In recent years, technology models have evolved towards subscription and pay-as-you-go services, taking advantage of the capabilities of the cloud and the flexibility of providers. Businesses can now access infrastructure and a wide range of software to meet their business needs. This environment of massive information consumption has driven the growth of Data as a Service (DaaS) models.
The concept of “Data as a Service” offers a new perspective on the storage and provision of information, based on access to high-quality, value-added data through cloud services. This model replaces or complements hosting, part of the processing and, sometimes, analysis in intermediate layers with a DaaS subscription, allowing information to be obtained ready for use.
This approach transforms the way companies develop analytics solutions and artificial intelligence models. By providing access to vast, diverse and up-to-date data sets, DaaS allows organizations to customize their solutions more accurately and efficiently.
Pedro Julián Domínguez, Alliance Manager of Innova-tsn explains that, “By combining the flexibility of cloud services with the richness of data, DaaS becomes a strategic ally for companies seeking to obtain a competitive advantage in a market increasingly driven by the good use of information” .
DaaS in the enterprise
Aware of the current situation of the technological market and customer demands, the experts at Innova-tsn, a leading consulting firm in the comprehensive life cycle of data, have identified doubts, challenges and benefits when adopting this approach:
- Data origin: They can come from various sources, including the provider’s own data, third-party data, or data generated by customers.
- Benefits: Savings in time and resources, pay per use in infrastructure, storage and processing, access to high quality data, greater agility, more potential for innovation and greater ability to customize solutions.
- Risks: Potential vendor lock-in, compromised data security and quality if vendor does not provide adequate guarantees. It is crucial to select a suitable partner based on existing needs.
Based on the experience with its clients, Innova tsn, a leading consulting firm specialized in the integral life cycle of data, includes in this decalogue the challenges and benefits of DaaS
- Recipients: Any company that needs data to make more informed decisions, even those with their own storage systems.
- Operation: Once the subscription is contracted, organizations access the data through an interface or API.
- Data Examples: Demographic and socioeconomic data, market data from various industries, data from sensorized environments, social media data, financial and transactional data, genomic data, etc.
- Suppliers: Companies specialized in data and large hyperscalers such as AWS, Azure or GCP.
- Solution customization: DaaS allows you to segment information, enrich and access new data in an automated and updated way. The right partner makes it easy to create highly customized AI models.
- Development Acceleration: By working with preprocessed data, DaaS accelerates development and enables faster iteration of analytical models.
- Innovation: Facilitates the discovery of new business insights, allowing more time to develop innovative solutions based on data.
