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2021-2022
 
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Business Data Analytics
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Graduate Certificate in Business Data Analytics

Jobs for business intelligence analysts—employees tasked with studying and analyzing large amounts of data generated by businesses—are opening up faster than they can be filled. Corporate executives are overwhelmed with volumes of data needing analysis and summary for better decision making. Forbes listed the business intelligence analyst among its top 10 best-paying science, technology, engineering and mathematics (STEM) jobs last year. While some industries have a greater need for this role than others, the position is by no means industry-specific—it can be found in a wide variety of settings. In the business intelligence and analytics module students (1) learn core intranets: electronic data interchange, electronic banking and payment systems, security and firewalls, software agents, and the social, legal, and international issues of electronic commerce; (2)  review business intelligence and analytics technologies; (3) define and frame the business context for decisions, decision models, data issues, business intelligence, building analytics capability, cloud computing, making organizations smarter, and measuring the value of analytics; and (4) study analytics software and techniques: data preparation, data exploration and visualization, predictive analytics techniques, text analytics, and spatial analytics. 

In today's business environment, ad-hoc approaches to information systems development are not sufficient. Modern approaches to the development of information systems, such as structured systems development, relational database development, and object-oriented systems development, are required. The Business Information Systems module prepares the student to become a business information systems developer using both structured and object-oriented systems development approaches. It also prepares the student to be able to design and develop business information systems that use a relational database. In this module, the student studies the strategies and techniques for dealing with the inherent complexity in the development of information systems. System development topics include coverage of (1) business systems planning; (2) fact-finding and requirements analysis techniques; (3) information systems process modeling; (4) logical and physical design; (4) user interface design; (5) introduction to database management systems and their use in business. Database topics covered include (1) data modeling, (2) normalization, (3) SQL, (4) transaction management and concurrency control, (5) physical data organization, (6) query optimization, (7) database administration, (8) distributed databases, (9) data warehousing, (10) integrating databases with the web.
One of the core problems in the broad arena of Information Technology is the extraction of useful information from massive amounts for data that is collected and stored. Two closely related disciplines lie at the head of the problem. The first is the construction of efficient, logically organized databases that reflect the physical and organizational realities that comprise the problem domain; and the second is the extraction of useful business intelligence from those databases.  

This set of three courses in the certification in Business Data Analytics will provide students with the specialized knowledge required to attack this problem domain. 

Target Audience and Time to Complete:

The target audience is Virginia Tech graduate students who are interested in adding expertise in business data analytics to that gained in their current degree program. 

However, we also expect that a number of other professionals will pursue the certification 
both for job knowledge and career enhancement. Those students will be admitted as non-degree seeking, MIT-Commonwealth students.

In most cases time to completion will be two semesters. Degree-seeking students may take courses in conjunction with their regular course load. Students attending full-time can complete

the certificate in a minimum of one academic year and a maximum of four academic years.Degree-seeking students attending part-time can complete the certificate in approximately two academic years and a maximum of three academic years. 

Non-degree seeking, full-time students can complete the certificate in a minimum of one academic year (two semesters). Non-degree seeking, part-time students, taking one course per semester, can complete the certificate in two academic years (four semesters).

Master of Information Technology (MIT) Program

MIT Graduate Certificates
How to Apply:
Fill out the online application for participation in the certificate program.
Upon processing of the application, you will be contacted
with information about the submission of additional
required materials. Thank you for your interest.

Admissions Requirements for the Graduate Certificate in Business Data Analytics

Admission to the Graduate School and completing a Graduate Certificate Application are required for both degree- and non-degree seeking students. 

Degree-seeking applicants: The Graduate School requires completion of a bachelor’s degree from an accredited institution with a GPA of 3.0 or better for admission to Certificate Status.  Applicants with an undergraduate GPA < 3.0 may qualify for Commonwealth Campus admission. Students pursuing a degree and a certificate simultaneously are classified within their degree program.

For students interested in pursuing both the Master's degree in MIT and the certificate in Information Technology Management no more than fifty percent of certificate courses will be included toward completion of the MIT degree. 

Non-degree seeking applicants
: A qualified person who wishes to enter Virginia Tech to obtain a graduate certificate, without being enrolled in a degree program, may apply for graduate admission to Graduate Certificate by completing the certificate application

Applicants must meet the following criteria:
  • GPA of 3.0 for admission for the last half of the credits earned for the undergraduate (bachelors) degree*
  • Official transcripts must be submitted
  • Academic background meets the requirements of the admitting academic unit
  • International Applicants must submit scores from the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). A minimum TOEFL score of 550 paper-based (PBT) or 80 internet-based test (iBT) is required for consideration of the application. On the iBT, sub-scores of at least 20 on each subject test (Listening, Speaking, Reading, and Writing) are required for admission. A minimum IELTS score of 6.5 is required for admission. Some departments have higher TOEFL or IELTS score requirements than those set by the Graduate School. 
Admissions - MIT Graduate Certificates 

Course Requirements for the Graduate Certificate in Business Data Analytics

Number of Credit Hours: 

A total of nine credit hours are required. Transfer credits are not permitted. Students must maintain a minimum GPA of 3.0 in the designated courses.

Required Courses: 

BIT 5524 Introduction to Business Intelligence & Analytics: Overview of business intelligence and analytics technologies and their strategic use including defining/framing the business context for decisions, decision models, data issues, business intelligence, building analytics capability, could computing, making organizations smarter, and measuring the value of analytics. 

BIT 5534 Applied Business Intelligence and Analytics: Development of business intelligence and analytics solutions and applications to various types of decision-making problems. Analytics software preparation, data exploration and visualization, predictive analytics techniques, and text analytics, spatial analytics. Pre: BIT 5524 

ACIS 5524 Advanced Database Management Systems: Relates database theories and practices to concepts from other areas such as programming languages, algorithms, data structures, and information systems. The relational, network, and hierarchical models are introduced. A major portion of the course deals with data manipulation languages for the relational model, design theory for relational databases, and query optimization. Pre: ACIS 5504