If you have been following anything related to tech, you would definitely know by now that Big Data has been the key term for the last couple of years. The importance of data analytics has blown up considerably, and it is being used by most of the organizations in the world either to derive business insights or to create an analytics product that will improve the value they provide to customers.
Why is Tableau Important in the Field of Big Data
Analytics?
However, Tableau is currently one of the most adopted data visualization tools in the world, and it is so popular because of how easy to use yet powerful it is. This means that more organizations are now searching for people who are proficient in Tableau since it can make a huge difference in the amount of value they derive from the data.
Some of the reasons why Tableau is so important in the current scenario are given below.
Competitive Dynamics
The market today is extremely competitive – you will need to adapt to changing situations and respond to the needs of the customer in order to survive in this scenario. Therefore, now more than ever, organizations need a tool which can be flexible enough to handle a variety of projects, but also useful enough to be read with ease by customers.
Tableau visualizations simplify the process of data analysis, and removes any distracting complications which are common in many other softwares– it focuses only on what creates value, and that is projected with clarity. Quick deployment and complex analyses are supported by the website, meaning that it is one of the most useful tools that an organization can have.
In-Memory Technology
The software uses in-memory technology, which means that it functions using the memory of the system to work quickly. Business Intelligence processes are therefore made comparatively easy, with the help of Tableau. Clients are now able to interact with their GUI and make changes in the way they see the data, without any external help from an IT professional.
Models and functions
Tableau is extremely cross-functional, too. Even though it can carry out basic calculations and some simple statistical processes, it can also work well with R. If you are ever in need of some heavy artillery when it comes to data analysis, you can always bank on R to carry them out, and then import the data model over to Tableau.
Tableau makes it easy to add new data sets, whether it be from an excel sheet, a flat file or any other kind of database. This means that users can obtain multiple ways to uncover value in the data, and consequently use it to their own accord!
If you are interested in making a mark as a data scientist or simply need a tool to visualize data, leaning Tableau would be the best choice for you. Acadguild offers many courses in data analytics and Tableau which are sure to help you to that effect.
