Tools Of the Trade for Big Data Analyst (Nov 27th)

 When it comes to Big Data we must use a specific set of tools in order to complete the job properly. most of the tools of the trade are software and hardware. One of the biggest software tools to use while trying to analyze data is Tableau. Tableau is the best at visualizing data. Tableau allows us to explore without having the interruption of the flow of data when analyzing.  Another benefit of using Tableau for any data analyst is the ability of Tableau using AI which will allow a faster and predicts outcomes much faster using CRM. CRM which is a branch of Tableau allows many sales associates to make the correct decision which allows us to work more efficiently. With this efficiency, we can ten to spot trends faster, predict outcomes. The AI feature usually allows us to have the guidance we desperately need so we do not make any mistakes because as humans we are not perfect and can make mistakes and dumb ones at that. In my research, I decided to go down the rabbit hole of information for Tableau CRM it allows many data scientists to unify platforms, focus on outcomes, automate discovery, unify multiple platforms into one and build a different database with just a simple push of a button. Like many different software programs, they all have their pros and cons. A similar software program is SAS visual analytics. This kind of software is most helpful with and sharing and analyzing data as well as presenting the data in clean and formal nature. The main function of this specific software is to allow companies in need of powerful software that will be to tie pieces of data together to have them in one file in order to showcase at a large event. In many ways, I would consider this software to be like Microsoft excel and word in one program where you are able to show different analyses in one meeting to make sure different departments understand how they all work together as a set of gears. With that being said there are multiple pros and cons to SAS one of them being it allows us to have a large number of users under one simulation. in the sense we could have multiple presentations all linked into one where SAS will take the data that you have selected and put it under one easy to read module instead of having to sift through many different simulations.  The second pro about SAS is it allows you to have a customizable portfolio that splits up the business into different aspects so you're allowed to divide a business. For example, we can take a car dealership where we allow to have sales, parts, and service department. So in retrospect, we need to see how much this car dealership makes in revenue. And in order to calculate that we need to divide it into sections while when showing the Ceo or sales team we need software that merges everything into one which is where SAS comes into play.