Skip top navigation Skip to main content
Lasell University
Lasell University

Data Analytics

Major

What You'll Learn
Career Outlook
Request Info
Loading...

The Data Analytics major prepares you for a career in sports analytics, big data, business and data analysis, and more.

The Data Analysis major prepares gives your the foundation to understand data and create actionable insights. Organizations across industries have the increasing need for skilled analysts who can collect, analyze, and produce actionable insights for their teams to generate more revenue, increase customer base, and develop products.

Program Features

  • Lasell University is proud to partner with Rize Education, an innovative organization that enhances higher education offerings by providing students with access to specialized courses designed in collaboration with industry experts and leading universities. Through this partnership, Lasell is able to offer cutting-edge curriculum in emerging fields, giving our students an opportunity to gain high-demand skills and certifications that can boost their career prospects.

    By working with Rize, we aim to provide our students with access to affordable, high-quality courses that complement Lasell’s core academic programs. This collaboration allows us to deliver real-world learning experiences that align with industry needs and future workforce trends, keeping Lasell at the forefront of education for today’s rapidly evolving job market.

    Through our shared vision, Lasell and Rize Education continue to support our students’ success by offering innovative learning solutions and expanding their opportunities in today’s competitive world.

  • The Data Analytics major allows students to earn certifications and badges in: Google Analytics and SAS Visual Analytics.

  • Learn techniques and tools to set-up, retrieve, aggregate, and process large data sets - from a traditional data store to Big Data insights.

  • Learn methods of data analysis and visualization using software to create charts, dashboards and reports.

  • Complete at least one industry-relevant internship.

What You'll Learn

From your first day, you’ll take courses in your major and advance towards graduation with a yearly plan. Not sure what classes to take? We’ll help you create the perfect plan. 

Courses and Sample 4-Year Plan

This example four-year plan is provided as a broad framework that you can follow in order to complete your degree within four years. Be sure to always consult your academic advisor before registering for classes.

MATH203
Precalculus

This course prepares students for the study of calculus, physics and other courses requiring precalculus skills. Included is solving systems of equations, the analysis and graphing of linear, quadratic, polynomial, exponential, logarithmic, rational functions, the unit circle, and triangle (right and non-right) trigonometry. Prerequisite: MATH 106 with a grade of C or better or demonstrated competency through placement testing. Restrictions: not open to students who have completed 205, 206, or any 300 level mathematics course successfully.

This course provides students with the fundamental skills and concepts required to maintain, support, and work efficiently with personal computers. It will assist students in preparing for the Digital Transformation. The course is organized around the five important uses of technology in business – IT concepts, Infrastructure, Applications and Software Development, Database fundamentals, and Security and Cloud Computing

In this course, students gain understanding of and confidence in strategies for effective writing by composing and reading in a variety of genres. The course emphasizes writing as a process and focuses on the rhetorical choices writers make. Students engage critically with sources by examining how genre, context, purpose, credibility, and bias work together to create meaning and impact audiences. Students who choose to take Writing I Workshop are provided with time during class to work on their writing while the instructor and a writing tutor are present to provide assistance. Students must earn a “C” or higher in order to pass this course

The First Year Seminar (FYS) is part of the Core Curriculum and a requirement for all incoming first year students and transfer students with fewer than 15 credits. The First Year Seminar is a theme-based inquiry course that engages students in a specific area of interest while providing support for a smooth transition into the Lasell University community and the Connected Learning philosophy. Through studying an academic topic, students develop and apply core intellectual skills and receive an introduction to the core knowledge perspectives. At the same time, students connect to the experiences and people that make up the Lasell University Community. Course outcomes are accomplished through engaging activities including reading, writing, class discussions, presentations, team projects, field trips, and exploration of campus resources. Civic engagement and service-learning activities are often part of this course as is participation in the Connected Learning Symposium. Through the seminar, students develop close ties with faculty and peer mentors who serve as advocates for first year students' academic success. Past course titles have included: The Immigrant Experience, Fashion & Film of the 20th Century, The Social History of Rock & Roll, Exploring Cultures & Languages, The Spark of Creativity, Women and Sports, and Latin America: Food And Traditions. This requirement may be fulfilled by taking either FYS103 or HON101 (for students enrolled in the Honors Program).

