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5 analytics tools that never fail to make the list

Big data analytics is the big game now. It is not a fancy buzz that gets lost in the incoming clamour. It is a multi billion dollar industry that is getting bigger with every breath. No wonder there have been, are and will be a ton of different tools to help you collect, sort, clean, and make sense out of your data. However, these five tools have never really left the list of top analytics tools. Your career in the analytics industry rides on your knowledge of these tools. Even if you do not use them for your day to day analytics work, these will help you land your first job.

The journey of any analytical query starts with a few simple questions. In the case of an online business there are questions like how often does a person A visit your website? How did A know about your website? Are there others like A who are looking for the same thing? What are they searching for? How old are they? Where do they come from? What will they look for in the next quarter. If we look at these questions, we will see that we are just trying to peep into what has happened and trying to assume what might happen, at a larger scale. These answers areĀ  easier to find if compared to questions like what should our strategy be if we want to convert A into a loyal customer? These questions are the bed rocks of data analytics. Your preparation starts with understanding the significance of these.

You need to develop an acute understanding of the factors that work like the wheels under the business you are serving. For instance, if you are working for an e-commerce company your business thrives on the understanding of consumer behaviour at different places and times. Your analytics efforts should comply with these. The tools are not the hero. You are. If you know your business from insight out, it will help you decide on which data scource to focus on and which one to keep on a low priority.

Process automation has become a huge part of business process management. Under the current circumstances, your success and sustenance as a data analytics professional depend on your ability to work in tandem with automation programm and to monitor and control the same. Choose your big data courses according to these plans and make sure you do not fall behind. The machines will not take your job but someone with a better understanding of process automation might.


Alright, we all know this. Do we know this well enough? Do you think MS Excel can be used as an elementary tool for data analysis for a few thousand lines of data? No? Then you should probably think again. There is a reason why this old tool has had the chance to get so old without becoming obsolete. The new features on Excel are handcrafted for elementary data analytics. The pivot tables and filters can reveal a bunch of insights. With a moderate learning curve and global acceptance this tool will keep making the list.


If statistical analysis is your thing, R is your guy. There is a tone of unanimity among large groups of data scientists regarding the appropriateness of R for computational work. It is an incredibly flexible tool which lets you load and process data from a wide range of different platforms.


An analyst needs to tell stories. You need to turn information into insights and Tableau is your best ally in the process. It turns your findings into interesting visualizations. Images and tables that speak more than hundred pages filled with numbers. It just makes life much easier for analysts. It has a pretty flat learning path. But do not live under the impression that you do not need to learn it well. The more you know the more value you can extract.


This is another reliable tool for statistical analysis and other analytics related tasks that has been in the scene for ages. This is not a free open source tool and makes the clients bleed money if you ask them. But they do not become irrelevant or obsolete because of their impeccable service record, maintenance and security. Consequently SAS training in Malaysia is quite popular despite the decreasing popularity of the tool itself among youngsters.     


The popularity of this tool tells more than I can. It has topped pretty much all charts listing data science tools or general-purpose programming tools. Python is designed for simplicity, efficiency, and power. A lot of vital programs around the world are riding on Python. No wonder Malaysian aspirants are flocking for Python training.

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