Data Analytics is big field which has two main categories of Data Analysis and Data Reporting. Data Analysis is putting the data and get the answers through Data Reporting. In short we can say Data Reporting provides data and Data Analysis gives the answers for the questions. Data Analytics is basically it start from slicing and dicing of the data and in advance it is lead to take decision of predicting the trend etc..,
There are so many software tools; software’s are used in real time Data Analytics
Tools are using for Analytics.
Microsoft Excel, SPSS, SAS and R Studio – GUI Based Tools
Tableau, micro strategy – visualizing
SAS and R code based tools – They are the leaders
The 36 best tools for data visualization
Why visualizing software role is critical in Data Analytics.
A picture is worth a thousand words. Mass data trend or patterns are representing by an image or graph it is easy to correlate and visualizing is help to taking the decision faster.
R Vs SAS
R and SAS are leading Data Analytics tools. R is open source and object oriented design. It has huge advantages of thousands of packages for extensibility. However it has demerit of scalability. It runs on machine memory. If needs to run huge data the proposed memory needs to be used in the machine otherwise it won’t handle that huge data sets.
SAS is the leader in Analytics tools. It is paid tool. The decision trees are done by SAS miner which is very expensive. However R does not offer many tree algorithms. SAS does not have memory issues like R and it is more flexible it can handle any amount of huge data. SAS has extensive documentation is another big advantage. R is open source and it has quite same extensive documentation like SAS. In market SAS has keep it strong position and the new data analytics projects are prefer to use R. Most of the current projects which are run by SAS are migrating to R to save the cost. Mix of the projects is run by both. In nutshell for job market R and SAS skills are highly demand in the current market.