With data-driven decisions and digital services at the center of most businesses these days, companies can never get enough data to power their operations. But not all data that could benefit a business can be easily produced, cleaned and analyzed by internal means. Enter data providers as a service: Entities that offer data on tap for a fee that your business can use.
Who needs Data as a Service (DaaS)? Anyone with a business who craves data and needs it to be trustworthy, loyal, useful, or one of many useful roles. Sometimes the data offered by DaaS providers comes from their internal workings or from their own business operations. Sometimes it comes from external, often open, sources gathered by the DaaS provider to help companies leverage data assets they otherwise couldn’t manage themselves.
DaaS offerings have been evolving for decades, but developers recently recognized that a cloud model, with its flexible, usage-based pricing, could more easily help businesses connect to the data sources that providers are looking to monetize. . And it’s not just about the offered data itself. DaaS providers can also improve the quality of data an organization might otherwise collect on their own by fixing errors or filling in gaps and even providing large chunks of data if you need more. This way, DaaS providers can enhance your in-house data warehouse by fertilizing it with other curated sources.
The region is developing rapidly. Some DaaS vendors emphasize the ability of their tools to manage information, analyze data, create reports, and support decision making. Others push the data themselves, knowing that having too much data is like being too rich or too thin. Everyone is in the market for information about their competitors, customers, internal operations, and the world at large.
Many tools also follow the current fashion of making development easier and smarter. The low-code and no-code options make it easier for anyone to click a few buttons and produce a report or download a data-laden spreadsheet, all without running a never-ending series of developer meetings. The companies also point to their links to good AI algorithms and data science options.
Here are a number of options available to help you meet your DaaS needs.
All major cloud computing companies maintain a large collection of open datasets for their customers. In many cases, the data is free and provided as an incentive to use local IT services. The data is usually already converted and sometimes enhanced as it is converted to local format for easy integration with your code. The datasets include many large government collections such as weather data, as well as a few surprises. Azure Open Datasets, for example, includes census data and crime data as well as some datasets focused on understanding global climate change. AWS Open Data includes a variety of genomic data and the Common Crawl, a collection of 50 billion web pages. Google Cloud datasets include patents, weather information, and Google’s own data produced by tracking web searches and analytics.
Three big companies – Experian, TransUnion, and Equifax – tracking how we borrow and repay all of our loans with the aim of calculating scores that are supposed to measure how confident we can be in the future. In the past, the scores themselves were rather mysterious and hidden, but lately banks and credit card companies are sharing scores directly with customers in an effort to encourage better behavior.
The credit agencies themselves don’t just work with lenders. Equifax, for example, wants to tackle bigger issues like workforce management, fraud, identity theft, and marketing. Knowing how much people earn and how they spend and repay loans can be useful in predicting a variety of issues for industries as diverse as healthcare, automotive, manufacturing, and retail.
Now, credit agencies are exploring new ways to provide answers. Equifax Ignite, for example, is a cloud-based tool that allows you to analyze Equifax data without sensitive personal information leaving Equifax machines. It produces sophisticated analytics under multiple layers of security and compliance.
Keeping up with the growth and development of every small business in the world is not easy. Enigma collects information from a variety of government agencies and open sources before blending anonymized transaction-level details provided by credit and debit card banks. If money talks, understanding cash flow is the quickest way to understand the nature of a business.
Much of the information you might want is often already available on websites. HIRinfotech specializes in scraping into databases and then analyzing them. The company collects price and product data across dozens of industries such as travel and financial services. Businesses can work directly with the data and reports or create similar reports using some of the Robotic Process Automation (RPA) tools built into the extracted information.
Marketing teams that need clean, up-to-date contact information can turn to Informatica to organize and update their contact lists. The company’s service mixes verification and enrichment. First, addresses and phone numbers are double-checked against address databases and national Do-Not-Call databases. Then, Informatica adds details from trusted business and consumer sources to create an enhanced contact record.
Marketers looking for better sales insights and opportunities to open lines of communication are prime targets for Oracle’s DaaS product. The DaaS database maintains up-to-date primary and secondary contact information for a wide range of businesses. Instead of struggling to keep your Rolodex up to date, the tool will import new and updated names and contacts into your software. If you are using other Oracle tools, such as Eloqua, the import path is already debugged.
Developers who need information about places on a map and the people who live there turn to Precisely. Its demographics APIs, for example, take an address or location and return a set of aggregate statistics about people and households within the search radius. Residential and commercial real estate parcels are tracked with the Property API. Some businesses use the data for real estate transactions and store location planning, but others use the database to simplify the checkout process for online retail by finding an accurate address with Typeahead search. . The company also builds a connection of data processing tools to simplify the development of better analytics.
The US Census Bureau locks down responses for 72 years to protect Americans’ privacy, and it can be a long wait to perform an analysis of the data. RTI took a different approach. Instead of providing personalized information, it created a synthetic dataset that mimics real data in many important ways. If there are 58 people in a block in the real census, you will find close to 58 entries in the synthetic data set as well as made up details that try to approximate the real values. Anyone trying to analyze census data can run their algorithms without worrying about personal data. The answers might not be exactly the same as using the real thing, but for many questions the answers will be pretty close. And that’s better than waiting 72 years.
Companies with data turn to Snowflake to store and analyze it instead of building their own infrastructure. The company offers a scalable, maintenance-free option that ingests structured and semi-structured data and then offers a variety of standard reporting and AI services. The Data Marketplace also allows users to buy and sell their data to improve the quality of information through cross-fertilization. Some of the datasets featured include market research from MSCI or S&P Global and COVID epidemiology data from Knoema or Starschema. There is a wide range of datasets for a wide range of topics ranging from demographic studies to marketing, media or sports, including fantasy football.
Street lighting data
Organizations involved in urban planning and the design of transportation networks need to understand what residents do on city streets. Streetlight Data tracks everyone using anonymized cell phone records and government sources to create a detailed model of when people should move around the city. With Streetlight Data, businesses can get accurate measurements of people flow without having to build their own sensor networks.
Generally, DaaS companies collect real information about the world. Synthesis AI, however, creates its data using some of the 3D models and CGI techniques that power video games and Hollywood action movies. If you want to train your machine vision routines, perhaps to build a self-driving car, you can find as many test cases as you need. Maybe your algorithm needs to test a street full of drunken pedestrians at Mardi Gras? Or maybe a scene at dusk right after a theater lets everyone out? Or are you just worried about the ethical issues of working with video footage of real children? Synthetic data is faster and more complete than anything you can generate with a film crew.