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Data is preliminary for companies and corporations to analyze and obtain business intelligence. It helps in finding the correlations between the data and the unique insights for a better decision-making process. And for these datasets sources are important to help you with your data science projects. But luckily there are many online data sources to fetch you free datasets to help with your projects by just downloading them absolutely free. Let's learn more about the top 7 free dataset sources to use for data science projects in this article.
Most of us think that Google is just a search engine, right? But it is way beyond. Several datasets can be accessed through the Google cloud and analyzed to fetch new insights from the data. Google cloud has more than hundreds of datasets that are hosted by BigQuery and cloud storage. Google's machine learning can be helpful in analyzing datasets such as BigQuery ML, Vision AI, Cloud AutoML, etc. Also, Google's Data Studio can be used to create data visualization and dashboards for better insights. These datasets have data from various sources such as GitHub, United States Census Bureau, NASA, and BitCoin, and many more. You can access these datasets free of cost.
Amazon Web Services has the largest number of datasets on their registry. It is very easy to download these datasets and use them to analyze the data on the Amazon Elastic Compute Cloud. It also employs various tools such as Apache Spark, Apache Hive, and more. The Amazon Web Services is an open data registry that is part of the AWS Public Dataset Program that focuses on democratizing the access of data so that it is available to everybody. AWS open data registry is free but allows you to own a free AWS account.
The US government is also keen on data science, as most of the tech companies are located in Silicon Valley. Data.gov is the main repository of the US government's open datasets that can be used for research, developing data visualizations, mobile applications, and creating the web. This is an attempt of the government to become more transparent in terms of access without registering. But some of the datasets need permissions before downloading them. Data.gov has diverse varieties of datasets relating to climate, agriculture, energy, oceans, and ecosystems.
Kaggle has more than 23,000 public datasets that can be downloaded for free. You can easily search for the dataset that you're looking for and find them hassle-free ranging from health to cartoons. The platform also allows you to create new public datasets and can also earn medals along with the titles such as Expert, Master, and Grandmaster. The competitive Kaggle datasets are more detailed than the public datasets. Kaggle is the perfect place for data science lovers.
If you are looking for interesting datasets then UCI Machine Learning Repository is a great place for you. It is one of the first and oldest data sources that are available on the internet since 1987. The datasets of the UCI are great for machine learning with their easy access and download options. Most of the datasets of UCI are contributed by different users so the data cleanliness is a little low. But UCI maintains the datasets for using them for ML algorithms.
If you are from a medical background then Global Health Observatory is a great option for creating projects on global health systems and diseases. The WHO has made all their data public on this platform. This is for the good quality health information available worldwide. The health data is characterized according to various communicable and noncommunicable diseases, mental health, morality, medicines for better access.
If you are looking for data related to Earth or Space then, Earthdata is your place. This is created by NASA to provide datasets based on Earth's atmosphere, oceans, cryosphere, solar flares, and tectonics. It is a part of the Earth Observing System Data and Information System that helps in collecting and processing the data from various NASA satellites, aircraft, and fields. Earthdata also has tools for handling, ordering, searching, mapping, and visualizing the data.
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