So far, this course has focused on the functionality of a database and how to interact with a database. Understanding why you may need databases in the first place is just as important.
Consider the fact that data is used in so much of what you do on a day-to-day basis. Companies use data every minute of every day, and they must use databases so that they can store, manage and retrieve that data quickly. Pretty much any current information system, eCommerce site, or app that you use relies on databases to manage its data and information.
There’s a lot of planning involved to ensure that data and information is accurate and usable. Data management is a discipline that requires focus on the creation, storage, and retrieval of data. There’s a big focus on data management in most organizations and companies, because ensuring that data is handled correctly is critically important to operations. Database management systems are collections of programs that help manage database structures and control access to the data in the database.
Data, information, and knowledge are important terms to know when it comes to databases. Recall that a database is a computer structure that holds a collection of related data. A database consists of two types of data: raw facts and metadata. Metadata, or data about data, describes the data characteristics or relationships of the data. The metadata describes the complete picture in the database, or the schema.
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This could include the data types and sizes of the columns in a table, or the relationships and constraints that have been set in the database.Regular data consists of raw facts that don’t have any meaning behind them yet. Think of the database that you have been using to try out SQL queries. End-user data like the employee name or customer address are just raw data elements. There is not much that can be done with this raw data unless you start to transform the data through those SQL queries that you have been using.
Information, on the other hand, is created when you take that raw data and process it to give it meaning, or to answer questions that you have. To give it meaning, information requires context about the criteria. This could be as simple as reordering rows of data with an ORDER BY or as complex as joining multiple tables and providing summaries of purchase trends. Those SQL queries process the data, turning that raw data into information.
Knowledge can then be built from the body of information and facts about a specific topic. The knowledge implies that you have some pre-existing understanding and familiarity of the information as it applies to the topic. This could be as simple as understanding the organization or business processes.
Source: Authored by Vincent Tran