The field of data analytics is adorned with new and more advanced tools regularly. Some of them make an impact and others get lost in the clutter. Some tools, however, have stood the test of time and established themselves as favourites. We will talk about some such tools and how they can help you gain a strong footing in the industry. Let us start without any further ado.
R : A fan favourite among data scientists
Your ambitions might be soaring right to the top, pondering about neural networks and computer vision or it might be grounded in humble data mining, either way this good old tool has a lot to offer to you. Data scientists love R because of its no nonsense computational support. You will love it even as a beginner because of the flexibility it offers when it comes to processing data from different sources. The visualization properties are decent too. You can get a lot of work of important work done with R with very little interference.
Python : A teenage dream
I will not be surprised if Python gets a knighthood or something. It has impacted so many lives with its simple interface, easy going learning curve and immense scalability, that it might as well be called a legend. Python was created with the aim of making programming easier. It uses simple syntax, less code and has some pretty rad libraries. A great tool for the supposedly harder jobs like writing machine learning algorithms and training neural networks, Python can be used with just as much comfort for designing mobile apps, websites, and games.
SAS: Loved by the big players
SAS was once the industry leader in data analytics. It has lost some of its status due to the competitive open source tools like the two mentioned earlier. But, still there is hardly a tool more trusted and relied upon than SAS. The financial institutes love SAS for the service, security, and the discretion it provides. No wonder aspirants still flock at the SAS training institutes. In fact a SAS certificate carries a lot of weight in the industry.
Tableau : For the love of visualization
Companies insist on their employees having Tableau skills because its utility is not limited to the data analysts. More people can contribute to data interpretation and decision making with the help of the interactive dashboards provided by Tableau. The visualizations on Tableau help data analysts tell their stories faster and in a more comprehensive manner. Learn it and you will know.
Apache Spark: The speedster
The in memory analysis enabled by Apache Spark has been a great step forward towards real time data analysis. It works like charm on Hadoop and empowers enterprises with unprecedented speed. The market is ripe, it is about time you took the opportunity.
Learn these tools and whenever you hit a roadblock in your journey, remember that there is hardly anything that knowledge cannot conquer, so, keep learning.