Innovative solutions combined with intelligence from property data providers are two of the foundations of digital analytics. But there is a third element. For superior results, the format of data delivery matters.
Institutional investors, mortgage providers, fintech, and proptech companies are successfully using artificial intelligence and machine-learning innovations to drive their strategies and relying on data delivery to do so.
Parquet is a new data storage format used by ATTOM. Parquet uses compressed data files that speed up queries, reduce storage costs, and power-up processing of large data sets. Here’s a look at Parquet’s unique design and why it is tailor-made for real estate and property data analytics
Parquet’s Unique Data Storage Format
Parquet, ATTOM’s most recent data storage and delivery format, has a structural design reminiscent of an old architectural concept. “Build up instead of out” is a way to build structures using fewer resources. Parquet follows that design by using a columnar data storage format rather than the traditional row-based format used, for example, with CSV files.
That matters because data organized by columns enables smaller file sizes, faster queries, and better support for complex data types. For data analytics, that translates to efficiency, scalability, and cost savings. Think faster property trend analysis on things like foreclosure and market insights and lower storage costs for cloud-based property databases.
Parquet files also integrate well with artificial intelligence (AI) and machine-learning solutions, such as automated valuation models (AVMs) and risk assessment tools.
File Formats and Their Features
Most data providers, including ATTOM, provide data in various file formats to meet the needs of clients. CSV and ASCII files have work for smaller datasets delivered to smaller businesses, and JSON files work well for APIs and apps. Parquet, however, combines highly compressed files, columnar format, and fast query speeds. That renders the files perfect for large-scale data analytics, big cloud, AI, and machine-learning (ML) applications.
Why Property Data Users Are Turning to Parquet
Users of big data need systems and storage that can handle the ever-increasing volume of information, especially in the form of bulk data.
Institutional Investors
Institutional investors deal with millions of property records, mortgages, and market trends. Perhaps Parquet’s biggest value add for institutional investors that use Parquet file delivery is the ability to scale and manage huge real estate datasets.
Compressed data files of historic information are perfect for automated valuation models (AVMs), pricing models, and risk assessments. For example, a query for “all distressed properties in Florida with LTV > 85%” can be completed 10x faster with Parquet vs. CSV.
Real Estate Brokerages
For real estate brokerages, Parquet file delivery makes mortgage trends, foreclosure, and distressed property tracking easier, faster, and less resource intensive. GeoParquet is a feature of Parquet that facilitates processing of geospatial datasets for mapping and website display, such as defining property boundaries and building footprints.
Fintech and Proptech
The fintech and proptech industries rely on data to deliver their products. Parquet file delivery enhances fraud detection, risk management, and customer segmentation for precision marketing and superior property and financial services.
Data Analytics Companies
Parquet’s compressed file storage model reduces the cost of data storage for data platforms. Smaller files and the columnar design enhance AI and ML analytics performance.
Why Parquet Is a Game Changer
For large-scale property data analytics, Parquet file delivery offers benefits beyond speed.
Reduced Cloud Storage Costs
Parquet compresses data up to 75% more efficiently than CSV, saving on infrastructure costs for users of Google Cloud, AWS, or Azure.
Easy Integration with Big Data and AI
Parquet integrates with real-time AI models for property valuation, risk assessment, and foreclosure prediction.
Quality Data
Parquet outperforms other file formats like CSV with strict schema definitions, preventing missing data, column misalignment, and resulting in more accurate analytic results.
Early Market Alerts
Parquet’s fast and efficient querying can track foreclosures, market liquidity, home price appreciation, and rental yields in real time. For example, a hedge fund using real estate data can make faster buy/sell decisions based on AI-driven market alerts.
Parquet’ s modern, columnar data storage format design removes the bottlenecks that other file delivery formats can experience. CSV files, for example, often create challenges for large-scale data processing. Parquet is a game-changer for institutional investors, fintech, and large proptech companies because it enhances speed, scalability, and cost-efficiencies.
To learn more about ATTOM’s data and file delivery options, contact an ATTOM property data expert.
Written by: Jennifer Von Pohlmann