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Data Practices

Data Practices

  • Best Practices
  • Data Tips & Toolkits
  • Database Best Practices
  • Transferring Data
Best practices for data management and analysis varies greatly depending on your data and analysis requirements.
Additionally, we encourage you to carefully consider the security level of the data you’re working on, as this may affect data transfer and how and where it is stored. We have compiled general information about best practices, efficiency, and strategies on working with data on the HBSGrid, found on the pages in this section.
→How to determine the security level of your data

Best Practices 

RCS provides guidance on data management and efficiency best practices, along with how to optimize your data generally and for specific software packages.

Data Tips & Toolkits 

RCS has compiled an array of packages and tools that can help you with your data wrangling, web scraping, and statistical analysis, among others. Below is a selected list of tips and toolkits.
  • Machine Learning
  • Fuzzy Matching
  • Natural Language Processing
  • Web Scraping
  • Power Analysis
  • Causal Inference
  • Missing Data

Database Best Practices 

Before you start building your database, consider your goals, carefully design your database, and ensure you document the process.

Transferring Data 

The HBSGrid is primarily used for data analysis, machine learning, data wrangling, and data visualization. Usually this means that you need to copy or transfer your data to the HBSGrid in order to do your work.

Other Data Resources

Data Repositories

  • Harvard Dataverse at IQSS

  • Baker Library Databases

  • Center for Geographic Analysis at Harvard

  • Figshare

Other Harvard Data Resources

  • Data Science Services at IQSS

  • DataFest (2020)

  • HMS Data Management Working Group

  • DataVerse

Other Data Resources

  • DataAbInitio blog: Managing Research Data Right, From the Start

  • Cookiecutter Data Science

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Research Computing Services (RCS) 
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Phone: 617.495.6100
Email: research@hbs.edu
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