by kerrywatson on April 10th Joe Montana Jersey , 2018
Since you are reading this we may suppose that you have already given a career in analytics ample thought. So it should not be necessary for us to engage in too many words about why you should take up analytics; though not enough can be said about the same. We shall rather delve into the ‘how’ part of it.
Analytics is not just one stream
It is in fact a multi-faceted discipline where you can opt to specialize in any tool or technique you choose.
Now, if you are from a computer science background programming should be your cup of tea. In that case you can learn a language like Python or R and then learn the features which can help you design analytical models. With the basics of computer science already in your grasp, getting started into a career in analytics should not be much of a problem for you.
If you are not from programming background, but from some other quantitative field Reuben Foster Jersey , analytics can still be your path of career. You will just need a head start into programming with some additional basic support. Post foundation training on less programming-oriented tools like Excel, SAS learning advanced tools and statistical models should be rather easier for you.
Training cannot be skipped
Anyhow a certain amount of training and proper guidance is a necessity. You can tell that there is a large amount of free material on the web regarding data analytics. Then I can tell you that there are a lot of companies which have run aground due to analytical mishaps. I am not trying to indicate a relation between the two, but it is just advisable that you undergo training before jumping into the industry which has, by the way Jaquiski Tartt Jersey , grown deep enough to gulp you down completely.
What's suitable for you?
If you are having a hard time deciding upon how to approach analytics training, let the counselors do the job for you. You should just have a very clear understanding of what you already know and what you would love to do as a professional. The career counseling which is often provided for free by some institutes of data analytics training in Bangalore.
The only thing that you should be very cautious about is whether the technology you are learning is relevant in the industry currently or not.
For instance if you want to explore your chances as a data science professionals and want to add a language to your repertoire you may be given options between SAS, Python and R. Your logical choice should be R or Python as it gives you more flexibility and takes least of your time to be mastered. At the other hand if you are targeting a specific company and it uses SAS, it is probably wise for you to learn SAS.
Make sure that the course has ample opportunity of industry exposure and your instructors are connected to