Data Protection Regulation has become the model for many national laws outside the EU, including the United Kingdom, Turkey, Mauritius, Chile, Japan, Brazil, South Korea, Argentina and Kenya, and formed the basis for the California Consumer Privacy Act. Another component of the business model is about ensuring that the customers may receive and use data to improve their own value propositions (products, services). In this business model, data provides value as a support mechanism or a tool for creating other value propositions, that's why the revenue stream is typically quite a bit lower. In turn, Data as a Service is one of 3 categories of big data business models based on their value propositions and customers: Answers as a Service; Information as a Service; Data as a Service. Use of DaaS business model in different areas Data as a Service vendors use different types of data to provide services in different areas of business. For example, People Data Labs is collecting public data about people for their customers could empower recruiting platforms, create AI models, custom audiences, etc. In the field of financial technologies consumers’ financial and behavior data are being collected and aggregated to help organizations to make better decisions to increase profitability and reduce risk in lending, to provide services to business, government and individuals. One more segment of DaaS vendors assemble mobile operators’ data to provide various types of services. For example, oneFactor platform where other businesses (telecoms, banks, retailers, payment systems, etc.) may monetize their own data by processing and enriching it with additional information, building machine learning models and launching them in production. There are companies in the DaaS market which offer weather forecasting services based on meteorological data collected around the world. Benefits Data as a service operates on the premise that data quality can occur in a centralized place, cleansing and enriching data and offering it to different systems, applications, or users, irrespective of where they were in the organization, or on the network. DaaS undertakes to provide the following advantages: Agility – users can move quickly, due to the simplicity of data access, and not needing extensive knowledge of the underlying data. Data structures and location-specific requirements can be modified to meet user needs. Cost-effectiveness – providers can build the base with the data experts and outsource the presentation layer, which makes for very cost-effective user interfaces and makes change requests at