Mukesh.Kumar wrote:Question to guru's more on the career front. What are the entry options and career opportunities for mid-senior level marketing (brick and mortar) into Big Data application related fields?
Say, I am a mid-level Sales and Marketing guy who has 10+ years in a traditional durables industry, lead a team of 20 at a country level. If I were keen to make a switch into this genre, are there opportunities? What kind of reskilling is required. Is there anyone here who works in Big Data and would be open for a one on one correspondence to help me identify what options are there?
Since the Board rules do not allow me to PM, would really appreciate if someone willing to help out on this corresondence would PM me their mail id's
First lets get one thing clear - "BIG DATA DOES NOT EQUAL TO HADOOP". This is the biggest misconception among the techies that learning big data means learning Hadoop technology stack and have knowledge in a programming language like Java or Python.
Given your background in the marketing, you will be the best person to answer questions like "why do customers buy?". This is the basic question, you can develop several metrics based on the industry for which you are solving this question eg. Look to book ratio for airlines, shopping cart abandonment rates for retail ecommerce companies or lead conversion ratios for a B2B company. What is most important is finding out "what question to answer", this is where most of the so called big data technical guys go blank faced.
I am in the market hiring Datascientists for my team, the target candidate for me is someone who is well versed with data mining techniques, can create algorithms for predictive analytics, can work with large amounts data, knows how to cleanse the data, can do exploratory analysis to find out the data is good enough to be experimented, conduct the experiment (this is where hadoop comes in) and validate the results, interpret and tell the story to large audience. All this, on top the specific domain experience, in my case Marketing (B2B marketing).
Leverage your experience as you understand the buyers journey better than any software engineer out there. Be a marketer who could analyze.
Don't get me wrong, technical skills are important however that's not everything to truly become a big data expert aka a data scientist.
My suggestion would be two pronged:
1. Acquire analytical skills - based on your experience and exposure this could be the difficult to acquire and may take longest time. I would suggest start by reading a book "Data Science for Business by Foster Provost & Tom Fawcett". This book is more on how to solve business problems with various data mining techniques/ algorithms. Then there are many excellent resources including MOOCS on Coursera.com. You can look at the "The data scientist Toolbox"
this course is conducted by John Hopkins university and it is the first course of the data science specialization. If you are interested you can take all 9 courses in this specialization for free.
2. Acquire sufficient technical skills:
a) You should be able to run exploratory analytics on your own to test that the algorithms that you created will work or to see if the data can give you the kind of answers that you are looking for. There are several tools that you can learn. I suggest start with R language, Weka or KNIME analytics platform.
b) Learn about Hadoop stack/ Map reduce - This will help understand the finer details on how to size your clusters, how to load balance and optimize for cost and time it takes to run a Hadoop job. Knowing Java will help you to write a Mapreduce job that will natively run in Hadoop environment. However you can submit a hadoop job written in any language via the streaming map reduce. You can use Python, Ruby, C#, C++ or use R directly (using the rmr package on top of Hadoop).
Remember that data scientists get better salaries and generally have more opportunities than the scripting/programming persons who can only code but cannot analyze.
Hope this helps.