The analytics industry is a slippery zone; you never know when a technology is outsmarted by something new. However, some tools have stayed relevant longer than the others, tools that have stood the test of time through modification and relentless progress. Let us take a look at 5 such analytics tools and find out why they are so important.
- R, SAS, and Python
These three are not interchangeable; they just look good together in your CV. That is why they have been grouped.
R is a statistical language that is loved by data scientists. It is a vector-based language – fast, accurate, calculative and open source.
SAS, an acronym for Statistical Analysis Software, is one of the industry leaders in the field of advanced analytics and statistical analysis. Used and relied upon by the largest players of the industry, this tool can be your ticket to the corporate houses.
Python, the youngest and most popular of these languages has made a name in both general purpose programming and data science. It is currently huge in India; two out of ten students graduating with Python language are from India. And the demand is more than ever.
If your skill set has all three of these languages, you are definitely going places.
- 2. AI, Machine Learning and Deep Learning
AI, Machine Learning and Deep Learning are inter-related technologies wherein Machine Learning and Deep Learning is the backbone of AI. Deep Learning is a technique of machine learning that is inspired by the neural networks in our brains. Sounds intriguing right? Deep learning is taking AI and automation to new heights. As an advanced student of data science, you can enroll for a deep learning course.
Data visualization is done best on Tableau. The features in Tableau make data representation faster and easier than other tools. The thorough knowledge of Tableau can be a real lifesaver during a time crunch.
You cannot start discussing analytics without mentioning this old piece of software. It literally changed the scenario for mid-sized and small companies trying to fight it out with the big ones when the Hadoop distributed file system was introduced. HDFS lets you store and access tonnes of data on multiple servers while cutting down the cost of data storage. Other tools from the Hadoop software suit like MapReduce, Pig, Hive, HBase, have their own roles in the scheme of things.
This is perfect nomenclature exemplified; Spark is lightning fast when it comes to data processing. This tool owned by Apache has come to be a fan favorite among the analysts who leverage its speed and accuracy to manage and sort data. It can also be an efficient aide for the machine learning professionals.
Learning and mastering these tools will help you find the best opportunities in the analytics industry. If you are from India or rather South Asia, Analytics courses in Bangalore can be the perfect pathfinder for you.