Among the accumulation of all kinds of Software as a Service, Platform as a Service, Infrastructure as a Service, Desktop as a Service and Healthcare as a Service, another *aaS proudly raised its head - Data as a Service.
As part of an article in The Economist, James Cortad, a researcher working for IBM, once said that the world has entered a fundamentally new period of existence because there has never been so much data before. Joy Hellerstein, a professor at the University of California at Berkeley, said that we live in an era of an industrial data revolution.
First, let's turn to Wikipedia - what does the omniscient web oracle say about DaaS? Data as a Service is the cousin of SaaS - software as a service. Like all members of the large *aaS family, DaaS is based on the concept that a product (in this case, data, sorry for the tautology) can be provided to the user on demand, regardless of its geographical location or organizational separation between the supplier and the consumer. And if before data provided as a service were used primarily in mashups, today they are increasingly used for commercial purposes, as well as by non-profit organizations such as the UN.
Mashaup is a web application that combines data from multiple sources into a single integrated tool. For example, when we combine Google Maps with real estate data from Craigslist, we get a new unique Internet service that was not originally offered by any of the data sources.
Marketers are constantly analyzing data and making all sorts of calculations. However, how many of them can say which companies or which consumers are exactly interested in their products or services? The new Data-as-a-Service approach enables companies to use real-time data to solve their most complex marketing challenges. In fact, DaaS is completely revolutionizing marketing by creating real-time insights and turning revenue generation from Big Data is no longer a ghostly, but a very real possibility.
WHAT IS DAAS?
In the vast amount of information that marketing systems collect, there is a large amount of valuable and accessible data hidden. We live in the world of Big Data, therefore all the information generated by mankind can be used without problems in real time to obtain those opportunities that even science fiction writers could not dream of before.
Data as a Service is a new approach that mines and structures unique data and Hard-to-Find Data (HTFD) to generate a steady stream of leads, including a company's own customers. These data sources are a very finely tuned marketing tool that disparate and “one-off” lists of potential customers cannot match.
The first DaaS approach was taken by Factual, founded by Gil Elbatz in 2007. He decided to create an open repository similar to Flickr, but only for data. Today, the range of data in Factual is huge: from computer games to information obtained from government agencies. Access to data is carried out both in manual mode and using an open API. Factual's bet is a market that will exceed $100 billion.
In the case of DaaS, all customer and market information is delivered directly to the company's multi-channel systems or digital marketing platforms, allowing marketers to send messages, personalized recommendations, and highly targeted content to customers in real time.
HOW DAAS WORKS?
The new approach combines three types of data that are uniquely customized for each individual company:
- Primary data. 1st party data, which are merged with 3rd party and HTFD. As for the latter, these special hard-to-find datasets are aggregated from hundreds of Big Data sources and go far beyond third-party data. Examples include highly specialized furniture data sources or high fashion user interests.
- Embedded data. This is offline data that has been converted to online address data. This data type provides new opportunities for and opens up prospects in a constantly changing digital universe. Targeted ads can be shown to specific customers or audience segments. For example, a car company might show ads to people whose leases are due to be renewed.
- Fast data. User behavior data that determines purchase intent in real time. An example would be statuses on social networks, such as “We have a baby” or “We are going on vacation with the whole family.”
UNIQUE DATA SETS
To understand the full potential of unique datasets delivered via DaaS, such as HTFD or fast data, it is important to understand where they come from. The information generated from Big Data can be divided into six specific categories:
▪ Web Mining. This is data that is freely available on the Internet. This category of data collection includes automated processes for discovering and extracting information from web documents and servers, including the mining of unstructured data: information extracted from server logs, information about user activity from browsers, information about site structure and links, or data obtained from content and documents.
▪ Search data. Information obtained as a result of the search activity of the user in the browser. This data identifies digital audiences through online identifiers assigned to each user.
▪ Social networks. The average Internet user spends about two and a half hours a day on social networks. Thanks to this, companies get access to a huge amount of data, which is based on personal preferences of consumers, likes, registrations, comments and reposts.
▪ Crowdsourcing. Data that is collected from various sources, including large communities, forums, surveys, studies, etc.
▪ Transaction Data. Data generated during business activities - purchases, inquiries, insurance claims, deposits, cash withdrawals, airline bookings, credit card purchases, etc.
▪ Mobile. Mobile data is driving the biggest data growth. This is not only information about the use of smartphones and user preferences for certain models, but also information obtained using mobile applications or other services running in the background.
A prime example of Data as a Service is Oracle DaaS for Customer Intelligence. This is a product that combines data about the company's customers from all channels, both social and corporate, and aggregates information about their activity, intentions, moods, keywords, etc. By combining unstructured data, Oracle has provided the ability to identify relevant topics, prevent possible problems, better understand what is called consumer brand perception, constantly improve customer activity analytics and make effective decisions on the development of their products.
For years, companies have relied solely on their internal or stagnant third-party data. DaaS, on the other hand, is a revolutionary way to get global datasets that can be successfully used to find new customers.
Why focus on families who might be interested in a family vacation when you can immediately reach out to those who have just booked plane tickets? Or why bother trying to figure out who to target with an ad campaign when you can use daily data feeds of potential customers who are actively searching the web for the product you're selling? The possibilities of Data as a Service are truly endless.
Instead of focusing on developing and managing a complex data network, companies can focus solely on their business results and the marketing benefits of Big Data. Getting immediate income from Big Data – a universal challenge facing many marketers, and DaaS makes this possible for any company, regardless of its industry affiliation. And if all this leads to the liberalization of the data world, then the game is worth the candle.
Materials of Forbes, Business 2 Community, Simple Talk, InfoWorld, DATAVERSITY.
