information & Knowledge: Data arise from raw bits and pieces of information with no context. By adding the context-the raw bits and pieces become information. the data is put into context, aggregated, and analyzed; it can be used to make decisions for an organization. The consumption of information produces knowledge.
Database: An organized collection of related information.
Database Management Systems (DBMS): Programs that provide user-friendly, interfaces to view and change a database, create queries, and develop reports.
Data Mining: An analytic process designed to explore large amounts of data.
Data Types: Text, Number, Yes/No, Date/Time, Currency, Paragraph Text, and Object are amongst the most common data types to be stored.
Data Warehouse: Extract data from one or more of the organization’s databases and load it into the data warehouse (which is itself another database) for storage and analysis.
Field(s): Database tables contain fields(columns) and records (rows). Example fields are firstname, lastname, studentID, GPA. It is possible to connect all the tables in the database through the field(s) they have in common.
Knowledge Management: The process of capturing, developing, sharing, and effectively using organizational knowledge.
Metadata: Data that describes other data.
Normalization: To normalize a database means to design it in a way that: reduces duplication of data between tables and gives the table as much flexibility as possible.
NoSQL Databases: Not Only SQL Database. A type of database that operates using means other than relational tables. NoSQL became popular with the growth of Web 2.0 and the need for faster data retrieval.
Primary Key: The unique identifier for each record in a table. For example, social security number or student ID.
Record(row): Records as the rows of the table.
Relational Database: One in which data is organized into one or more related tables.
Structured Query Language (SQL): A computer language that lets people, database developers, and others extract information from the database.
Table: Each table has a set of fields, which define the nature of the data stored in the table. Database tables contain fields(columns) and records (rows).