Improved security, better business performance in a multi-cloud environment (without taking on more IT infrastructure), greater flexibility, reduced cost and complexity, and quicker time to extracting value from customer data are among the many reasons enterprise companies are pivoting to a data cloud architecture.
However, without a clear strategy for ensuring data readiness, many of these promised benefits remain out of reach, turning cloud investments into expensive storage rather than engines of business value. A clear data readiness strategy reduces many gaps in infrastructure, applications, data and skills that have the potential to hinder business goals.
Primary data readiness objectives – making data both right (complete, accurate, timely) and fit-for-purpose (actionable, trusted, compliant) – are a prerequisite for effective cloud management, for migrating and managing data in the cloud, and for maintaining the quality, accessibility, and governance of customer and business data over its lifecycle.
Maintain Control of the Single Customer View
A data readiness platform that operates on a primary customer database within a data cloud and creates a unified profile of a customer, household or business entity is a key first step in cloud data management. By making the profile accessible and available in real time to any application that needs it, a data readiness platform provides the enterprise with an actionable single customer view while minimizing data movement and replication, leading to better performance at lower cost, with better governance – security and compliance, but also lineage, usage patterns, quality standards.
Costs are controlled because data readiness produces clean, unified and fit-for-purpose data before it is activated, preventing unnecessary data movement or redundant processing within the data cloud. Minimizing compute and storage costs yields greater efficiency, ensuring optimal business outcomes both by not having to manage messy data, and because the business operates with a firmer understanding of the customer – fewer duplications, more targeted marketing, relevant CX, etc.
In this way, the enterprise controls their data – and the cost of managing data – all while having control and visibility into the building of the unified profile. And, by maintaining a data-in-place environment, the enterprise is able to execute queries and processes directly within the data cloud, ensuring that no data persists outside of the environment.
API Accessibility
With a data readiness platform deployed on a data cloud, organizations can easily handle, store, and examine large amounts of customer data in a quick and adaptable way, helping them get immediate insights and customize customer experiences. And with near-infinite scalability in a cloud-based architecture, organizations ensure that their infrastructure grows with the business as CX, AI and other use cases evolve.
Additional flexibility comes from a data readiness platform that offers bi-directional APIs from data ingestion through to activation. This capability ensures that data is ready and fit-for-purpose across the customer data lifecycle, available to any external touchpoint, outbound service provider, or marketing channel – and for modeling and analytics.
Data Readiness as You Define It
Another reason a data readiness platform is ideal for managing customer data in a data cloud is that composable services give organizations the option to use only what they need.
When data quality, identity resolution, and audience/segment selection are core features of a data readiness platform, an organization does not have to outsource these activities to another application – or write code. Instead, with a platform that offers composable services and APIs for identity resolution, customer profiles, segmentation, data orchestration and real-time interactions, the platform brings together the various pieces needed to perform a complete business process or function in one environment. The platform then becomes the single source of truth for customer data, maintaining a consistent understanding of the customer, household or other entity across all applications connected to the data cloud.
A robust, enterprise-ready data readiness platform should provide:
- Automated Data Ingestion and Data Quality: Handling all enterprise data at the cadence of the customer.
- Identity resolution: Tunable for any use case while delivering complex and accurate customer profiles using probabilistic, deterministic and machine learning techniques.
- Segmentation and activation: Using selection rules and models to dynamically and precisely segment audiences and power superior CX at every touchpoint.
Using these composable services, an organization can deploy data readiness capabilities where and when they are needed, including as part of enterprise data services or agentic workflows.
Ready to maximize your data cloud investment with a data readiness strategy? Learn how Redpoint can help you deliver immediate CX and AI value with clean, connected, compliant data in your data cloud environment: Data Readiness Hub – Redpoint Global
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