Dear Sir,
In my point of view, most traditional visualization approaches are used to create maps, tables, charts...from static data which is pre-calculated and stored in the database server (MySQL, SQL Server, ..). If the request is related to a static visualization, it will query data on the database server and show the result immediately in a fixed form. However, in some cases, we may want to visualize data which is updating in a real-time manner and the form for showing data is customizable. Moreover, users may want to make a data visualization by themselves without some fixed tables or charts which are provided before... Therefore, we have to think about dynamic visualization analytics techniques. For that, we might need to solve some challenges of dynamic visualization including perceptual scalability, real-time scalability, and interactive scalability.
For an instance, we can develop a web interface to help users to make queries (SQL query, Hive query,..) by themselves to obtain and visualize the data what they want. I have designed and implemented a platform like that.
Conference Paper Big Data Analytics and Visualization Techniques: A Case Stud...
In addition, in big data domain, we might need to consider some techniques related to real-time data collecting (Spark Streaming, Flume, Kafka,..), big data processing (Spark, Hadoop/MapReduce), big data visualization (Zeppelin, ..).
Best,
Van-Quyet Nguyen
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