Analytics in its pure sense takes place only after efficient data mining and exploration. Since data mining is essential and a critical step, there are plenty of popular technologies available to collect and examine data. Both web and desktop applications have provided online resources for data visualization that have gained in popularity over the past few years.
First, let us understand why visualization is important. Sometimes key insights on the data may be missed if we look at it without graphical representation. Essentially data visualization in its very core allows one to understand the data better. Data Visualization tools not only allow us to assess the data but also to make it look interesting and presentable. Data Visualization also allows a quick overview of the data instead of spending hours on looking at the numbers and trying to figure out what they mean.
Some examples of where Data Visualization tools can be used are:
Today there is no dearth of data visualization tools available. To help you decide which is the best one for you, here are some of the free and popular ones that we would recommend:
1) Microstrategy provides Visual Insight, a data visualization tool. It is similar to Tableau. Microstrategy is offering their online service (Analytics Express) gratis. It works for Macs.
2) Tableau Public Software: Originally founded at Stanford University, it provides several products. The Public software allows you to use visualizations on desktop as well as on cloud.
It is widely used tool for interactive data visualization focused in business intelligence. While the other products of Tableau are not free, Tableau Public data visualization is free. It works however for public data of less than 100,000 rows. There are other visualization tools available with Tableau which have costs associated but you can get a discount if your organization is an educational institution or nonprofit.
3) R- Graphics software: R is open- source free software and provides inbuilt functionalities for graphics. However, R may need some programming skills for customised graphics. R also has the ability to handle big data which is very useful. There are high-level, medium level and trellis graphical functions that can produce an entire multipanel display in a single call.
4) SAS BI: SAS offers a BI module which is graphics friendly. Base SAS is widely used in Analytics but unfortunately not designed for visualization. SAS BI module is helpful for creating graphical representation and is also efficient in handling huge datasets.
5) Excel : Microsoft Excel is very popular and inexpensive. It is most user friendly, needs no programming skills and extensively used for reporting and data mining. Though excel also has a limit on no. of records, because of its ease, it still has huge demand.
Besides the above there are several inexpensive data visualization tools hosted by QlikView, Spotfire, Tibco, SAP, Sisense, Pentaho, Jaspersoft and IBM. To explore further visit the sites below –