DATASOURCES EXPLAINED

Analytics Data: The process of examining datasets to draw conclusions about the information they contain. Data analytic techniques enable you to take raw data and uncover patterns to extract valuable insights from it..

Audio Data: A binary representation of a sound. This data can be written to a binary file using an audio file format for permanent storage much in the same way bitmap data is preserved in an image file format..

Audio Visual Data: Electronic media possessing both a sound and a visual component, such as slide-tape presentations, films, television programs, videos recording devices.

Big Data: A field that treats ways to analyse, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

Biometrics Data: Body measurements and calculations related to human characteristics. Biometrics authentication is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance.

Date Stamped Data: Similar to the Time Stamped Data but only shows the date instead of only the time or time and date.

Dark Data: Acquired through various computer network operations but not used in any manner to derive insights or for decision making. The ability of an organisation to collect data can exceed the throughput at which it can analyse the data.

Genomics Data: The Genome (The genetic material of an organism. It consists of DNA. The genome includes both the genes and the non-coding DNA, as well as mitochondrial DNA and chloroplast DNA.) and DNA data of an organism. They are used in bioinformatics for collecting, storing and processing the genomes of living things. Genomic data generally require a large amount of storage and purpose-built software to analyse.

High Dimensional Data: Data whose dimension is larger than dimensions considered in classical multivariate analysis. High-dimensional statistics relies on the theory of random vectors.

Machine Data: Information automatically generated by a computer process, application, or other mechanism without the active intervention of a human.

Marketing Data: The pool of information extracted from various touch-points and interactions between a customer and a brand. This data drives Marketing Analytics to evaluate the effectiveness of any Marketing Campaign and justify the Return on Investment (ROI) of these campaigns.

Open Data: Data which is freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control.

Operational Data: Integrate data from multiple sources for additional operations on the data, for reporting, controls and operational decision support. Unlike a production master data store, the data is not passed back to operational systems. It may be passed for further operations and to the data warehouse for reporting..

Real Time Data: Information that is delivered immediately after collection. There is no delay in the timeliness of the information provided. Real-time data is often used for navigation or tracking.

Semi Structured Data: Data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.

Spatiotemporal Data: Spatial refers to space. Temporal refers to time. Spatiotemporal, or spatial temporal, is used in data analysis when data is collected across both space and time. It describes a phenomenon in a certain location and time, for example: shipping movements across a geographic area over time. A person uses spatial-temporal reasoning to solve multi-step problems by envisioning how objects move in space and time..

Structured Data: Data created using a predefined (fixed) schema and is typically organised in a tabular format. Think of a table where each cell contains a discrete value.

Time Stamped Data: A time registered to a file, log, or notification that records when data is added, removed, modified, or transmitted.

Tracking Data: Data delivered by a combination of hardware and software, which when used together allows you to know where something is at any point in time.

Translytic Data: Enables on-demand real-time data processing and data reporting with new metrics not previously available at the point of action.

Unstructured Data: Information that either does not have a predefined data model or is not organised in a predefined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts.

Unverified Outdated Data: Data that has been collected where nobody has any idea of it’s relevance, accuracy or purpose.

Verified Outdated Data: Data that has been collected where someone has an idea of it’s relevance, accuracy or purpose.

Visual Data: Graphical representation of data. By using visual elements like charts, graphs, and maps, data visualisation tools provide an accessible way to see and understand trends, outliers, and patterns in data.

Website Data: A variety of tools on websites that collect data using both cookies and javascript libraries. Cookies are small text files that store Internet settings from the websites you visit. They are widely used to make website features work, operate more efficiently, or improve the user experience on the site. Cookies are also used to remember the user preferences or personalise the content so that it is more relevant to them. Javascript libraries are snippets of codes which run on a web-page that are executed when certain actions take place..