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Cloud Data Infrastructure involves the design, implementation, and management of a scalable and reliable data storage and processing environment in the cloud.

Cloud storage setup

Configuration of cloud-based storage solutions, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage, to store structured and unstructured data securely and durably in the cloud.

Data processing framework

Implementation of data processing frameworks and tools, such as Apache Spark, Hadoop, or Google Cloud Dataflow, to perform data transformations, analytics, and batch or real-time processing on large datasets.

Database management

Deployment and management of cloud-based databases, such as Amazon RDS, Google Cloud SQL, or Azure Cosmos DB, to store and manage structured data efficiently for transactional and analytical workloads.

Scalability and elasticity

Design of the infrastructure to scale seamlessly based on demand, allowing businesses to handle growing data volumes and workload spikes without performance degradation.

Data integration pipelines

Development of data integration pipelines to ingest, cleanse, transform, and load data from various sources into the cloud data infrastructure, ensuring data consistency and reliability.

Security and compliance

Implementation of security measures such as encryption, access controls, and data governance policies to protect sensitive data and ensure compliance with regulatory requirements such as GDPR, HIPAA, or PCI DSS.

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