Data is the New Oil and Google DataSet Search is the Motherlode of Data

Data is the new oil and now Google is providing Dataset Search.

Datasets are needed to train Machine Learning and for other computer projects.

Data is a vital resource for the modern age and now Datasets are easily published and discovered.

Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets and find links to where the data is.

You can now filter the results based on the types of dataset that you want (e.g., tables, images, text), or whether the dataset is available for free from the provider. If a dataset is about a geographic area, you can see the map. Plus, the product is now available on mobile and we’ve significantly improved the quality of dataset descriptions. One thing hasn’t changed however: anybody who publishes data can make their datasets discoverable in Dataset Search by using an open standard (schema.org) to describe the properties of their dataset on their own web page.

The largest topics that the datasets cover are geosciences, biology, and agriculture. The majority of governments in the world publish their data and describe it with schema.org. The United States leads in the number of open government datasets available, with more than 2 million. And the most popular data formats? Tables–you can find more than 6 million of them on Dataset Search.

7 thoughts on “Data is the New Oil and Google DataSet Search is the Motherlode of Data”

  1. Schools not teaching set theory isn’t a case of too much inertia.

    It’s the exact opposite: set theory used to be taught, and was abandoned as teaching theory flitted from one option to another like an ADHD butterfly seeking a way to achieve their impossible requirements (teach all kids to be above average without putting in lots of (expensive) skilled instructors, and at the same time keeping the unions, parents, wacko pressure groups and taxpayers all from getting too upset).

    Here’s an article from the 1970s complaining about how schools had changed to teaching set theory (among other things) and urging the system to flutter to the next promising flower.

    https://www.nytimes.com/1974/01/06/archives/does-new-math-add-up-new-math.html

  2. Data is the new oil… and those with the best data mining skills will be the new refiners.

    So when does petroleum become the new whale oil ?

  3. I spent some serious time as a database programmer and DBA. Getting my mind wrapped around relational databases after being out of college for over a decade was a bit of a challenge, but eventually I even found myself dreaming in SQL (fortunately, that phase has long passed).

    Ever since then, however, it has boggled me that our schools don’t teach set theory right along with algebra, geometry, calculus, and trig. Truly, inertia in our educational system is an awesome force.

    And yes, my stock in Google and Amazon has done some amazing things for my portfolio these couple of decades. Facebook at IPO was something I was unsure about, and Tesla has been a bit too risky for me, Apple always seemed like it was too expensive already and too dependent on the next big gadget (although that might be changing as they move to selling services rather than widgets).

    Peter Lynch, in his classic “One Up On Wall Street,” cautioned against buying a company that made the best widget, or was about to, as someone else might always trump them the next day, but, instead, to buy companies that benefit (more than most) when widgets improve (because they will).

  4. can we please get a consistent font size between the main articles and comments?
    With latest update, if I scale up to read the article comfortably, the comments are difficult to read, and vice versa.
    (If the screen size matters, I’m on a tablet.)

  5. It has been over 3 years since frackers drilled a dry well.
    They can use this data to thread a needle in the geologic substrate.

  6. Note to self: keep buying shares in companies driven by massive and growing datasets: Google, Amazon, Facebook, Tesla.

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