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If you are looking for some usable and significant data for either creating reports, statistical modeling, or anything else then here is a list of 10 places you can go to download data.

1. Google Fusion Tables

Google Fusion Tables

All the support you would need for this site is located here. The nice thing about Google Fusion Tables is that there are many others doing the same thing, sharing data and using it as well!

2. Data.gov

A primary goal of Data.gov is to improve access to Federal data and expand creative use of those data beyond the walls of government by encouraging innovative ideas (e.g., web applications). Data.gov strives to make government more transparent and is committed to creating an unprecedented level of openness in Government. The openness derived from Data.gov will strengthen our Nation’s democracy and promote efficiency and effectiveness in Government.

Data.gov

3. WorldBank

This site is meant to provide all users with improved access to World Bank data and to make that data easy to find and use. The World Bank recognizes that transparency and accountability are essential to the development process and central to achieving the Bank’s mission to alleviate poverty. The Bank’s commitment to openness is also driven by a desire to foster public ownership, partnership and participation in development from a wide range of stakeholders. As a knowledge institution, the World Bank’s first step is to share its knowledge freely and openly.The WorldBank

4. DataWrangling

DataWrangling’s author Pete Skomoroch who is the founder of Data Wrangling LLC and a Sr. Data Scientist at LinkedIn has been tagging interesting data he finds on the web in del.icio.us. He wrote a quick python script to pull the relevant links from his del.icio.us export and list them at the bottom of this post. Most of these datasets are related to machine learning, but there are a lot of government, finance, and search datasets as well.

DataWrangling.com

5. CKAN – the Data Hub

CKAN is the Comprehensive Knowledge Archive Network, a registry of open knowledge packages and projects (and a few closed ones). CKAN makes it easy to find, share and reuse open content and data, especially in ways that are machine automatable.

CKAN The Data Hub

6, Infochimps

From the most basic blog to the human genome, the world is full of data. It’s interesting, but it’s not always in a format that people or machines like computers can understand. Infochimps is a place for people to find, share and sell formatted data. Both users and Infochimps employees scrape, parse and format data so that it’s easily accessible to you. We take the chimp work out of working with data so you can literally start building cool stuff in minutes.

InfoChimps.com

7. Freebase

Freebase is an open, Creative Commons licensed repository of structured data of almost 22 million entities. Ways to use Freebase: Use Freebase’s Ids to uniquely identify entities anywhere on the web Query Freebase’s data using MQL Build applications using our API or Acre, our hosted development platform Freebase is also a community of thousands of data-lovers, working together to improve Freebase’s data. Learn how to contribute, join our mailing list, or find out more on our community page.

Freebase.com

8. Datamob

Datamob aims to show, in a very simple way, how public data sources can be used. Datamob welcomes your contributions of high-quality public data sources and interfaces. Datamob was built with Rails in 2008 in coffee shops around New York City by Sean Flannagan and Lauren Sperber. Datamob currently lists 225 datasets, 163 interfaces and 66 resources, which are categorized by 67 tags.

DataMob

9. Reddit

Datasets for Data Mining, Analytics and Knowledge Discovery

reddit

10. DiggingIntoData

In 2011, the Digging into Data Challenge has returned for a second round, this time much larger, with sponsorship from eight international research funders, representing Canada, the Netherlands, the United Kingdom, and the United States.

What is the “challenge” we speak of? The idea behind the Digging into Data Challenge is to address how “big data” changes the research landscape for the humanities and social sciences. Now that we have massive databases of materials used by scholars in the humanities and social sciences — ranging from digitized books, newspapers, and music to transactional data like web searches, sensor data or cell phone records — what new, computationally-based research methods might we apply? As the world becomes increasingly digital, new techniques will be needed to search, analyze, and understand these everyday materials. Digging into Data challenges the research community to help create the new research infrastructure for 21st century scholarship.

 

diggingintodata

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About The Author

Joshua Burkhow

Joshua is working to become a Data Scientist with focus on Analytics, Big Data, Machine Learning, and Statistics. His passion for Data and Information are second to none. He is a certified IBM Cognos Expert with more than 10 years experience in Business Intelligence & Data Warehousing, Analtyics, IT Management, Software Engineering and Supply Chain Performance Management with Fortune 500 companies. He has specializations in Analytics, Mobile Reporting, Performance Management, and Business Analysis.

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