Professional Certificate in Cloud Data Architecture

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The Professional Certificate in Cloud Data Architecture is a crucial course designed to meet the increasing industry demand for data professionals who can design, implement, and manage secure cloud-based data solutions. This program equips learners with essential skills in cloud data architecture, big data, and data engineering, using industry-leading tools such as AWS, Microsoft Azure, and Google Cloud Platform.

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By earning this certification, learners demonstrate their ability to leverage cloud services to collect, process, store, and analyze large-scale data sets. As data becomes an increasingly valuable asset for organizations, there is a growing need for professionals who can design and implement effective cloud data architectures that comply with industry regulations and ensure data security and privacy. This Professional Certificate in Cloud Data Architecture prepares learners for in-demand roles such as Cloud Data Architect, Data Engineer, and Big Data Analyst, providing them with the skills and knowledge needed to advance their careers and succeed in today's data-driven economy.

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โ€ข Cloud Data Architecture Fundamentals: Understanding cloud data architecture and its components such as data storage, data processing, and data integration.

โ€ข Data Modeling in the Cloud: Learning how to design and implement data models in the cloud using tools like AWS Glue, Azure Data Factory, or Google Cloud Dataflow.

โ€ข Data Security and Compliance in the Cloud: Understanding data security and compliance best practices in the cloud, such as encryption, access control, and data masking.

โ€ข Big Data Processing in the Cloud: Learning how to process big data using cloud-based technologies like Apache Hadoop, Apache Spark, or Google BigQuery.

โ€ข Cloud Data Warehousing: Understanding how to design, build, and manage cloud-based data warehouses using tools like Amazon Redshift, Azure Synapse Analytics, or Google Bigtable.

โ€ข Cloud Data Lake Design and Implementation: Learning how to design and implement data lakes in the cloud using services like Amazon S3, Azure Data Lake Storage, or Google Cloud Storage.

โ€ข Cloud Data Integration: Understanding how to integrate data from various sources into the cloud using tools like AWS Data Pipeline, Azure Data Factory, or Google Cloud Dataflow.

โ€ข Cloud Data Governance: Learning how to establish and maintain data governance in the cloud, including data quality, data lineage, and metadata management.

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PROFESSIONAL CERTIFICATE IN CLOUD DATA ARCHITECTURE
ๆŽˆไบˆ็ป™
ๅญฆไน ่€…ๅง“ๅ
ๅทฒๅฎŒๆˆ่ฏพ็จ‹็š„ไบบ
London School of International Business (LSIB)
ๆŽˆไบˆๆ—ฅๆœŸ
05 May 2025
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