Tools for Data Science
What you should learn to be a Data Analyst?
A Data analyst is someone who can interpret raw data into a story. A story which can tell performance of an entity.
There is a new fancy word popular these days call “Data Scientist”. A Scientist is someone who do experiments and analysis and comes with a result. Data Scientist or Data Analyst needs a lot of tools or operate data.
Following are the tools that one should learn and get expertise to get a nice salary job anywhere in the world –
Microsoft Excel –
Microsoft Excel is starter and widely used application to data analysis. It is best of small dataset. But this one is most advanced tool to analyse and present data. your data science start from here.
Excel Support programming in VBA, which makes it even more powerful. Excel can do a lot of complex charts which are not available in other available tools.
When excel get too much data, it doesn’t perform well, BUT!! There are some advanced features added like PowerPivot which can handle large data easily.
Microsoft Access –
Microsoft Access entirely different than the Microsoft Excel, we can build a full fledge software application. MS Access support SQL and VBA. It means we can work on large dataset and program manual analysis operations.
In MS Access, we have Tables, User Forms, Queries and Reports. When you get expertise on Access. Trust me you can do almost anything.
SQL is language which communicate with data faster than anything. It is call Structured Query Language. Almost all database system like SQL Server, Oracle support SQL.
SQL is a data language and we can only use it to read and write database. It can give specific dataset based on query and further we use that dataset in our analysis.
There are hundreds of inbuild function in SQL (Based on the DBMS we are using) we can use to analyse data.
This is an era of power BI. Power BI is reducing dashboard building and reporting time. It’s drag-drop-done technology. There is new formula language called DAX is being used to design the dataset to use further in presentation. DAX stands for Data Analysis expressions. It is like Excel Formulas and very easy to learn.
Python & R
Python doesn’t need an introduction. Python is gaining popularity and every company is hiring python developers, because it is for everything. For data science it has so many libraries that can process data quickly.
R is the language for statistical and graphical reorientation of data. R and Python.