Читать книгу Tableau Your Data! - Murray Daniel G. - Страница 8

Data graphics should draw the view’s attention to the sense and substance of the data, not to something else.

– Edward R. Tufte1

The seeds for Tableau were planted in the early 1970s when IBM invented Structured Query Language (SQL) and later in 1981 when the spreadsheet became the killer application of the personal computer. Data creation and analysis fundamentally changed for the better. Our ability to create and store data increased exponentially.

The business intelligence (BI) industry was created with this wave, each vendor providing a product “stack” based on some variant of SQL. The pioneering companies invented foundational technologies and developed sound methods for collecting and storing data. Recently, a new generation of NoSQL2 (Not Only SQL) databases are enabling web properties like Facebook to mine massive, multi-petabyte3 data streams.

Deploying these systems can take years. Data today resides in many different databases and may also need to be collected from external sources. The traditional leaders in the BI industry have created reporting tools that focus on rendering data from their proprietary products. Performing analysis and building reports with these tools require technical expertise and time. The people with the technical chops to master them are product specialists who don’t always know the best way to present the information.

The scale, velocity, and scope of data today demand reporting tools that deploy quickly. They must be suitable for non-technical users to master. They should connect to a wide variety of data sources. And, the tools need to guide us to use the best techniques known for rendering the data into information.