How you ever felt the need to understand the difference between analysis and analytics (of data)? If you have and want to know the answer, you will find it in this article. I will also try to explain the utility of various tools that analysis and analytics need.
Analysis is the art of segregating and structuring information to understand what happened. It necessarily reproduces existing data in different ways. Analytics will use this information to attempt predict what may happen. The purpose of the two could be very different. It should not be confused with descriptive and inferential statistics.
Imagine that you graduated from school. You scored GPA of 3.5 or you scored 90%. What you scored in individual subjects, even individual tests is breaking down of the information. This process is analysis. If your score in mathematics and physics were highest, it may be predicted that you will do well in related subjects in future. This process is analytics.
Data manipulation and extraction
In most of the situations, the analysis and analytics is based on data. The volume and storage format of data makes it necessary for us to use different tools. The data may be stored in a database. Sometimes the data may be downloadable in several ways and formats. Moreover there may be need to download data in a specific format which is different from the way it is stored. This process is called manipulation of data. The extraction and manipulation of data from database is using tools like My-SQL. Extraction of data is not analysis or analytics. It merely provides the raw material.
Tools for analytics and analysis
Once the data is available or accessible, analysis and analytics can be done using Spreadsheet (with or without add-ons), Statistical softwares (R/Python/SPSS), Mathematical softwares (Matlab) etc. All of these are capable to handle both analysis and analytics. Spreadsheets have limitations on the amount of data it can handle. It is comparatively easier to use than the other tools.
Tools for Graphical representation
Graphical representation of data is an important aspect of analysis and analytics. It not only helps the analyst but also makes it easier for the audience to understand. Typically, management will not have time to go through all the details of the analysis. However, as the saying goes, a picture says a thousand words.
The tools mentioned above are more than capable to represent data in desired graphical format. However, there are tools available that are capable to create dynamic visualisations from live data. Softwares like Tableau, Periscope, PowerBI does this. These softwares are capable to manipulate and extract data and also create visualisation from the same.
The mentioned (and non-mentioned) tools are being updated regularly and are increasingly becoming capable to handle all tasks starting from manipulation, extraction, analysis, analytics and visualisation.