Introduction to DataSets:

DataSets are no more limited to specific formats such as tabular, or comma-separated. Today non-traditional data formats such as unformatted text (or the usual textual data that we write), images, videos, audio. And more are being used to delve deeper into big data projects. Even the data sources are no more restricted to official excel sheets. Data is being extracted from social media, facial recognition systems. Sentiment analysis engines, review websites, and more.

Our team at PromptCloud offers data scraping solutions from many sources and we can get you data. Whether conventional or non-conventional. Companies from different sectors and industries from recruiting to hospitals are using non-traditional datasets. This is a process done to make better predictive models today.

Traditional DataSets vs Alternative DataSets:

One of the most important points when it comes to their differences is that alternate datasets such as a blob of text or audio will not consume a system. There’s a need to convert the data into a format using which a predictive model can generate. Temporary data used in data mining to find trends that exist in the data. While traditional datasets point only to well-structured datasets generated by systems. Various organizations such as banks, or eCommerce. Alternative data comes from a wide variety of sources such as-

Mobile devices – As per a report, today, the number is close to 3.5 billion, or 45.12% of the people on the planet.

IoT devices such as smart assistants – McKinsey had forecasted that there would be 50-100 billion connected devices by 2020. While that number is no more realistic they still have quoted a sizeable 20-30 billion units.

Satellites – With the growth of private companies such as SpaceX entering the space industry. There have been more and more satellites that are being sent to space. Communication data, as well as satellite imagery collected from them.

Online search – Search data, that is, data of what people are searching on the internet is important information. Used by companies to decide on things like advertising campaigns and product launch.

Alternative DataSets That You Can Use On Your Next Project:

While alternative data sources are a hit, they can be hard to find and even harder to extract. So today, our team has curated 5 different alternative datasets that you may find useful in your data-mining or machine learning endeavors:


1. Facial Image DataSets:

Websites like Face-Rec and can provide you with links to facial image datasets. Together they can help you get millions of facial images. But this number can be helpful instead of being overwhelming since a system needs to train a huge quantity of images before its usage in real-life scenarios. Also, the greater the amount of data a system trained on, the better it will perform.

Facial data image datasets used for many purposes such as building a system that can guess the expression of a person from his image. Or for training a system to identify people from security camera footage once fed a facial image of the same person.


2. YouTube Videos DataSet:

One of the largest treasure troves accessible but rarely used data is YouTube. Yet, for using the data available in them, there’s a need for pre-processing. First, the textual transcription done on the videos to extract the information in words. On completion using an automated system, certain levels of manual intervention would need to make sure that the data extracted matches the video.

After doing this for a large number of videos on the same subject, one can use data mining or machine learning to find trends or build analytical solutions. The example provided is one of the many ways in which data from YouTube can serve you as an alternative dataset.


3. Audio DataSet:

There are many sources of audio data and structured datasets of this alternative data format do exist. But if you want to start from a certain point, then Google Research AudioSet is your best bet. It consists of 632 different audio classes (such as music, speech, lawnmower, and gargling) and it is a massive collection of 2,084,320 human-labeled sound clips, each 10 seconds long. These extracted from existing YouTube videos. A wide range of human sounds, machine noises, animal sounds, musical instruments, and genres. Along with common environmental sounds covered in this dataset.

It is a pre-validated dataset and is accurate. To collect all the data, human annotators verified the presence of sounds extracted from YouTube videos. To mark specific segments for classes, YouTube metadata used along with content-based search.


4. Satellite Images:

When it comes to satellite images, different datasets provide you with the data in different formats. In case you cannot decide to chose which fits your project best. Here’s a list of some of the best satellite images used in a wide variety of research projects. Some top features that are available in datasets in this list-

USGS Earth Explorer stands out as the only source for satellite images that go back more than 40 years. So you can see the transformation of a place, on the ground in the last 40 years. This data used to predict future land-use changes as well as the effect on nature, such as increased levels of pollution.

NASA Earthdata is one of the best sources of satellite images that show you land use and cover on a global scale. Also the land use and cover are not on a basic level, but very specialized. For example, it has satellite-derived images on places that cover with permafrost or wetlands.

The NOAA Data Access Viewer can help you get satellite images along with aerial and LiDAR photographs. It works somewhat like a search engine. Where once you enter a specific location, you will show all the associated datasets in a right-hand panel. You can download it and get going.

Satellite Images used most for predicting natural disasters, or for handling them. For this, DigitalGlobe’s Open Data Program helps provide images that can aid the effort. Different calamities such as fires, cyclones, hurricanes, floods, and earthquakes are part of this list. Satellite images of the most recent disasters are already a part of this list. These used by researchers to sound early alarms for similar happenings in the future.


5. Quora Unstructured Textual DataSet:

Quora is the largest dataset of questions and answers. And even though the text is in an unstructured format, used for analytics, data aggregation as well as data mining. Q&A data for some specific questions (or questions having a set of keywords) can gather from different websites to understand the public knowledge on a topic, their sentiments, and thoughts.

This information used to create fresh content, run media campaigns, create public awareness on issues.



When it comes to alternative data sources, the complexity barrier keeps most people out of the competition. But as these sources grow and become many times the number of traditional datasets available. Using them is imperative to get to the bigger picture. For understanding how models work and training them in the real world. Data you can use any of the instant-download and ready-to-use datasets available at DataStock– our one-stop dataset solution.


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