Advanced Certificate in Data Warehousing: Data Storage
-- ViewingNowThe Advanced Certificate in Data Warehousing: Data Storage is a crucial course for professionals seeking to excel in data warehousing. This program focuses on teaching learners essential skills in data storage, addressing industry demand for experts who can design, implement, and manage effective data storage solutions.
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⢠Database Design and Modeling: This unit will cover the best practices for designing and modeling databases for data warehousing. It will include topics such as normalization, dimensional modeling, and data modeling tools.
⢠Relational Database Management Systems (RDBMS): This unit will focus on the use of RDBMS for data warehousing, including SQL, data integrity, and data manipulation. It will also cover the differences between RDBMS and other database management systems.
⢠NoSQL Databases: This unit will explore the use of NoSQL databases for data warehousing, including key-value stores, document-oriented databases, column-family databases, and graph databases. It will also cover the benefits and drawbacks of using NoSQL databases compared to RDBMS.
⢠Data Warehouse Architecture: This unit will cover the different architectures for data warehousing, including traditional, cloud-based, and hybrid approaches. It will also cover the components of a data warehouse, including the staging area, the integration area, and the access area.
⢠Data Marts: This unit will focus on the design and implementation of data marts, which are smaller data warehouses that are used to serve the needs of specific business units or departments. It will cover topics such as data mart architecture, data mart modeling, and data mart deployment.
⢠ETL (Extract, Transform, Load) Tools: This unit will explore the use of ETL tools for data warehousing, including the process of extracting data from various sources, transforming the data to fit the needs of the data warehouse, and loading the data into the data warehouse. It will cover topics such as ETL design, ETL implementation, and ETL testing.
⢠Data Warehouse Optimization: This unit will cover the best practices for optimizing the performance of data warehouses, including caching, indexing, and partitioning. It will also cover the use of data warehousing performance monitoring tools and the process of tuning SQL queries for optimal performance.
⢠Data Security and Privacy: This unit will focus on the importance of data security and privacy in data warehousing, including data encryption, data access controls, and data masking. It will also cover the legal and regulatory requirements for
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