The influx of data that businesses now experience is staggering. It is so much that even with the right analytics tools it can be hard to find the right insights or make sense of it all. This is especially true when it comes to utilizing big data. Big data is a term that was first used around 2005 when it became apparent to the business community that it was becoming possible to collect and process much more data than ever before. The three original characteristics of big data were its velocity, volume and variety.
Velocity refers to the speed at which data accumulates and must be processed in real time. It also refers to the fact that many big data environments contain a tremendous amount of data – sometimes referred to as “volume” – that is generated continuously from sources such as clickstreams, system logs and stream processing systems. The term variety describes the variety of formats in which the data is stored and analyzed. It includes structured data (such as rows and columns in spreadsheets) and unstructured data (such as free-text clinical documentation, pathology and radiology images and Google Glass videos).
Effectively using big data requires a comprehensive strategy that encompasses governance, data management, business needs, technologies, visualization techniques and other methods of delivering meaningful information to people of all skill levels. One of the most important components in this equation is a powerful, easy-to-use analytics platform. Tableau enables self-service visual analysis of governed big data, so people can ask new questions of the data and share those discoveries with others.