Analytics is an exciting field which examines methods to discover and communicate some form of meaningful patterns which exist within data. This is not a particularly new area since there are rich sources of methods to record, manage and analyse data in several related fields such as computer science, statistics, computer programming and operations research to quantify performance. However, what is novel is the exponential growth in data (i.e. ‘big data’ and ‘small data’) which lends itself well to data visualisation or visual analytics. This supports us in how we communicate meaning and derives additional value from rich data sources and support decision-making. This page will summarise some of my ‘analytics research’ and share insights on the various methodologies employed.
Visual analytics is an interdisciplinary field which borrows techniques from information visualisation and and data analytics. The visual properties provide an important interface between user and machine and supports our cognitive capabilities to understand data in a more useful format. This enables us to incorporate analytic reasoning to support the sense-making process and decision-making processes.
Social Network Analysis
Social network analysis (SNA) is an approach and set of techniques which studies the exchange of resources (for example, information) among actors. SNA focuses on patterns of relations among nodes such as people, groups, organisations, or information systems. SNA demonstrates the value of ties and relationships between each node to provide a visual and mathematical representation of interaction and exchanges which influence behaviour. Managers realise that the key to continued success is within their understanding of how workflows and business processes can be optimised. SNA offers a useful technique to model a system ‘as it is’ and provide us with some truths as to how resources are exchanged and relationships are formed. This is also an interesting approach to model a Connected Health ecosystem to identify the exchange of resources and care pathways. It enables us to visualise and learn how technology can impact on the health service ecosystem and develop novel health metrics to evaluate the impact of Connected Health innovations.
Social media are computer-mediated tools that allow people to create, share or exchange information, ideas, and pictures/videos in virtual communities and networks. The power of social media has become evident in many ways to which it supports business startegies, for example, to create awarness of specific products and services. Consumers and businesses alike have something to learn from just about all of your social media interactions. How many people did your post reach? What sort of links do your followers like best? Does anything you do online even matter? Analysing the collective behaviour of online communications channels dedicated to community-based input, interaction, content-sharing and collaboration is of growing importance in many business and community spheres since it offers direct interactions with end-users.
From Data to Decisions
Exploring Data to inform Decisions is an exciting area of study. There are ample tools and techniques available to enable data-driven decisions across the various organisation to support business intelligence strategies. There are a number of key stages to gather key insights from data, transform insights into actionable information, and then make the right decisions. The power of data anaytics has given rise to ‘Big Data’. Big Data transforms describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information. The key is to understand the business problem, analyse the unstructured data, and look for insights from it to support the decision at hand. Understanding the problem to which data analytics can provide a solution is a vital skill in today’s world.