The document discusses the importance of data governance, data quality, and master data management for business success. It notes issues that can arise from a lack of data quality and master data management, such as bad decisions from incorrect data, duplicate customer records wasting money, invoices going to the wrong addresses, and regulatory penalties. It then outlines different approaches to data quality and its relationship to master data management. The document also provides an example of how master data elements relate to a single transaction and explains why managing these elements is important for meaningful data analysis. It promotes Oracle solutions for data relationship management, data governance, and data quality to help organizations properly manage hierarchical master data across systems.

1. ALL THE INGREDIENTS FOR
SUCCESS: DATA
GOVERNANCE, DATA
QUALITY AND MASTER DATA
By : Soheil Zarei

2. INTRODUCTION
Soheil Zarei
M.Tech Software Engineering JNTU Hyderabad India
Oracle Fusion Middleware Consultant
Oracle Business Intelligent Consultant
Email : soheil.zarei@gmail.com
Telegram : @sohzarei

3. LACK OF DQ AND MDM ISSUES
1. Bad decisions made in the past, based on reports with wrong or
missing information
2. The costs of duplicate data in your customer master database
3. Cash flow being negatively impacted because invoices are going to
the wrong customer email addresses
4. Penalties incurred for not complying with regulations on customer
data and privacy
5. Information-heavy projects that run over time or require lengthy
rework after go-live
6. IT staff spending a lot of time re-integrating

4. DATA GOVERNANCE, DATA QUALITY
AND MASTER DATA MANAGEMENT
1. Data quality independently, which is good for cleaning data
inside an application or as it’s being moved into another
application
2. Data quality as a first step towards MDM, which allows you to
start with one application knowing that MDM will be introduced
as more applications get into the act
3. Data quality in parallel with an MDM implementation, which
is good for cleaning up and standardizing data across multiple
applications

5. DATA QUALITY INDEPENDENTLY
Some client base has included many clients
where they have struggled with an enterprise
resource planning (ERP) or customer
relationship management (CRM) application that
didn’t have any built-in data quality
capabilities.
Another scenario that comes up frequently is a
business intelligence or data warehousing
application, where the data being extracted
from the operational systems is – after some
basic analysis – too “dirty” to bring into the

6. DATA QUALITY AS A FIRST STEP
TOWARDS MDM
Data quality as a first step towards MDM can be
a powerful strategy, because it allows you to
ease into MDM in manageable phases, and get
distinct business value at each stage. Think big,
start small has become a piece of conventional
wisdom in the MDM world, and this is a great
way of doing that.

7. DATA QUALITY IN PARALLEL
WITH AN MDM IMPLEMENTATION
Data governance approach is even more critical
here, because now your newly constituted data
governance organization will be making
decisions not only about data quality for the
enterprise, but also about how to implement
one or more master data management hubs.

8. MASTER DATA EXAMPLE
John (Sales Representative) who works in
California (Territory) sells 10,000 (Quantity) of a
new widget (Product) to a customer (Customer)
based in New York (Geography) for $50,000
(Total Sale) on December 15, 2017 (Date).
Taken together, this information is about one
transaction, but included in the transaction are
individual elements of master data—Sales
Representative, Territory, Quantity, Product,
Customer, Geography, Total Sale and Date

9. MASTER DATA MANAGEMENT
These individual elements must be identified
and changes to them must be managed across
the enterprise to ensure data integrity. For
instance, john could be moved to a different
territory or the territory could be assigned to a
different geography. Without good enterprise
data governance, transaction data cannot be
analyzed or reported in a meaningful way.

10. ORACLE SOLUTION
It is therefore essential for organizations to
effectively manage hierarchical master data
across multiple information systems.
Organizations need to move beyond the mix of
email, spreadsheets and adhoc systems that
many currently rely on to execute this
extremely important function. Numerous
organizations are turning to enterprise software
solutions like oracle data relationship
management and oracle data relationship
governance to help them deliver enterprise data

11. ORACLE DATA RELATIONSHIP
MANAGEMENT

12. ORACLE ENTERPRISE DATA
QUALITY
Oracle Enterprise Data Quality helps companies to
achieve maximum value from their business-critical
applications by delivering fit-for-purpose data –
enabling individuals and collaborative teams to quickly
and easily identify and resolve any problems in
underlying data. Oracle Enterprise Data Quality is a
complete and integrated suite of data quality tools
that provide an end-to-end solution to measure,
improve, and manage the quality of data from any
domain, including customer and product data. With
Oracle Enterprise Data Quality products, customers
can identify new opportunities, improve operational
efficiency, and more effectively comply with industry

13. HOW TO INSTALL ORACLE DATA
QUALITY
movie

14. HANDS ON WORK WITH ORACLE
DATA QUALITY

15. Thank you