What’s in a name? That which we call a rose
By any other name would smell as sweet
Tell that to the folks wandering around aimlessly trying to get their head around “What the heck do all these analytics terms mean?”, and I include myself in that category.
Being slightly pedantic, I frequently have to hold myself back from getting obsessed about terminology, however in the case of analytics the surrounding language is so ambiguous, conflicting, contradicting, and confusing, that I believe it warrants an element of pedantic-ness. There is Social Analytics, Content Analytics, Social Network Analytics, Social Media Analytics, Web Analytics, Business Analytics, Business Intelligence, and God knows how many other concepts that I am not going to even consider.
So, since I am Ms. Pedantic I am going to take a stab at defining a bunch of concepts, self-coined or harvested/merged/evolved from a variety of sources. Here goes…
And I caution… these are horrendously techno-nerdy definitions :-)
Business Analytics: Refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.
Business Intelligence Traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning.
Content Analytics: Refers to the process of identifying and exploring trends, patterns, and statistically relevant facts found in various types of content. I tend to think of content analytics as the language analysis that humans don’t do well, ie. the correlating of large volumes of content to find patterns, anomolies, etc. (as opposed to text analytics, see below).
Content: Refers to the information explicitly contained within an artifact, such as a document, video, voice recording, or web page, and may comprise both structured (such as XML tags or document headers) and unstructured (such as text, voice, image, or video) information.
Network Analysis: Is the study of graphs as a representation of relations between discrete objects, with applications across logistical networks, the World Wide Web, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.
Predictive Analytics: Encompasses a variety of techniques from statistics, data mining and game theory that analyze current and historical facts to make predictions about future events.
Semantic Analysis (Knowledge Representation): A method for eliciting and representing knowledge about organizations.
Semantic Analysis (Linguistics): The process of relating syntactic structures to their language-independent meanings.
Semantic Network: A network which represents semantic relations among concepts which is often used as a form of knowledge representation. It is a graph consisting of vertices, which represent concepts, and edges.
Social Analytics: Describes the process of measuring, analyzing and interpreting the results of interactions and associations among people, concepts, and facts. Social Analytics is not content analytics although it frequently uses it.
Social Media: A broad umbrella term encompassing all content and interactions through group communication channels, such as Twitter, Facebook, Google+, …
Social Media Analytics: Descries the process of applying analytics (content, social, web, predictive, …) to social media content to inform business decisions. One of my pet peeves is when people equate “social analytics” w/ “social media analytics”. Social media analytics can be “so much more” although today it is frequently “so much less”, being in most cases simply content analysis of social media content.
Social Network Analysis: Is an instance of Network Analysis which views social relationships in terms of network theory consisting of nodes and ties (also called edges, links, or connections). Nodes are the individual actors within the networks, and ties are the relationships between the actors.
Social Network: A social structure made up of individuals (or organizations) which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange, like, dislike, etc.
Social Semantic Network: Although a social network may be considered a specific instance of a semantic network, a social semantic network (or socio-semantic network) is frequently being used to represent the merging of these two network ideas.
Text Analytics: Describes a set of linguistic, statistical, and machine learning techniques that allow text to be analyzed and information extracted. I tend to think of text analytics as what a human does well… they read a document and extract facts & concepts (as opposed to content analytics).
Triple Store: A purpose-built database optimized for the storage and retrieval of short statements called triples (subject-predicate-object), such as “Marie knows Scott” or “Marie creates Document”.
Web Analytics: The measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage.