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Explore our MS in Information Technology Big Data Analytics specialization

In this specialization, you will develop the knowledge and competence to turn big data into actionable intelligence. Designed to cultivate your analytical skills, Walden’s Big Data Analytics specialization will introduce you to the intricate world of data mining, including data auditing, aggregation, validation, and reconciliation. By learning how to turn big value data into business intelligence, you will acquire the ability to drive enterprise productivity and increase operational efficiencies.

Students interested in this specialization should have knowledge of Java, SQL, and data processing/warehousing principles and applications. A student with a bachelor’s degree in Computer Science, Engineering, Finance, Math (Discrete Mathematics, Statistics) or similar field grounded in quantitative skills is required. Students who have completed a bachelor’s degree outside of those listed above and at a least one of the following certifications are also eligible:

  • IBM certification in Cognos, Risk Analytics, or SPSS
  • SAS certification in Foundation, Analytics, Administration, Data Management or Enterprise Business Intelligence
  • Microsoft certification (e.g., MCITP, MCSA, MCSE, MCSM, MCDBA)
  • Certified Business Intelligence Professional
  • Certified Analytics Professional
  • Certified Data Management Professional
  • Certified Health Data Analyst

Program Savings

Receive up to a $3,000 grant if you reside in the U.S. and start this program on September 27, 2021. Contact one of our Enrollment Specialists to learn more.

Get Started Now



Course Code Title Credits


ITEC 6111

Information Technology in the Organization

Through a review of modern computer systems and the social and economic issues related to their use, students in this course are introduced to the conceptual foundations for designing, developing, and deploying large-scale management information systems. Students investigate the role of information technology in an organization—particularly the collection, storage, and distribution of information for operations, planning, and decision making.

(3 sem. cr.)
ITEC 6115

Computer Networking and Operating Systems

Within this course, students can learn the concepts of computer operating systems, including the main functions, similarities, and differences. Students can explore a variety of topics, including configuration, file systems, security, administration, interfacing, multitasking, and performance analysis. In addition, they can further their understanding of computers through the study of computer networks by learning key networking concepts, components, and the design of information and communication infrastructure solutions.

(3 sem. cr.)
ITEC 6030

Principles of Programming

The discipline of software development demands a variety of skills. Students in this course assess the fundamental practices and principles of designing and constructing object-oriented programs. They engage in substantial hands-on practice, reinforcing algorithmic thinking, logical design, precise coding, and careful attention to quality.

(3 sem. cr.)
ITEC 6145

Enterprise Database Design

In this course, students discuss the design, implementation, and operation of databases using a principal relational database management system (DBMS). Many fundamental topics are covered in this course including: data modeling using entity-relationship diagrams; data storage, manipulation, and queries using structured query language (SQL); functional dependencies, normalization concepts, data warehouse architectures, data warehouse modeling, and data analytics.

(3 sem. cr.)


ITEC 6655

Data Warehousing and Business Intelligence

Students learn key approaches to the integration of enterprise-wide information to support business strategy and decision making. They cover issues in data acquisition, storage, retrieval, and analysis in this course. Topics include data warehouses; data marts; dashboards, key performance indicators, and scorecards; online analytical processing; and data visualization.

(3 sem. cr.)
ITEC 6661

Business Analytics and Data Mining

Students learn and apply techniques for inference and discovery in large data sets. Topics include statistical inference, exploratory data analysis, data mining, text mining, and machine learning for predictive modeling.

(3 sem. cr.)
ITEC 6160

Enterprise Systems Architecture

Large-scale enterprise systems often rely on architectural frameworks that define their main components as well as the interactions among these components. Students in this course survey the principal design strategies and tools for constructing the modern information system. They identify common vendor and open-source components, illustrating how these elements can create and integrate robust web- and cloud-based services and applications.

(3 sem. cr.)
ITEC 6401

Statistical Concepts for Big Data

Statistical analysis supports quality management, drives decision making, enables forecasting and prediction, and provides a means for understanding many aspects of our world. Data is everywhere in today's integrated technological society, and statistical analysis provides the means to access and interpret data. Students in this course are introduced to statistics focused on working with complex data sets and analyzing big data. Students synthesize theory with practical applications to learn the fundamentals of statistical reasoning, descriptive statistics, visual data display, regression, hypothesis testing, research design, anomaly detection, and advanced analysis practices. They have the opportunity to practice using a statistical software package to solve statistical problems. Students use a publicly available big data set to formulate their own study and complete a statistical analysis.

(3 sem. cr.)
ITEC 6675

Introduction to Big Data Analytics

The amount of data available to organizations to help them create a competitive advantage is growing exponentially. These data sets are so large and complex that traditional data modeling and data analysis processes are inadequate. In this course, students are guided through basic approaches to querying and exploring data using higher level tools built on top of a Hadoop Platform. Students will walk through query interfaces, environments, and the canonical situations for tools like HBASE, HIVE, Pig, as well as more open source tools like HUE.

(3 sem. cr.)
ITEC 6685

Data Visualization

Big Data normally refers to petabytes (1000 terabytes) or exabytes (one billion gigabytes) of unstructured data. This amount of data requires new methods to analyze, visualize, and present these data in a way that yields insight and understanding. Students in this course are introduced to elementary graphics programming, focusing primarily on two-dimensional vector graphics and the programming platforms for graphics. This infrastructure will also include lessons on the human side of visualization, studying human perception and cognition to gain a better understanding of the target of the data visualization.

(3 sem. cr.)

Tuition and Fees

Curriculum Component Requirements Cost amount
Tuition 30 semester credit hours $880 per semester hour $26,400
Technology Fee Per semester $210 $1,050


*Tuition reflects the minimum time to completion. Time to completion varies by student, depending on individual progress and credits transferred, if applicable. Tuition and time to complete may be reduced if transfer credits are accepted, or if you receive grants, scholarships or other tuition reductions. Walden may accept up to 15 transfer credits. For a personalized estimate of the number of your transfer credits that Walden would accept, call an Enrollment Specialist at 855-646-5286.

Tuition and fees are subject to change. Books and materials are not included and may cost between $1,000 and $1,400.


Many Walden degree-seeking students—67%—receive some form of financial aid.* Create a customized plan that makes sense for you.

*Source: Walden University’s Office of Financial Aid. Data reports as of 2018.

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Program Savings

Receive up to a $3,000 grant if you reside in the U.S. and start this program on September 27, 2021. Contact one of our Enrollment Specialists to learn more.

Get Started Now

Admission Requirements

Program Admission Considerations: All specializations require a bachelor's degree or higher.

The Big Data Analysis specialization requires the following: A bachelor’s degree in computer science, engineering, finance, math (discrete mathematics, statistics), or similar field grounded in quantitative skills is required. Eligibility will also be considered for candidates who hold a bachelor’s degree outside of the specified fields plus at least one of the following certifications:

  • Certified Analytics Professional
  • Certified Business Intelligence Professional
  • Certified Data Management Professional
  • Certified Health Data Analyst
  • IBM certification in Cognos, Risk Analytics, or SPSS
  • Microsoft certification (MCITP, MCSA, MCSE, MCSM, MCDBA)
  • SAS certification in Foundation, Analytics, Administration, Data Management, or Enterprise Business Intelligence

General Admission Requirements: Completed online application and transcripts. Please note that the materials you are required to submit may vary depending on the academic program to which you apply. More information for international applicants.



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