dat390 | undergraduate

Database Integration With Other Systems

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This course addresses the main standards for data integration, movement or replication and federation. Students will investigate transparency and emulation, cleaning, archiving, and information preservation across systems.

This undergraduate-level course is 5 weeks To enroll, speak with an Enrollment Representative.

Course details:

Credits: 3
Continuing education units: XX
Professional development units: XX
Duration: 5 weeks

topic title goes here

    Data Warehouse Reporting and Analytics

    • Integrate the appropriate business intelligence tools into the data warehouse given selection considerations in a business case.
    • Utilize ongoing and appropriate query optimization and rewriting for a given database system.
    • Assess semi-structured data in relational DBMS.
    • Apply appropriate analytic techniques for data sets in a given business scenario.

    Schema and Data Definitions; Relationships and Discrepancies

    • Prepare a schema matching and mapping appropriate for a business case.
    • Develop appropriate metadata for a database system.
    • Resolve conflicts between heterogeneous data sources.
    • Resolve schematic discrepancies.
    • Validate data quality and provenance for use in a distributed database system.

    Complex Query Development and Optimization

    • Identify the appropriate optimization strategy that incorporates best practices and design considerations of a database system.
    • Evaluate queries for distributed data sources, source descriptions, and limitations.
    • Develop appropriate Schema SQL statements.

    Data Warehouse Integration and Data Replication

    • Recommend the appropriate database connectivity technology for given business scenario.
    • Transform data structured under a source schema into data structured under a different target schema.
    • Evaluate data relationships across data sources.
    • Prepare a database for integration with an Internet application.

    Data Warehouse Tools to Populate and Recover Data

    • Prepare data, including data cleaning, for integration into a data warehouse environment.
    • Evaluate database incompleteness, inconsistency, nulls, and consistent query answers.
    • Recommend the appropriate data exchange option using appropriate source-to-target dependencies.
    • Develop appropriate data preservation strategy for a data warehouse.
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