KP (Knowledge Perspective) Course

This course introduces students to basic Microsoft Excel skills. Excel is an electronic spreadsheet program used for storing, organizing and manipulating data. It is critical to the business world today as the volume of data generated has exploded. This introductory course will provide students with information and skills needed to create basic workbooks and worksheets, create simple formulas, copy and move data, format data and cells, work in large spreadsheets and with data series, create pivot tables, and more. As part of this course, all students will have the opportunity to become certified in Microsoft Excel through the professional certification called Microsoft Office Specialist: Excel 2016 – Core Data Analysis, Manipulation, and Presentation. The certification also comes with an electronic badge. Students are also introduced to Income Statements, Balance Sheets, Statement of Cash Flows, Ratios, and the Basic Accounting Cycle.

This course is a continuation of Writing I and focuses on research and public writing. Theme-based courses provide students with lenses to explore issues of interest and develop their reading, research, and writing skills. Students work with a topic of their choice, broadly based on the course theme. Assignments build upon each other, lead up to a researched position paper, and culminate in a public piece. Students who choose to take Writing II Workshop are provided with time during class to work on their writing while the instructor and a writing tutor are present to provide assistance. Students must earn a grade of “C” or higher in order to pass this course. Prerequisite: WRT 101

Equity & Intersectionality(KP)

MATH208
Statistics

This is an introductory course in descriptive and inferential statistics. Topics include: data analysis, and graphical methods of describing data, measures of central tendency and variability, probability, the normal distribution, sampling distributions, confidence intervals, hypothesis testing, correlation, and regression analysis. Prerequisites: MATH 106 with a grade of C or better or demonstrated competency through placement testing and ENG 102.

This introduction to computer science, emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students learn design, implementation, testing, and analysis of algorithms and programs. And within the context of programming, they will learn to formulate problems, think creatively about solutions, and express those solutions clearly and accurately. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, astronomy, video games, and environmental simulation. Students get instruction from a world-class computer science professor, delivered remotely through video and interactive media and attend class for collaborative team projects to solve real-life problems. Prior programming experience is not a requirement for this course. Formerly: INTC102

This course is an introduction to limits, continuity, and methods of differentiation. Application to problems in business management and physical science is emphasized. Prerequisite: MATH 203 with a grade of C or better or demonstrated competency through placement testing. Restrictions: not open to students who have completed MATH 206, or any 300 level mathematics courses.

This Knowledge Perspective course will provide students with the opportunity to interpret and analyze the complex interrelationships and inequities in human societies in a global historical context. Emphasizing the interrelatedness and mutuality of influence between East and West, we examine questions of exclusiveness, intolerance, and cooperation. Prerequisite: ENG101 with a C or better

KP (Knowledge Perspective) Course

Quantitative statistical tools for modern data analysis are used across a range of disciplines and industries to guide organizational, societal and scientific advances. Using data sets from across a variety of fields, the focus will be on applications and analysis. Topics include two sample confidence intervals, Chi Square tests, multiple regression analysis, ANOVA, non- parametric tests, sampling, and simulation. Prerequisite: Math 208 or Math 209

In this project-based course, students explore a social or intellectual problem using at least two knowledge perspectives. Faculty and students follow a collaborative process of exploration, discussion, and problem solving that integrates knowledge perspectives and core intellectual skills.

An introduction to the theory and structure of modern operating systems, including hardware abstraction, process management, memory management, system performance, and security. Specific attention to multi-threaded processing, semaphores, locking and inter-process communication. Prerequisites: DSCI102 and DSCI103 (formerly INTC102/INTC103).

This course introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Students will learn to use a combination of tools and techniques, including spreadsheets, SQL and Python to work on real-world data sets using a combination of procedural and basic machine learning algorithms. They will also learn to ask good, exploratory questions and develop metrics to come up with a well-thought-out analysis. Presenting and discussing an analysis of data sets chosen by the students will be an important part of the course. Prerequisites: DSCI102 and DSIC103 (formerly INTC102/103).

KP (Knowledge Perspective) Course

DSCI105
Data Warehouse and Business Intelligence

This course begins with the introduction of a data warehouse. Students will learn the concepts, tools and application of data warehouse for business reporting and online analytical processing. Students will also learn how to create visualizations and dashboards, and descriptive analytics. The material builds from the concepts learned in basic statistics courses. Core tools used in this course include Microsoft Excel, and SAS Visual Analytics. Excel will be used to teach the basics of visualizations – like bar charts, line charts etc. in order to ramp-up the students’ expertise into SAS Visual Analytics. SAS Visual Analytics will be used as a tool to introduce students to data warehousing, and building basic visualizations. Students will also be exposed to Facts and Dimensions.

