Personal Statement Of Purpose : Kevin Huynh : Data Science

“Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses.” (SAS, 1)

Brown, B., Chiu, M., Manyika, J. (2011), Are you ready for the era of big data? Retrieved

Data are raw facts that have no meaning until they are processed and organized to identify patterns and relationships between the data elements.

Many people have become so immersed in data, that they are unable to recognize the data that they have been exposed to. For example, many college students either watch tv or listen to music while completing homework. Students often time just see this as background noise when in reality this is data that become stored in your unconscious mind. The film Big Data gives a visual account of how much data streaming has impacted society both negatively and positively through the use of data analysis. Data has taken away the ability to remain anonymous and has also sparked a decline in human interpersonal skills. However, Data also has allowed humanity to collect new information providing new solutions to world issues. The film Big Data is able to

The word "data" may seem to be facts or numbers collected for future references and analysis of a subject that is being carefully examined, but data are pretty much used in all aspects of our lives. With these important facts and statistics, we can help an individual or a company reduce a significant amount of cost. These data can help companies such as Apple realized future growth potentials and where it can better maximize its income.

In her article “The Broad Application of Data Science and Analytics: Essential Tools for the Liberal Arts Graduate,” Isabel Cárdenas-Navia talks about incorporating STEM courses into non-STEM majors and opening the option to study data science to Liberal Arts majors. Cárdenas-Navia is the director of emerging workforce programs at the Business-Higher Education Forum (BHEF), and her co-author Brian K. Fitzgerald is the chief executive officer for BHEF. In this article the authors talk about what skills are looked for in the job market today and present an intriguing argument on why data science and analytics should be open for Liberal Arts majors to study to create a more diverse field in the data science.

In my professional career, information and reports containing statistical data help draw conclusions that assist with the daily management of business. The reports are provided by analyst who are responsible for gathering the data, providing analytical analysis. The information is forwarded to my department and there it is used to help with decision making such as staffing, performance measurements and development.

The field of data analytics and business intelligence excites me because it is a field where I can learn applicable “hard,” “technical” skills that are required to execute quality work.

Considering the career plan, my immediate career goal is to work as a Data Analyst in an investment bank or Internet company. Data Analysts often need to dig the information behind the data to answer the questions of market operation to guide high-level business decision-making, precise data mining or advertising. In fact, there is also a growing number of large data need in the company's recruitment of data analyst. By learning statistics in graduate school, I believe I can process data precisely with my professional statistic knowledge. However, the same data has inconsistent content in the eyes of different people. A good data analyst is able to find the problem through the data, to position problems accurately, to find the cause of the

As coined in an article in the St. Louis Post-Dispatch by Aisha Sultan, “Data is the new world currency.” Data mining is the process of analyzing data from different perspectives and then summarizing it into useful information. In essence is it applying all different types of what if scenarios on large swaths of data to get possible results to aid in better decision making. This sort of decision making isn’t something new, it’s the technology aiding the decision making that is new. This has reduced the amount of time it takes in the decision making process and given the

Education has a new push to fully embrace data as the pivot for program delivery but there is significant danger when there is misapplication or misunderstanding regarding the value of the data. Currently, it is hard to attend an education conference or read an education magazine without encountering broad claims for data-based decision making and research-based practice - convenient buzzwords that obscure rather than clarify, to justify incoherent and glib new proposals or courses of action.

Data, Data everywhere. It is a precious thing that will last longer than the systems. In this challenging world, there is a high demand to work efficiently without risk of losing any tiny information which might be very important in future. Hence there is need to create large volumes of data which needs to be stored and explored for future analysis. I am always fascinated to know how this large amount of data is handled, stored in databases and manipulated to extract useful information. A raw data is like an unpolished diamond, its value is known only after it is polished. Similarly, the value of data is understood only after a proper meaning is brought out of it, this is known as Data Mining.

Colleges and universities use data mining and predictive analytics to methods to review student progress, courses advisement, personalize student curriculum, and create connection and networks with students. Data mining refers to the identifying relationships in large datasets (Campbell, DeBlois, & Oblinger, 2007). Data integrity is the amount of trust an institution or school has in the relevance, accuracy, and validity of the data that is being collected. Big data is classified as large data sets. A data warehouse is a centralized location for all or significant parts of the data that a systems collect. A dashboard is a computerized graphical reporting of data utilized on a computer system. The data is often times accessed by managers as a quick report on student’s status or academic performance (Campbell, DeBlois, & Oblinger, 2007). Data is used to pinpoint the variables in student outcomes.

“Information is the oil of the 21st century, and analytics is the combustion engine.” was introduced by Peter Sondergaard during Gartner Symposium/ITxpo 2011. In fact, data is like oil! It has value, but it needs to be extracted and refined to get the true value from it.

You may have heard the term “Big Data” often these days and the importance of analytics attached to it. The availability of good data set and analytics of it provide organizations ability to understand consumer behavior and future prospects. This has now become an essential part of every business operation. Data itself is not a new thing to humans, written records have been in existence since 4th millennium BC. What has changed recently is that with digital inventions and significant growth in internet access, most people are on the electronic grid for longer periods and spending lot of time on emails, messaging, entertainment and social media applications. This huge growth in data generation has given birth to the concept of