updated daily. It also allows a data provider to push out code to clients. For example, if an ATTOM data licensing client wants query code to identify the most recent update on a property — which can be challeng- ing given that ATTOM is tracking myriad changes to the 155 million U.S. properties in its data ware- house, including sales, mortgages, property value, and much more on a daily basis — ATTOM can proactively push that code to the customer in the DaaS environment. That code becomes a turnkey solution not only for that client but for other clients using DaaS. Secondly, DaaS is not an API (Ap- plication Program Interface). Some have conflated the two services given that both help companies avoid the hassle of managing a mas- sive database. The API solves the database management challenge by serving up individual data elements
and combinations of data elements needed just in time for the client or end-user to use, typically in a soft- ware environment. The API solution is ideal for companies that need to auto-fill an online application or serve up specific property details for an end-user in real-time. An API isn’t a database that com- panies can query for use in robust analytics, modeling and machine learning. All of that, however, can be accomplished in DaaS using data analysis tools such as R, Python or Java. In short, DaaS provides analyt- ics-ready data. ANALYTICS-READY DATA The analytics-ready component of DaaS is especially relevant in the world of real estate data, which is awash with derivative data designed to show market trends — from more common derivatives such as me-
dian prices and AVMs (Automated Valuation Models) to more niche derivatives such as home flips and home equity. Many data licensing clients don’t want to rely on the assumptions made for those standard derivatives; instead they want to analyze the record-level source data directly and use their own assumptions to create their own versions of those deriv- atives — not to mention additional data-derived metrics that aren’t readily available from other sources. DaaS provides quick and convenient access to the record-level data, allowing customers to get analytics in minutes rather than the days or weeks it would take to ingest the flat files and build the tables needed to run those same analytics. The analytics-ready nature of DaaS also appeals to clients who are “drowning in data.” These cli- ents are spending so much energy
30 | think realty magazine :: may / june 2019
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