Placement Scenario in Analytics

Analytics, as the name itself suggests, is the phenomenon of analyzing data through the use of strong techniques and tools for various business decision. Today, with the advancement in technology and so many statistical tools at businesses disposal, analytics has made its way into social media, HR, gaming, and e-commerce as well. Analytics has become the most common and an integral part of industries across which included KPOs, BPOs, IT, BFSI, Finance, consultants as well. This is the reason why the analytics industry in India has soared significantly in the recent years and aspirants now have a wide scope. India already has more than one lac professionals in this field, working for various businesses.

In India today, you will find anywhere between 500 to 800 analysts from 10,000 employees. With the increase in the demand, the salary associated with this job field is also increasing at a fast pace. Currently KPOs are one of the industries hiring maximum number of employees in Analytics domain with offering Rs 5 Lac to a fresher and then the level goes increasing. Depending on the experience, there are four levels of jobs:

– Entry-level: 0-2 years of experience

– Mid-level: 2-5 years of experience

– Senior management level: 5-10 years of experience

– Director level: Over 10 years of experience

 

 

Business consulting firms are the best pay masters in this segment and offers somewhere between 8L to 12 to freshers.

 

The size of the analytics market in India is worth a whopping $375 million. This number is expected to increase drastically to $1.15 billion according to recent reports. Presently, there are over 500 companies operating in this industry in India.

Analytics gives the individual the opportunity to get into various different departments across sectors with the same skills and technology. The flexibility to work in different sectors and domains is something that appeals to many aspirants.

Analytics jobs are of various types including data analytics, web analytics, marketing analytics, system analytics, analytics consultant, financial analytics, investment analytics, business analytics, HR Analytics and so on. This, again, proves the point that those interested in the field of analytics have a lot of scope and demand in various industries with highest number of roles offered.

 

 

 

MBA Vs. Business Analytics

“Every two days now we create as much information as we did from the dawn of civilization up until 2003” – Eric Schmidt (Executive Chairman, Google), Techonomy Conference – 2010

The turn of the millennium saw a paradigm shift in the engine of growth, sustenance and innovation. The advancements in computing systems, electronics and social media have transformed how decisions are taken in running a business. Information readily available over the internet has provided businesses with immense insights into consumer behavior and needs. A seemingly innocuous “like”, “tweet” or a “click” on a link becomes a binary code in a database that companies employ to provide targeted marketing, personalized services and better goods for the consumers.

The implications of the availability of data is however not limited to only industries such as retail, consumer goods and advertising but also in telecommunication – to improve services and customer experience, financial services – in identifying stock trends, healthcare – in formulation of drugs, security systems – in identifying crime prone areas, automotive – in developing robust mechanical systems, governments and energy – in developing smarter electricity grids among others. Moreover, the efficiency brought in and the financial implication of timely and correct interpretation of data is estimated to improve the operating margins of companies by around 25 per cent and it is increasingly turning out to be the chief differentiator between organizations.

We are currently in the zettabyte era (approx. 1012 GB) a full 90 per cent of which has been created over the last two years. It is an immense challenge faced by organizations to sift through these enormous volumes of data to identify and exploit meaningful relationships between seemingly uncorrelated data points. It is the role of a data scientist to filter the noise and identify these useful relationships to aid the organization in its daily and strategic decision making. The exponential increase in availability of data and dearth of qualified professionals to assimilate, scrutinize and derive meaning from this data has created an opportunity like never before.

[cs_column column_size=”1/2″ flex_column_section_title=”Main challenges with big data projects”][cs_progressbars column_size=”1/1″ cs_progressbars_style=”strip-progressbar”][progressbar_item progressbars_title=”Security” progressbars_percentage=”51″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Budget” progressbars_percentage=”47″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Lack of talent to implement big data” progressbars_percentage=”41″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Lack of talent to run big data and analytics on an ongoing basis” progressbars_percentage=”37″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Integration with existing systems” progressbars_percentage=”35″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Procurement limitations on big data vendors” progressbars_percentage=”33″ progressbars_color=”#1e73be”] [/progressbar_item][progressbar_item progressbars_title=”Enterprise not ready for big data” progressbars_percentage=”27″ progressbars_color=”#1e73be”] [/progressbar_item] [/cs_progressbars][/cs_column][cs_column column_size=”1/2″]

McKinsey Global Institute has estimated that there will be only 140000 to 190000 professionals with deep analytical skills to fill the demand of Big Data jobs in US by 2018. Further, survey conducted by EMC – a leading US based data management corporation, had 31 per cent of respondents reply that over the next 5 years demand for data scientists will significantly outpace the supply. Additionally a survey conducted by Accenture of IT leaders regarding challenges of big data projects pegged lack of talent to implement big data projects as their third highest concern.

Major Information Technology companies in India have already identified the opportunity to offer these services and have begun building capacities for such an eventuality. The lack of professionals with the requisite qualifications has pushed up demand and subsequently the salaries.

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[cs_column column_size=”1/2″]For perspective, a recent survey has pegged the average salary for an MBA graduate to be around 300 thousand per annum however a data scientist is estimated to earn a salary upward of 600 thousand per annum. A further analysis of MBA salaries across the popular domains of Finance and Marketing shows startling results that are tabulated below.[/cs_column][cs_column column_size=”1/2″][cs_image column_size=”1/1″ image_style=”plain” cs_image_url=”http://www.datapanaceaonline.com/wp-content/uploads/2014/09/Salary-1.png” cs_image_url1=”Browse”]Source: Payscale.com[/cs_image][/cs_column]

 

Entry level data scientists with skills that include SAS, SQL, and R could potentially earn as much as 2 times as much as a financial analyst with an MBA, the second highest paying entry level job in the peer set used for comparison.

An analysis of the incremental salaries over the career graph of a data scientist, an MBA in marketing and an MBA in finance shows that a data scientist earns substantially higher than her/his peers through the course of their exciting careers.

[cs_column column_size=”1/2″][cs_image column_size=”1/1″ image_style=”plain” cs_image_url=”http://www.datapanaceaonline.com/wp-content/uploads/2014/09/salary-2.png” cs_image_url1=”Browse”]Source: Multiple – Analytics India Magazine and payscale.com [/cs_image][/cs_column][cs_column column_size=”1/2″]Comparing the salary that an entry level MBA receives with that of the cost of an MBA degree, which averages around 6.00 to 9.00 lakhs from a Tier-II B-School and 12.00 to 15.00 lakhs from a Tier-I B-School, the returns on investment is abysmally low on an average and completely unjustified.[/cs_column]

Contrast that with a degree in data analytics the returns are far more substantial. Moreover, the skills developed during this course of Business Analytics, offered by Data Panacea, transcends industry constraints and domain expertise to open a plethora of opportunities for you.

With our robust course curriculum, superior teaching methods and experienced instructors we at Data Panacea would like to help you in developing the skills sets for a professionally fulfilling career as a data scientist and help you ride the wave into the Information Age.