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. The course covers issues both theoretical and practical. Students will be presented with algorithms and approaches in such a way that can ground them in larger systems as they learn about a variety of topics, including statistical supervised and unsupervised learning methods, randomized search algorithms and reinforcement learning. Prerequisites: DSCI102, DSCI103 and DSCI204.

This course will address the interaction between the lives we lead and the application of traditional (and some nontraditional) ethical theories and principles to important decision points in our lives. Students will take on real-life ethical problems and dilemmas for each class; each student will be responsible for presenting a number of issues, as well as for guiding the discussion of those issues in class. The problems we address will largely span a lifetime of experiences and concerns. Students will also write several papers that evaluate formal arguments, using standard tools of critical thinking and philosophy. The course is discussion based, so a willingness to read carefully, to think critically, and to engage in classroom presentations and discussions is essential. Prerequisite: Junior standing, MDSC203 & ENG102.

This course provides the conceptual and technical foundations of various aspects of Data Analytics. The purpose is to prepare students with foundation skills in Big Data, a skill widely needed and valued across the business world. The course will expose students to the data analytics practices executed in the business world and explores key areas of the analytical process, how data is created, stored, accessed, and how organizations work with data and creates the environment in which analytics can flourish. This course will provide students with a strong foundation in all the areas that support analytics and will help them to better position themselves for success within any organization. This course provides the conceptual and technical foundations of various aspects of Big Data Analytics, including cloud computing, NoSQL Databases, predictive and prescriptive analytics. Prerequisite: MATH208 or MATH209.

KP (Knowledge Perspective) Course

This course provides students with the opportunity to write useful Python applications in the ETL, web, and data analysis domains and knowledge of industry-standard tools and techniques for working within a development team. The course goes further into Python’s powerful advanced features, such as user-defined classes, object-oriented design, decorators, and generators. Students will learn to employ the most widely used algorithms and libraries to solve common problems in the field and gain a working familiarity with statistical analysis and visualization using Pandas, NumPy, and Matplotlib. Query and parse HTML, XML, and JSON are used. Students will learn to apply industry-standard tools and techniques for working within a development team, such as Git for versioning and code review. The course concludes with a discussion of common interview questions and pathways for gaining experience and eventually securing a position in the field. Prerequisites: DSCI102, DSCI202 and DSCI204.

This course focuses on building and enhancing skills from the Data Warehousing and Business Intelligence course. Students will expand their concepts of Business Intelligence, Visualizations, Dashboards, and Descriptive Analytics. The core tool used in this course is SAS Visual Analytics. Students will create visualizations, dashboards, and export reports to be able to present to the class. Prerequisite: DSCI105.

Topics will include elementary logic and set theory, equivalence relations, functions, counting arguments, inductively defined sets, recursion, graphs and trees, Boolean algebra and combinatorial circuits, and countability arguments. Prerequisite: MATH203 with a C or better.

KP (Knowledge Perspective) Course

KP (Knowledge Perspective) Course

DSCI402
Analytics with R

This course introduces students to R, a widely used statistical programming language. Students will learn to manipulate data objects, produce graphics, analyze data using common statistical methods, and generate reproducible statistical reports. They will also gain experience in applying these acquired skills in various public policy areas. Prerequisites: DSCI102, DSCI202 & DSCI204

This course provides the conceptual and technical foundations of various aspects of Big Data Analytics. The purpose is to help students acquire foundation skills in Big Data – which can be used to further their specialization in a niche within Big Data. Upon completion of the course students should be able to understand: What Big Data, Cloud Computing and NoSQL Databases are; Various components and architecture of Big Data Analytics; Different types of Analytics including Text, Descriptive, Predictive and Prescriptive; and how Big Data Analytics is used in different contexts. Students should also be able to use Analytics and Dashboards to present actionable Insights. This course will use SAS Visual Analytics as one of the tools for illustrating the volume of Big Data, and how it can be used to harness actionable insights. Students will use datasets to create visualizations and actionable insights. Prerequisites: DSCI102, DSCI105 and DSCI201.

