Python
Pandas deals with the data processing and analysis in five steps: load, prepare, manipulate, model and analyze. It is a widely used tool, particularly in data wrangling and munging. Lately I learn Python and I use this to manipulate and analyze large datasets from different resources. I realize that programming is not only for Software Development but also for Data Manipulation and Making decisions for Business improvements in the future.
SQL is an exceptional reason programming language that is utilized to interface with databases. It works by understanding and analyzing databases that include data fields in their tables. Database management is important, and when things get complex it's easy to mess up data. SQL keeps things organized and simple, protecting your database from accidental manipulation and speeding up the process of data management. It's quick, efficient, and will save your company a lot of money in the long run.
SQL
Excel
Excel for quick analysis for smaller datasets
It is commonplace for the vast majority of office workers to interact with Excel daily. With over one billion Microsoft office users worldwide, Excel has become an integral part of our working lives. This incredible platform has many uses beyond that of the traditional spreadsheet. The uses for Excel are ever growing and developing as Microsoft technologies advance. The most profitable and organized businesses across the world see the importance of Excel and its value to their company’s success.
I used tableau for Data Visualization to present data based on their stories. Tableau is used more frequently as the tool allows to analyze the data more quickly and visualizations are generated as dashboards and worksheets. Tableau enables us to make dashboards that give actionable insights and spreads the business faster. Tableau products are always operated in virtualized environments if they are configured with proper hardware and operating system. With Tableau, you can work with more unordered data and create varieties of visualizations with the help of the in-built features offering by Tableau. Moreover, you will be able to achieve great context, several ways of drilling the data and exploring the data within minutes. Tableau helps organizations in analyzing future data without any future goals in mind. You will be able to explore visualizations and observe data from different approaches. With hypothetical visualizations and a feature of adding components for comparison and analysis, you can frame ‘what-if’ queries and work on the data accordingly. The user-friendly feature is the major strength of Tableau. This feature demonstrates the ability of an individual to work without any technical or coding knowledge. Since Tableau offers most of its features in a drag-and-drop form and each visualization is built-in and self-depicting, any newbie can work without any prior set of skills. The reason behind must-add Tableau to the process by various enterprises is that data can come from any source in today’s data-driven world. This feature makes Tableau more powerful than Business Intelligence and Analytics tools. This tool allows you connecting different data sources, data warehouses, cloud files, big data, spreadsheet data, non-relational, and several other types of data. Tableau can blend every kind of data to help organizations for producing attractive visualizations. Tableau can add new data sets easily which can be automatically blended with Tableau using common fields.