Master of Science in Data Architecture and Management

学历文凭
Masters Degree

专业院系
数据库管理

开学时间

课程时长

课程学费

国际学生入学条件
A bachelors degree or equivalent from an accredited college or university.
To submit and complete your application you must upload a PDF file of your unofficial transcript directly to your online application Unofficial transcripts must be in English.
Please ensure that the scanned documents are readable and include all courses grades ie marks scores etc and credits completed to date The scanned documents should also include information about the institutions grading scale If admitted you will need to provide your official transcript For a transcript to be official it must be in a sealed envelope from the transferring college or university.
Other Documents -
Statement of purpose - 500 words minimum.
Letters of recommendation 2 or 3 for graduate programs.
Curriculum vitae CV Resume.
TOEFL 79, IELTS 6.5, GPA - 3.0
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CRICOS代码:
申请截止日期:请 与IDP联系 以获取详细信息。
课程简介
The Master of Science in Data Architecture and Management addresses crucial activities, including data preparation, data curation, application integration, and data engineering based on the combination of use cases and integration persona.<br>Potential career paths: Engineering, Operations, Business Development, Project management<br>If you want to earn your master’s in Data Architecture and Management at Northeastern, Global Pathways can help you succeed through rigorous language training, cultural activities, and support.<br>The Master of Science, MS, in Data Architecture and Management degree at Northeastern University is designed to prepare you for the evolving and growing field needing data engineers. You will gain the holistic knowledge and technical skill to engineer big data systems, curate data, and integrate and process data so that data scientists and business analysts can access and interpret data in context to provide meaningful results to management.<br><br>Businesses across industries have a rising need for data engineers—those who can integrate gigantic amounts of fragmented data, often from thousands of data sources, and transform it into useful information used to identify business opportunities and avoid risk.
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