KP (Knowledge Perspective) Course

KP (Knowledge Perspective) Course

This course allows students to develop the competencies and skills for planning and controlling projects and understanding interpersonal issues that drive successful project outcomes. Focusing on the introduction of new products and processes, students will examine the project management life cycle, define project parameters, matrix management challenges, effective project management tools and techniques, and take on the role of a project manager. This course is designed to guide students through the fundamental project management tools and behavioral skills necessary to successfully launch, lead, and realize benefits from projects in both for-profit and non-profit organizations. Prerequisites: Senior Standing and internship.

This course focuses on building and enhancing skills from the Data Warehousing and Business Intelligence course. Students will expand their concepts of Business Intelligence, Visualizations, Dashboards, and Descriptive Analytics. The core tool used in this course is SAS Visual Analytics. Students will create visualizations, dashboards, and export reports to be able to present to the class. Prerequisite: DSCI105.

In this course, students will be introduced to the fundamentals of the art and science of Predictive Analytics as it relates to improving business performance. This hands-on course covers the key concepts necessary to extract stored data elements, understand what they mean from a business point of view, transform their formats, and derive new relationships among them to produce a dataset suitable for analytical modeling. At the end of the course, participants will be tasked with using these skills to produce a fully processed data set compatible for building powerful predictive models that can be deployed to increase profitability. Prerequisite: DSCI303.

KP (Knowledge Perspective) Course

KP (Knowledge Perspective) Course

Lasell students can receive an industry-recognized certificate issued jointly from Lasell and SAS in Analytics upon the completion of 4 courses and an elective involved with using SAS Analytics.

Courses:

INTC104X: Data Analytics and Statistics
This course will review the different concepts in statistics that apply to technology. During the course, the students will start from basic concepts such as central limit theorem, basic statistics (mean, median, mode, etc.) to concepts such as correlation and regression, quantitative analysis, and probability.   The course will use the theory of SAS to get students familiar with the terminology and concepts used in SAS Analytics. 

INTC105X: Data Warehouse and Business Intelligence
This course will start with the introduction of a data warehouse. Students will learn the concepts, tools, and application of data warehouse for business reporting and online analytical processing. The course will also teach students how to create visualizations and dashboards, and descriptive analytics. Core tools used in this course: Excel, SAS Visual Analytics. 

INTC201X: Analytics using SAS Visual Analytics
This course will focus on building and enhancing skills from the data warehousing and business intelligence course. Students will expand their concepts of business intelligence, visualizations, dashboards, and descriptive analytics, and export reports to present to the class. Core tool used in this course: SAS Visual Analytics.

INTC301X: Big Data Analytics
This course provides the conceptual and technical foundations of various aspects of big data analytics. The purpose is to help students acquire foundation skills in big data, which can be used to further their specialization in a niche within big data. Upon completion of the course students should be able to:

  • Understand what is big data, cloud computing, and NoSQL databases
  • Various components and architecture of big data analytics
  • Different types of analytics: text, descriptive, predictive, and prescriptive
  • How big data analytics is used in different contexts
  • Using analytics and dashboards to present actionable insights.

The course will use SAS Visual Analytics as one of the tools to showcase students the volume of big data and how it can be used to harness actionable insights. Students will use datasets to create visualizations and actionable insights.


Electives:

  • Marketing Analytics
  • Sports Analytics
  • Healthcare Analytics
  • Fashion Analytics

This example four-year plan is provided as a broad framework that you can follow in order to complete your degree within four years. Be sure to always consult your academic advisor before registering for classes.

4-Year Plan
Student Profile
Trevor Lopinsky with a book

"The Forensic Science program has given me so much hands-on knowledge. I feel confident about getting a job."

Trevor Lopinsky '24

Forensic Science

Read more about Trevor
Trevor Lopinsky with a book

For a complete list of courses and learning outcomes, view the Academic Catalog

Career Outlook

Data Analytics majors are prepared for careers in a broad array of industries including sports analytics, big data engineering, and business analysis.

Our alumni have careers in areas such as:

  • Data Scientist
  • Data Analyst
  • Business Analyst
  • Big Data Engineer
Beyond the Classroom
VR/AR Lab

Lasell's new virtual reality lab enhances classroom experience by with cutting edge virtual reality/artificial intelligence technology.

Take Your Next Steps

Contact Our Admission Team

Visit Campus

Apply Now