Data Trends for Investment Professionals

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Quandl Phase 2: The Democratization of Commercial Data

Today, 18 months or so since we launched, Quandl offers the world unlimited and unrestricted access to over 10 million time-series datasets. That number grows every day thanks to our small team here in Toronto and thanks to the many users around the world who contribute data to the site every day. While this is a great beginning and we are definitely proud of what we have achieved, we are nevertheless just getting started; we have aspirations way beyond 10 million datasets.

Our ultimate objective is nothing less than everything: all numerical data in the world available on Quandl. This is perhaps quite an audacious goal, but we are inspired by Wikipedia, YouTube, Google and others who have, for their respective media types, largely achieved what we seek to do with numerical data.

By “everything” we do not mean just the data that we can get for free. “Everything” means all the data that is not free too. There is a huge amount of important, valuable data that is proprietary; we are determined to offer this too on Quandl, not least because so many of our users are asking for it. Therefore, in the coming weeks we will be launching the first set of paid premium databases on the site.

Quandl’s approach to paid premium data will be unprecedented. We will not play by the rules the incumbent data oligarchy has established. Their decades-old model has not served consumers well: it keeps data prices artificially high, it cripples innovation, and it is antithetical to modern patterns of data consumption and usage. (I have discussed this before.)

Our plan is to democratize access to commercial data. Anyone will be able to buy data on Quandl. There will be no compulsory bundling, forcing you to pay for extra services you don’t need; no lock-in to expensive long-term contracts; no opaque pricing; no usage monitoring or consumption limits; no artificial scarcity or degradation. Users will be able to buy just the datasets they need, a la carte, as and when they need them. They will get their data delivered precisely the way they want, with generous free previews, minimal usage restrictions and all the advantages of the Quandl platform. And of course, the data itself will be of the highest quality: truly professional grade.

We will also democratize the supply of data. Anyone, from existing data vendors and primary data producers to individuals and entrepreneurs, will have equal access to the Quandl platform and the unmet demand of Quandl’s user base. We want to create a situation where anyone capable of curating a database can monetize their work. In time, we hope that fair competition among vendors will force prices to their economic minimum. This is the best possible way to deliver the lowest possible prices to our users.

At the same time this democratization should empower capable curators to realize the full value of their skills: If someone can build and maintain a database that commands $25 a month from 1000 people, then Quandl can be the vehicle that transforms that person from skilled analyst to successful data vendor.

Our foray into commercial data will start officially this fall with 8 pilot vendors. They range from entrepreneurially-minded analysts who are building databases to rival what the oligarchs sell for exorbitant fees, to long-established data vendors progressive enough to embrace Quandl’s modern paradigm. Other vendors will follow soon after. If you are interested in learning more, you are, as always, welcome to email me.

(Oh, and just to be absolutely clear: the addition of paid commercial data will not affect the 10 million free datasets already on Quandl in any way. All data and all features that are currently available for free on Quandl, will remain free forever. Nor will the addition of paid premium data affect our free data pipeline; we will continue to add hundreds of thousands of free datasets to Quandl every month. Our mantra remains unchanged: Any data that we can acquire for $0 will always be offered to users for $0.)

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