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Articles by: Faithe Day

Faithe Day

Faithe J. Day is a writer, researcher, and educator with a BA in English and Digital Humanities and a PhD in Communication Studies. Over the past few years, she has been awarded research fellowships focused on data science, curation, and education, during which she developed projects that critique the role of information and technology within society and culture. Through a focus on the ethics of data collection and sharing, her writing explores the politics of platforms, the role of social media in society, and the future of algorithms and artificial intelligence.

Best Open-Source Tools for Data Scientists

The rising interest in open-source platforms could potentially change the future of science and technology, as these tools offer various options and provide better accessibility. This article discusses the importance of open-source software to data scientists, highlighting the top five open-source tools in the industry, and how to further explore them.

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Best Statistical Analysis Software for Data Scientists

Discover the intersection of data science and statistical analysis and understand the importance of statistical analysis software in data science. Uncover the top tools used by data scientists for statistical analyses and explore the unique features of popular software like SAS/STAT, IBM SPSS, Stata, MiniTab, and scikit-learn.

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Best Data Science Tools for Social Media

Uncover the role of social media in data science and learn key tools that can help you capture and analyze data from this fast-growing source. Discover how the analysis of social media data can yield valuable insights into consumer behavior and future trends, despite the ethical and privacy challenges it presents, and explore the industries where this knowledge can be applied.

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5 Reasons Data Scientists Should Use Excel

Explore the dynamic world of data science; uncovering how it goes beyond conventional statistical analyses to include advanced techniques, programming languages, and complex code. Discover five compelling reasons why the classic software, Microsoft Excel, remains a crucial tool in this ever-evolving industry.

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Best Data Science Tools for Beginners

Navigate the world of data science tools with ease, utilising this comprehensive guide designed for beginners. With a detailed breakdown of tools for data collection, database management, data exploration and analysis, as well as data modeling and visualization, this guide offers a curated list of software and programs integral for kick-starting your journey in data science.

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Best Data Science Tools for Non-Programmers

If you're entering the data science field, choosing the right tools is fundamental to your success. This guide provides an overview of various data science tools useful for different stages of a project, and includes a toolkit specifically for beginners, with software and programs recommendations you can use to complete simple data science projects.

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Database Management Tools for Data Scientists

Explore the pivotal role of database management in data science, from its focus on data storage, organization, and cleaning to an in-depth description of different types of databases. Learn about top database management tools and how you can enhance your skills in the data science industry, ranging from SQL programming to managing documents in NoSQL databases.

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Why Learn R for Data Science?

Discover the power and versatility of the R programming language, the preferred tool for data scientists and computer scientists worldwide. With a rich history and a host of features, R offers an effective solution for statistical analysis, machine learning, and artificial intelligence, making it essential for anyone interested in data science.

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Why Learn Java for Data Science?

Choosing a programming language to learn and master can significantly impact your future career in data science. This article explores why Java, known as one of the world's most popular and lucrative programming languages, is highly beneficial for data science professionals in expanding their skills and capabilities.

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