Welcome to Types of Data, Sources, and Uses. After watching this video, you will be able to: Identify different types of data, Recognize data sources, and List some of the ways to use data. Today’s world is full of data. But how do we define data? Data is any set of characters that is gathered and translated for some purpose, usually research or analysis. Data can consist of: Facts, observations, perceptions; Numbers, characters, symbols; Images, audio, text; or any combination of these. There are multiple types of data, including these common types: Single character, Boolean (true or false), Text (string), Number (integer or floating point), Picture, Sound, and Video. Data can be classified as primary or secondary. Primary data is generated directly by the individual needing the information. Secondary data is information is data that has already been gathered for another purpose. Raw data, also known as primary data, contains numbers, instrument readings, and figures collected from sources. In the context of an examination, the raw data might be a raw score. When processed, this raw data output can be analyzed and studied. Data and information are collected on a computer using a hard drive or another storage device. Data is stored in binary form using 0s and 1s. There are several forms of data. Personal data is anything specific to an individual, like name, demographics, location, address, and other identifying information. Transactional data is anything that requires an action to collect the information. Clicking online advertisements, making an online purchase, and visiting certain websites are all forms of transactional data. Transactional data is crucial for businesses, helping them to expose variability and optimize operations. Web data refers to any data pulled from the Internet for research or other purposes. Web data is a catchall for public-facing information on the Internet (in other words, not stored in a private database). Companies can use this information to monitor competitors, track potential customers, keep track of channel partners, generate leads, and build applications. Sensor data is information produced by objects and is often known as the Internet of Things. This type of data covers everything from a smartwatch measuring heart rates and temperature, to a building with external sensors that measure the weather or turn on lights when motion is detected. Currently, sensor data’s primary use is to help optimize processes. The level and rigidity of the data’s structure determine the information’s classification. Data can be structured, semi-structured, or unstructured. Databases store and display structured data in rows and columns, similar to an Excel or Word table. The information has a well-defined schema and a rigid structure. These characteristics make relational databases, which store data in tables, ideal for structured data. Microsoft SQL Server, IBM Db2, and Oracle databases are forms of structured data. Semi-structured data has some organizational properties; however, the information does not collect in the rows and columns required by a rigid, tabular schema. Instead, semi-structured data is organized into a hierarchy using tags and metadata and is stored in non-relational databases. Unstructured data is information that does not have an identifiable structure or specific format, sequence, semantics, or rules, and is often stored in NoSQL databases. The most common examples of unstructured data include text, like Word documents and emails. However, unstructured data also includes images, audio files, and log files. MongoDB, Hbase, Cassandra DB, and Oracle NoSQL DB are forms of semi-structured and unstructured data. A multitude of data sources are available today, including: Internal organizational data stored in a database; Publicly available data like weather, financial, and government; APIs and web services,; 67 00:04:45,030 --> 00:04:47,050
Web sites; Data streams and feeds; Social platforms; and Devices with sensors. This data is stored, processed, and made available for analysis, providing businesses with insights into their performance. Data sources can be: internal or external. When an individual collects data from reports and records supplied by an organization, group, or other entity, this is known as internal sourcing. Examples of internal sources include accounting information, order processing details, payroll, and shipping information. When users collect data from sources outside an organization, group, or other entity, this is known as an external sourcing. Examples of external sources include social media feeds, weather reports, government information, and research. Companies use internal and external data to scale up businesses, understand customer purchasing trends, and increase overall productivity. In this video, you learned that: Data is information like facts, observations, perceptions, numbers, characters, and images that are processed to become meaningful, for example, upper- and lower-case letters, numerals, and special characters. Data can be structured, semi-structured, or unstructured, depending on the level and rigidity of its organization. Different data sources offer different types of data; for example, data from social media can be unstructured or semi-structured. And data is essential to many organizations and is used to manage information from accounting to shipping and routing. Data is generated constantly in today’s world, 24 hours a day, seven days a week.