Traditional university level tracks to careers in Data Management have pertained to Computer Science, Information Management, and Computer Engineering. The majority of these programs pertain to either analytics (Business Intelligence and business analysis) or Data Science. Regardless of the particular area of specialty, these programs are teaching college graduates to utilize one of the most vital technologies in the Data Management landscape. For example, the Northwestern College in Iowa’s Analytics certificate program is offered through its Adult and Graduate Studies Division, and provides the basics in text and predictive analytics. An increasing number of accredited educational institutions are now offering undergraduate programs in Data Science. The majority of educational opportunities in Data Science revolve around master’s degrees in this subject.
Some of the more competitive programs offer an inter-disciplinary approach wherein students are able to take classes from different divisions of the university in order to meet their needs for specialization after fulfilling core requirements.
Options for a Masters in Analytics are generally categorized as those pertaining to business analytics or those pertaining to analytics in general or some other aspect of specialization in this field. The plethora of options for training in Big Data and Data Management in general attests to the increasing democratization of these technologies. The clinical data management plays a key role in the setup and conduct of a clinical trial. The data management team creates an accurate electronic database that captures the clinical data in accordance with the study protocol. Our bi - weekly Newsletter about biotechnology, bioinformatics and clinical research news, up - coming events. First of all I want to thank you sincerely for being here and I hope this will be useful to you. Enter your email address to subscribe to this blog and receive notifications of new posts by email. However, the growing prominence of Big Data in operations and analytics has resulted in an increasing number of collegiate programs expressly designed to account for Big Data.
Their principle distinction from formal degree courses is their relative brevity; whereas the former may require upwards of 60 or 70 credits, the latter generally requires less than 20.
The University of Maryland University College has a Foundations in Business Analytics certification program in which candidates must meet the same academic requirements that apply to its Masters of Science in Data Analytics. Such programs enable students to specialize in studies pertaining to this field in addition to completing core academic subjects.

These programs provide an even greater degree of specialization than bachelor’s degree programs do, and detail the intricacies of technologies such as Neural Networks, Deep Learning, and the most advanced forms of analytics. Such options, including those for summative assessments and practicums, help to categorize more notable programs from lesser ones. The former are oftentimes more interdisciplinary than the latter, which tend to focus more on business schools.
Each successive wave of programs and their graduates helps to make data-driven processes that much more accessible to an ever diversifying number of business analysts, Data Scientists, architects, and end users, even.
The data collected during a clinical trial forms the basis of subsequent safety and efficacy analysis which in turn drive decision making on product development in the pharmaceutical industry.
The data are cleaned according to the specifications contained in the data validation manual.
Subsequently, the area of concentration of certification programs is narrower and less focused on business applications and more on elements of computer science. Those requirements include a bachelor’s degree and choices of previous professional certification, a requisite score on a graduate school exam, or additional graduate level coursework. There is a great degree of variation in program length, with some full-time programs taking less than a year. This fact becomes particularly poignant when one considers that one of the chief characteristics of a Data Scientist is his or her cognizance of any multitude of domains and academic disciplines. Perhaps it is because of that fact that business analytics programs might be more expensive than their counterparts.
Moreover, the wide range in options for formal academic training in these facets of Data Management underscores the broadening body of use cases for data across vertical industries. The final deliverable is sending a final clean database to the client or biostatistics and programming group for statistical analysis and final study report. Oftentimes, such programs are available in a part-time capacity and through distance education opportunities, since they are targeted towards professionals. Depending on a student’s enrollment status (part-time or full-time), some programs can span the better part of two years. Program requirements frequently include a bachelor’s degree in a subject related to statistics and math; additional coursework can include subjects such as ethics and aspects of Data Modeling. Programs in business analytics tend to offer a variety of options for areas of focus in business that supplements basic requirements in computer science, analytics, and statistics. Not only is it easier for high school and college graduates to attain the necessary training to pursue careers in Data Management and Big Data, but it is also easier for established professionals to do the same to formalize their mastery of some of the more recent developments in this discipline.

Data Science programs tend to encompass various aspects of analytics such as Machine Learning and predictive and prescriptive analytics, whereas some BI programs detail various aspects of algorithm development and database systems that is vital to Data Science. As such, these programs are frequently offered through continuing education departments at colleges and universities.
Other varieties of post-undergraduate degrees in analytics feature combinations of concentrations in data analytics, formal BI, and Data Management.
Part-time options for master’s degree programs augmented by distance learning opportunities are equally as viable as abbreviated certificate programs—some of which are also accessible online.
The interrelation between these disciplines is denoted by the Institute for Advanced Analytics in the fact that, “Since 2013, degrees in Data Science have emerged as a close kin to M.S. Most undergraduate programs in Data Science involve elements of computer science, math, and statistics. The former tend to be involved in the science departments whereas the latter are involved in business schools.
Additionally, the vast majority of programs enable students to choose different tracks of specialization. The University of San Francisco’s undergraduate major in this subject offers students areas of concentration in economics, math, and computer science. Core classes consist of database systems, visualizations, and data mining, while students have a host of electives in subjects as varied as Natural Language Processing, network security, Artificial Intelligence, and facets of algorithms such as computational topology.
The degree of specification such programs provides can help students to prepare for vertical industries. This type of framework—an offering of core courses related to the degree programs and optional electives for areas of specialization—is typical of all degree programs and simply requires research on the part of students to see which ones are best suited to their needs. The College of Charleston’s Bachelor of Science in Data Science lets students select between 13 “cognates” from biomechanics to marketing, geology to physics, thereby ensuring the scientific aspect of this discipline.  Core requirements in most bachelors’ programs include calculus, data mining, and Data Visualization, among other subjects.
Frequently, capstone projects or some other summative assessment is required for graduation.

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