IBM is more than 100
year old company and pioneer in computation tech domain. We feel that in a
world, where there is growing demand for skilled IT professionals, the key to
transforming today's students into tomorrow's working professionals is to develop industry capabilities
right from foundation level. To this effect, the Career Education of IBM (under
Software Group) has caused revolutionary changes in academia, rapidly building
industry-relevant software capabilities that organizations need today and tomorrow.
Do you love technology, and have good business
acumen too? I would love to tell you that I have a career-booster for you- Bigdata & Hadoop Training program.
Hadoop In Great Demand!
Did you know voting advertisements like Abki baar- Modi Sarkar were made
by analyzing public interests through social media. Amazon is making pricing
decisions, by using data-driven
statistics. How do they do it? They track your data and your
behavior to reach to conclusions and make business decisions. What you want,
which deal will suit you best, what will motivate you to take actions, are all
the decisions playing in the mind of an Analytical professional. As you guessed it right, they are in HUGE demand. Not only that,
financial services, utilities, media, retail, energy and pharmaceuticals, all
are hiring Analytics Professionals, certified in Hadoop.
Hot Jobs:
Since Analytics is utilized in varied fields, there are numerous job
titles for one to choose from: Like Big Data Scientists, Big Data Analyst, Big Data Solutions
Architecture, Big Data Engineer & BigData Researcher.
Salary:
Most analytical companies pay candidates a modest 4-7lakhs per
annum at the entry level.
WHO SHOULD DO THIS COURSE?
· Software
Engineers, who are into ETL/Programming and exploring for great job opportunities
in hadoop.Any Graduate/Post-Graduate, who is aspiring a great career towards
the cutting edge technologies in IT.
· Managers, who
are looking for the latest technologies to be implemented in their
organization, to meet the current & upcoming challenges of data management.
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