Oracle Data Warehousing Online Training and Placement

  Oracle Data Warehousing Training for OPT CPT Students

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Oracle Data Warehouse Online Training


Oracle Data Warehouse Online Training Course Content:


Introduction to Data Warehousing

  • Identifying data warehouse components
  • Analyzing failed installations
  • Top-down vs. bottom-up approach
  • Selecting the appropriate technique for your environment

Establishing Dimensional Modeling


Modeling the business process


  • Relating business processes to dimensions with a Bus Matrix
  • Reviewing denormalization techniques to optimize database read performance
  • Identifying the advantages of Star Schemas over Snowflake Schemas
  • Differentiating between normalized and renormalized system design
  • Enabling drill-up and drill-down reporting through the use of hierarchies

Building fact tables


  • Setting the grain of your fact tables to maintain a balance between flexibility and performance
  • Identifying primary keys and foreign keys
  • Tailoring business analysts' needs through the use of summary tables

Creating dimensions


  • Resolving date dimension issues
  • Exploring connections between separate events with conformed dimensions
  • Increasing model flexibility through the use of role-playing dimensions
  • Substituting surrogate keys for natural keys

Building the Data Warehouse


Architecting the physical database


  • Mapping the logical data model to the physical data model
  • Evaluating hardware considerations
  • Choosing a method of data storage
  • Indexing and materialized views for performance

Ensuring data quality


  • Profiling source data
  • Configuring the database for change data capture
  • Refreshing the data warehouse

Extracting data from multiple sources


  • Connecting to different data sources
  • Databases
  • Spreadsheets
  • Text files

Transforming data during migration


  • Cleansing and scrubbing data
  • Mapping data elements and data types
  • Conforming dimensions and facts

Loading data into a data warehouse


  • Employing a staging database
  • Automating incremental data loading
  • Verifying success for data integrity

Leveraging BI for Data Analysis


Identifying levels in the BI stack


  • Demonstrating SharePoint as a deployment platform
  • Utilizing Excel as a client tool for data analysis
  • Querying data from the OLAP server

Exploring business intelligence tools


  • Multidimensional cubes
  • Slicing and dicing your data
  • Surfacing Key Performance Indicators (KPIs) to evaluate the health of your organization

Deploying a Complete Data Warehouse Solution


Taking advantage of industry-standard data-mining techniques


  • Identifying data-mining methodologies
  • Choosing the right data-mining tasks based on organizational needs

Planning for the future


  • Big Data and the impact on traditional data warehousing
  • Supplementing the traditional data warehouse to handle unstructured data
  • Dealing with large data sets via Hadoop

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