ANALYTICS is the new buzz word and everyone seems to be running towards it. But most struggle to find the correct point of entry into the space. And by forcing through a wrong entry point, they generally mess up things for both parties.
Analytics space is a combination of 3 completely independent fields of study -
BUSINESS MANAGEMENT, STATISTICS, COMPUTER SCIENCE.
With this post, I want to paint a clear picture of the analytics space, its entry point and the ladder up.
I will consider the space of analytics analogous to the human body. I hope this will help us understand the analytics space much better.
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BUSINESS MANAGEMENT - This has been and will be the brain in any analogy. Business skills are the thinking centers and the control towers of the analytics space. It is the source of all the queries and questions that has fueled the need of analytics and lead to the convergence of these distinct fields of study.
But these are most "TAKEN FOR GRANTED" skills in the space, however, people must understand that it's a DATA-DRIVEN BUSINESS now. So people must understand and accept the fact that their X-X years of experience is no longer the data that can convince others.
Not to be mistaken that the XX years are no longer important, they are important.
The convergence of statistics and business is still fresh and we still require a way to validate if the statistical tools and methods are guiding us correctly or not.
People with these skill-sets report to their respective (CXOs) like the marketing guy to the Chief Marketing Officer and so on.
STATISTICS - It is the heart of the analytics space. This is probably the most direct, logical and visible set of skills in the analytics space. The industry has forced people to believe that one must be a statistician to be in the analytics space but I personally believe that this the biggest myth.
It's true, the whole data processing algorithms are results of this field of study. Statisticians are the ones who develop methods and algorithms to process data and get those strange numbers out of it. But it's also a fact that in general, it's about using the already developed algorithms efficiently rather than developing new ones. You need the best solider to use the weapons, not the blacksmith who created them.
So every person in an analytics team must have a fare bit of understanding of statistics and statistical methods and need not be a statistician.
People with these skills would generally be under the Chief Analytics Officer (CAO). This team would be responsible for using the data assets of a company and deriving actionable insights and presentable ideas. They would also have the big responsibility of breaking down the statistical results to business language.
This team is the new inclusion in the traditional organization structure, so in some companies it will have an independent identity and in some, it will be part of the traditional departments working in silos and in the absence of CAO.
The structure of the analytics team is still a debate where some suggest a central team catering to all and others suggest a department-wise teams. A third hybrid structure is also in discussion nowadays.
COMPUTER SCIENCE - These skills are the blood veins and arteries of the analytics body. I believe technology has been the ultimate enabler for this convergence.
Till now
Statisticians had algorithms. Business had some data.
Statisticians needed more data for holistic view. Business concentrated on day-to-day operations.
Statisticians needed supercomputers to process this data, Business was not capable of funding such operations.
Statisticians needed months to generate results, Business understood nothing more than seconds.
Then came the CLOUD revolution, the NoSQL & HADOOP revolt, the MOBILE uprising and the giant leap of 32-bit to 64-bit, which drastically reduced the cost and improved performance.
People of these skill-sets are needed to transform the traditional system into an analytics ready system.
People with these skills will be reporting to the traditional Chief Technology Officer (CTO) or the Chief Information Officer (CIO) or the Chief Data Officer (CDO) depending on the companies structure and industry domain. This team would be responsible for the storage, security, management of the companies data assets.
_______________________________________________
Analytics is an area of convergence, so an analytics team needs all these skill-sets to work together towards a common goal to derive the most out of it. So one needs to exhale in one or a combination (Business\Computer with Statistical Understanding) of these categories to enter the analytics space, which one... I think you alone are the most capable of answering that.
Analytics space is a combination of 3 completely independent fields of study -
BUSINESS MANAGEMENT, STATISTICS, COMPUTER SCIENCE.
With this post, I want to paint a clear picture of the analytics space, its entry point and the ladder up.
I will consider the space of analytics analogous to the human body. I hope this will help us understand the analytics space much better.
_________________________________________
BUSINESS MANAGEMENT - This has been and will be the brain in any analogy. Business skills are the thinking centers and the control towers of the analytics space. It is the source of all the queries and questions that has fueled the need of analytics and lead to the convergence of these distinct fields of study.
But these are most "TAKEN FOR GRANTED" skills in the space, however, people must understand that it's a DATA-DRIVEN BUSINESS now. So people must understand and accept the fact that their X-X years of experience is no longer the data that can convince others.
Not to be mistaken that the XX years are no longer important, they are important.
The convergence of statistics and business is still fresh and we still require a way to validate if the statistical tools and methods are guiding us correctly or not.
People with these skill-sets report to their respective (CXOs) like the marketing guy to the Chief Marketing Officer and so on.
STATISTICS - It is the heart of the analytics space. This is probably the most direct, logical and visible set of skills in the analytics space. The industry has forced people to believe that one must be a statistician to be in the analytics space but I personally believe that this the biggest myth.
It's true, the whole data processing algorithms are results of this field of study. Statisticians are the ones who develop methods and algorithms to process data and get those strange numbers out of it. But it's also a fact that in general, it's about using the already developed algorithms efficiently rather than developing new ones. You need the best solider to use the weapons, not the blacksmith who created them.
So every person in an analytics team must have a fare bit of understanding of statistics and statistical methods and need not be a statistician.
People with these skills would generally be under the Chief Analytics Officer (CAO). This team would be responsible for using the data assets of a company and deriving actionable insights and presentable ideas. They would also have the big responsibility of breaking down the statistical results to business language.
This team is the new inclusion in the traditional organization structure, so in some companies it will have an independent identity and in some, it will be part of the traditional departments working in silos and in the absence of CAO.
The structure of the analytics team is still a debate where some suggest a central team catering to all and others suggest a department-wise teams. A third hybrid structure is also in discussion nowadays.
COMPUTER SCIENCE - These skills are the blood veins and arteries of the analytics body. I believe technology has been the ultimate enabler for this convergence.
Till now
Statisticians had algorithms. Business had some data.
Statisticians needed more data for holistic view. Business concentrated on day-to-day operations.
Statisticians needed supercomputers to process this data, Business was not capable of funding such operations.
Statisticians needed months to generate results, Business understood nothing more than seconds.
Then came the CLOUD revolution, the NoSQL & HADOOP revolt, the MOBILE uprising and the giant leap of 32-bit to 64-bit, which drastically reduced the cost and improved performance.
People of these skill-sets are needed to transform the traditional system into an analytics ready system.
People with these skills will be reporting to the traditional Chief Technology Officer (CTO) or the Chief Information Officer (CIO) or the Chief Data Officer (CDO) depending on the companies structure and industry domain. This team would be responsible for the storage, security, management of the companies data assets.
_______________________________________________
Analytics is an area of convergence, so an analytics team needs all these skill-sets to work together towards a common goal to derive the most out of it. So one needs to exhale in one or a combination (Business\Computer with Statistical Understanding) of these categories to enter the analytics space, which one... I think you alone are the most capable of answering that.
