Data as a Service (DaaS) is a cloud-based model that allows companies to access, manage, and analyse data on demand, without the need for extensive on-premise infrastructure.
DaaS provides data, typically through APIs, web services, or other interfaces. This model enables businesses to access a wide range of data sources, including public databases, proprietary data, and aggregated data from various channels.
It can also generate value for your company, diversifying your service line.
Data As a Service process
To create new services based on data we first need to manage and expand your data portfolio:
1. Data Scouting
Map and evaluate data providers and consumers to conduct a deep technical inspection of offered data and services to expand your data portfolio.
The Data Scouting Service is a quick and effective solution to discover opportunities for acquiring or exchanging data. It maps and evaluates the data providers and consumers directly related to your business and conducts a deep technical inspection of offered data and services.
The mapping process helps your organisation consolidate and expand collaborations, contract providers, identify the right data partners and test their offers.
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- PREP: Preparing criteria for profiling and pre-selecting data sources.
- SCOUTING: Identifying data sources that meet the pre-selection criteria.
- ANALYSIS: Profiling data suppliers and data solutions, classifying offers by cost and added value.
- EVALUATION: Inspecting and evaluating quality of demo data samples.
- PRESENTATION: Interactive digital map of data offers and acquisition conditions, written report.
2. Data enhancing
Evaluate, enhance and consolidate your core data. High-yield low-cost data improvements, eliminating major causes of bias, imprecisions, and noise.
Mosaicfactor’s data assessment platform includes expert inspection and evaluation tools compatible with any type of data. The tools help to verify the data quality, consistency, precision, density, and privacy compliance, and detect possible bias in the data.
We use our Data Assessment Toolkit:
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- Evaluate your core data, and assess its compatibility with critical planning, forecasting, and analysis applications.
- Identify high-yield low-cost data improvements, that eliminate major causes of bias, imprecisions, and noise in the data.
- Enhance and consolidate real-world data, in order to obtain more precise AI models and more reliable AI-based solutions.
3. Generate Data as a service offering: we help extracting value from data by using DaaS to provide valuable information to different stakeholders.
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- Data Provisioning: offering access to diverse datasets, addressing specific data needs that might be challenging to fulfill independently.
- Data Management: handle the storage, organisation, and maintenance of large datasets, ensuring compliance with regulations and managing data access rights.
- Data Analytics: integrate DaaS offering including analytical tools, allowing businesses to derive insights from the data they access.
Typical use cases DaaS can help with are:
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- Operational Efficiency: by analysing operational data, businesses can identify areas for improvement and optimization of their processes.
- Customer Insights: DaaS can provide detailed customer data, enabling personalised marketing and improved customer service.
- Market Analysis: companies can use DaaS to access market data and trends, helping them make informed business decisions.
Benefits for companies
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- Cost Efficiency: by outsourcing data management to DaaS providers, companies can reduce the costs associated with maintaining their own data infrastructure.
- Scalability: DaaS solutions can easily scale to meet the growing data needs of a business, providing flexibility as the company expands.
- Accessibility: data is available on demand, regardless of the user’s location or infrastructure, making it easier for businesses to access and use data when needed.
- Focus on Core Activities: with data management outsourced, companies can focus more on their core activities and strategic goals, rather than the complexities of data handling.
Data as a Service offers a flexible, cost-effective, and scalable solution for companies to manage and use data, driving better decision-making and operational efficiency.
