>

Learning Resources

  • Vanderbilt University

    What does DSA do?

    What does DSA do? The primary focus of the Office of Data & Strategic Analytics (DSA) is to ensure that Vanderbilt’s decision-makers can access data they trust to do their jobs better. We want to make data the oil that keeps the Vanderbilt engine humming, and to keep it… Read More

    Mar. 4, 2026

  • Vanderbilt University

    How to Get the List You Really Want: Why Identifiers Matter in List Enhancement Data Requests

    Requests to add additional data to a list are common and often straightforward. The information exists, the desired output is clear, and the goal is simple: connect one dataset to another and return a more complete picture.  Whether that connection happens smoothly depends on the structure of the file… Read More

    Feb. 24, 2026

  • Vanderbilt University

    The Value of Effect Sizes

    Why Understanding Effect Sizes Are Important  Imagine you’re conducting a survey and want to understand how meaningful your results really are. Is this difference small or large compared to previous surveys conducted at my institution or with other populations? Enter Cohen’s d – one of several effect size measures.  What exactly is Cohen’s d? Cohen’s d is a statistical calculation that helps you compare the magnitude of differences between two groups, regardless… Read More

    Feb. 23, 2026

  • Vanderbilt University

    Degrees of Detail

    Granularity and Cardinality in Higher Ed Data  “Just give me a big table and I’ll figure it out in Excel” is a sentiment often expressed to the Data and Strategic Analytics team. If only it were that easy.  Sometimes it is. You have a… Read More

    Feb. 23, 2026

  • Vanderbilt University

    No Student Left Unjoined: Basics of SQL Joins

    If you’re new to SQL, one of the first concepts you’ll encounter is joining data.  At Vanderbilt we have thousands of tables of data stored separately. One table might hold core student information, another demographic attributes, another course data, and another faculty assignments. The question is how those pieces connect.  If you’re fortunate, a data model… Read More

    Feb. 23, 2026

  • Vanderbilt University

    Data Transformation 101: What Happens Between Raw Data and Your Dashboard

    You’ve got a beautiful dashboard. Clean visualizations. Clear metrics. Your stakeholders love it. But what if I told you that what they’re looking at did not come directly from the source system?  The Problem Many people assume that data flows seamlessly from your operational systems (your CRM, your ERP,… Read More

    Feb. 18, 2026

  • Vanderbilt University

    Oracle Analytics Cloud (OAC) Access Request Guide: A Thoughtful Approach

    Requesting data access matters more than it might seem. The degree of thoughtfulness and specificity of a request for a report determines how quickly, and how accurately, that access is granted. Thoughtful requests are usually processed in a day or two. Vague ones tend to stall,… Read More

    Feb. 12, 2026

  • Vanderbilt University

    Sensitivity Is Not the Same as Sensitive Data 

    Leaders reviewing a draft article agreed on several things. The data itself was sound. No protected information was included. No departments were named. No policies were violated. And yet, there was discomfort about publishing the piece. The worry wasn’t about confidentiality. It was about whether someone might read the story and… Read More

    Feb. 4, 2026

  • Vanderbilt University

    Data Literacy: It’s Not a Class…It’s a Culture!

    We talk about data all the time along with dashboards, metrics, reports, and insights. But having data is not the same as understanding it and understanding data is not the same as being able to use it well. According to the Data Management Body of Knowledge (DMBOK), data literacy is… Read More

    Feb. 2, 2026

  • Vanderbilt University

    Different Is Not Always Wrong: Why Transactional Systems and the Data Warehouse Can Tell Different but Correct Stories

    “The data is wrong!”  That reaction is common when numbers don’t match across systems. Sometimes it’s justified. More often, the data isn’t wrong at all. It’s simply answering a different question.  When users compare figures from a transactional system with those from the data warehouse, discrepancies can feel alarming and are often… Read More

    Feb. 2, 2026