SAS MASTER DATA MANAGEMENT TRAINING ,SAS MDM SYLLABUS

1. MASTER DATA MANAGEMENT
Installation,Administration, ONLINE /CLASS ROOM
/CORPORATE TRAINING
,technical support
Training /Technical Support
bidwhm@gmail.com

2.  SAS MDM is a merge
◦ Software
◦ Templates
◦ Documentation
◦ Data models,
 Helpful to maintain a master entity database

3.  The SAS MDM hub is a set of tables and table
relationships that contain entity information
 This hub provides end-users or other applications with
a complete view of an entity and its relationships with
other entities

4.  SAS MDM performs the following functions:
 Extracts business information from your data sources
 Validates and standardizes the data
 Captures data errors through user-defined business
rules and sequesters the data for review and correction
 Consolidates the information into a single view of the
information available from all the data sources

5.  Help us to discover which enterprise systems contain
entity information and the attributes

6.  Managing Entities from the Master Data Management
Tab
 Searching Entities
 Quick Search
 Field Search
 Deep Linking to Master Data

7.  SAS MDM is used for Phased deployment approach
achieving a single view of customers, products and
other important entities across both traditional and big
data sources.
 It will give you a more complete view of your business
and help you gain insight for smart decisions
 Data quality and Data governance to data visualization

8.  Day-to-day success,
 SAS MDM, you can achieve a single, unified view of
your most important assets to increase revenue,
reduce costs and manage risk.

9.  Start small and build out as necessary for reduced risk
 Understand every aspect of your organization
 Improve customer experience and reduce costs
 Achieve high-quality, consistent data and pervasive
data governance
 Foster collaboration between IT and business
 Gain a deeper, more complex view of relationships

10.  SAS MDM empowers you to govern consistent data,
achieve a single view of your business and implement
more effective processes
Embedded data quality
Source system harmonization
Multidomain data model
Integrated data governance
Big data access and integration
Built-in data visualization and reporting
Unified, web-based dashboard

11. Embedded data quality
• SAS MDM is built on data quality technology to help
you standardize and rationalize data during its life
cycle. Processes include:
• Data access and integration.
• Data profiling.
• Address verification, standardization, parsing.
• Data matching, linking and householding.
• Data rule monitoring.
• Improved cross-field matching for easier creation of a best record
that matches across distinct columns.

12.  You can create master data domains for party (citizen,
customer, patient, etc.), organization, site, supplier,
product, asset or other data elements.
 You can also: Identify and centralize key core reference
data.
 Grow from batch-oriented maintenance to real-time
application integration through SOA.

13.  The ability to add, modify and retire entities and
relationships.
 Role-based access to attribute content, allowing only
authorized individuals to view sensitive at tribute
content.
 Managing metadata that spans data management and
analytics for entities, attributes and transformations.

14.  SAS Data Management Console is a browser-based
central management dashboard that enables you to:
 Access all role-based MDM interfaces from a common
location.
 Experience role-based access to MDM entry points.
 Create business rules, data quality procedures and data
definitions from within the same environment

15.  Get your MDM program up and running faster with
streamlined installation and deployment.
 Common installation standards mean SAS MDM is
compatible with other SAS products, eliminating
installation and interoperability issues.

16.  Detect data problems early, before they can cause
problems downstream. You can:
 Design and publish workflows for governing MDM
stewardship (and other) processes.
 Rely on workflows to perform case management of
issues flagged during MDM operations, and allow for
run-time drill-through of tasks associated with active
workflows.

17.  Access, integrate and publish data to sources such as
Hadoop (via Apache Hive) and Impala in addition to
numerous traditional relational database engines.

18.  Gain more administrative control over how source data
is prepared and managed prior to loading data into the
hub.
 Load and update data from individual contributing
source systems.

19.  Training /Technical Support
 bidwhm@gmail.com