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SAS DataFlux Management studio training,Technical support ,Outsourcing ,DataFlux Data Management Platform
Overview of DataFlux Data Management Studio
DataFlux Methodology: Plan, Act, and Monitor
Managing Repositories
Different types of Data Connections
Creating and Managing Data Collections
Creating , Setting , Working with Data Explorations
Introduction ,Creating Business Rules and Custom Metrics
Overview, Creating , Preparing of Data Profiles

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  2. 2. DF Content DataFlux Data Management Platform Overview of DataFlux Data Management Studio DataFlux Methodology: Plan, Act, and Monitor Managing Repositories Different types of Data Connections Creating and Managing Data Collections Creating , Setting , Working with Data Explorations Introduction ,Creating Business Rules and Custom Metrics Overview, Creating , Preparing of Data Profiles
  3. 3.  Overview ,Creating Data Jobs  Creating, Building a Process Job  QKB
  4. 4. Score Board ,Model validation ,Logistic, Linear ,Cluster ,GML ,Comparing Models ,Predictive Modelling, BASEL II Model Validation & technical support ,Segmentation analysis
  5. 5. DataFlux Expression Engine Language Array Functions Blue Fusion Functions Boolean Functions Database Functions Data Input Functions Date and Time Functions Event Functions Execution Functions External File Functions Information/Conversion Functions Logging Functions Testing and Evaluating  Selecting Output Fields  Sub-Setting  Initializing and Declaring Variables  Saving Expressions  Counting Records  Debugging and Printing Error Messages  Creating Groups  Retrieving and Converting Binary Data
  6. 6. Defining business rules Data profiling with business rules and alerts Data jobs with business rules Data jobs with monitoring tasks Working Through the MONITOR Phase of the DataFlux Methodology(Business Rule creation)
  7. 7. Data Input Nodes Data Source SQL Query Text File Input Job Specific data
  8. 8. Data Output Data Target (Insert) Data Target (Update) Delete Record HTML Text File output Frequency Distribution
  9. 9. Data Integration Data Sorting Data Joining Data Joining (Non Key) Data Union SQL Look Up SQL Execute Parameterized SQL Query
  10. 10. Utilities Expression Data Validation Concatenate Branch Sequencer Field Layout
  11. 11. Profile   Pattern Analysis  Basic Statistics  Frequency Distribution  Basic Pattern Analysis
  12. 12. Entity Resolution  Match Codes  Clustering  Surviving Records Identification 
  13. 13. Quality Gender Analysis Identification Analysis Parsing Standardization Standardization (Parsed) Change Case
  14. 14. DataFlux Data Management  The DataFlux Data Management Platform enables you to discover, design, deploy and maintain data across your enterprise in a centralized way.  The following diagram illustrates the components of the platform
  15. 15. Overview of Data Management Studio  DataFlux Data Management Studio is a data management suite that combines  Data quality,  Data integration,  Master data management.  It provides a process and technology framework to deliver a single, accurate and consistent view of your enterprise data.  Data Management Studio gives you the ability to:  Merge customer, product, or other enterprise data  Unify disparate data through a variety of data integration methods (batch, real time, virtual)  Verify and complete address information  Integrate disparate data sets and ensure data quality  Transform and standardize product codes  Monitor data for compliance in batch or real time  Manage metadata hierarchy and visibility
  16. 16. DataFlux Methodology: Plan, Act, and Monitor  The main activities in the DataFlux methodology are as follows: I. Plan - Identify patterns and problems in your data. II. Act - Create processes to improve data quality and data integration. III. Monitor - Monitor your processes for data quality and data integration
  17. 17. Overview  1Main Menu — Enables you to select features that are active in the current context. For more information, see Main Menu.  2Navigation Pane —Enables you to navigate riser bars, trees, and folders.  3Navigation Riser Bar — Enables you to select riser bars that display a set of related features. For more information, see Information Riser Bar, Data Riser Bar, Folders Riser Bar, Business Data Riser Bar, Data Management Servers Riser Bar, or Administration Riser Bar.  4Status Bar — Displays status messages, current server logins, and similar information.  5Information Pane — Contains one or more portlets that display information, such as a list of the files that were last accessed, or details about a selected item.  6Title Bar — Displays the product name.  7Portlets — Components that display information, such as a list of the files that were last accessed, or details about a selected item.  8Toolbar — A set of icons that enable you to access context- sensitive features with one click.
  18. 18. Overview of the Job Dialog  1Home Tab — Click this tab to return to the main window, so that you can select or open another item from the Riser Bars.  2Resource Pane — Contains components such as the Nodes tree, the Folders tree, and the  3Help Area. Help Area — When a node is selected in the Nodes tree, a brief description of the node is displayed in the Help Area, along with a link to the help topic for that node.  4Details Pane — Displays tabs for the selected node, a log for the current job, and other information about the selected item.  5Work Area — The area where you build flows for data jobs and process jobs.  6Secondary Toolbar — A set of icons that enable you to access context-sensitive features that are appropriate for the work area.  7Secondary Tabs — A set of tabs for the current job or a node that is selected within the job.  8Detach Tab — Click this tab to detach the job dialog from the main Data Integration Studio window.  9Primary Tabs — Each open job has a primary tab.