With science which provides a new paradigm to tackle

With large amounts of data available, organizations in most of the industries are now focused on exploiting data for competitive advantage. Additionally, the broad availability of data has led to increasing interest in new methods for extracting beneficial information and knowledge from data. I am amazed by what today’s large volume of data and cutting-edge technology could achieve, helping individual or organization to make wise decisions, and improving and optimizing the existing process in an unprecedented way. Analyzing the current statistics of exponentially increasing data, information flare has started becoming a pressing concern and recent studies uphold that the amount of digital information would increase tenfold every five years, which seems reasonable, considering 1.2 million new data-producing social media users each day. Hence, the only way to realize the value of this deluge of data is Data science which provides a new paradigm to tackle these vast accumulations of data.

In fact, data-driven analysis has been also widely used in security, healthcare, business, agriculture, transport, education, prediction, telecommunication and every possible industry where data gets generated. As one might imagine, the use of data science will become more ubiquitous. Due to such diverse scope to leverage our lives through Data Science is one of the many reasons for my curiosity to study more about it and would be a logical culmination of my passion for solving such problems through data analytics. My penchant for analytics was evident right from high school and before long during my undergraduate studies, I was exposed to courses like Numerical Techniques, Logic design, Probability-Random Processes and Computer Architecture, Organization & Algorithms, where I developed an interest in programming in liaison with mathematical and statistical logic.

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Progressing towards my final year BE project, where I chose to work on an idea ‘CMOS Camera to Embedded Image Processing’ which enabled utilization of a CMOS Camera to wirelessly transmit a bitmap image and induce FPGA image processing algorithms using C#. After instituting a firm foundation through my academic digest, it was time to dive in the data-centered economy, where I procured professional experience at Accenture and Deloitte. I have over 7 years of experience and currently positioned as Senior Consultant at Deloitte Consulting in their Analytics and Information Management service line. I have extensive experience in building enterprise-wide data strategy roadmap, designing and implementing complex business technology solutions in Analytics and Data Warehousing and Decision Support Systems in Financial Services Industry along with broad functional expertise in Insurance, Credit Card, and Banking, Investments, and Loan Servicing industry.

Through my career in consulting with Deloitte and Accenture I have had the opportunity to lead, architecting, and implement large scale Finance Transformation Data Warehouse initiatives across industries for Fortune 500 clients, where I have lead data analytics, integration, conversion, upgrade and migration initiatives to enable data integration capabilities to create a foundation system of record for reporting and analytics with scalability and flexibility to support the changing business. The end to end implementations involved leading the core Data Integration Hub solution architecture with a scalable and re-usable generic business rule engine, Audit and Reconciliation and Exception and Error components with integration to Master Data Management and Data Governance capabilities.  My experience and focus area have been data integration; master data management; data governance; data modeling with various case tools; developing multi-dimensional data warehouses; enterprise reporting – static, ad-hoc and analytics. Using the above experience and skillsets, I have been able to make strong client impacts by leading implementation of next generation Data Architecture to help design and implement scalable, source system agnostic and harmonized Data Integrated OLTP/OLAP systems and Business Transformation Hubs using various Data modeling, Data integration (ETL), Relational – Row & Column DBMS and enterprise reporting tools.Altogether, being professionally acquainted with elementary concepts of Data Science, I wish to pursue my Master’s in Data Science at Illinois Institute of technology, as it supplies a program with an emphasis on Scientific Approach and Practical experience.

The curriculum provides a proper unification of both technical and computational courses like Machine learning, Data-Intensive Computing and Cloud Computing which will refine my current capability. The relevance of the program to my specific interest with strong industry opportunities at Chicago, remarkable faculty and a strong emphasis on research will aid me in realizing my potential to the fullest. Along with technical expertise, it will provide me with cohort experience and ability to think about real problems which are conducive to my development as a professional.