Database workload of your data warehouse in advance,

Database Administrator (DBA)

 

            The Database Administrator is a person responsible for
the

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·        
Installation

·        
Configuration

·        
Upgradation

·        
Administration

·        
Monitoring and
maintenance of databases

Primary Roles:

1.     
Database design

2.     
Database
accessibility

3.     
Performance issues

4.     
Capacity issues

5.     
Data Replication

6.     
Table maintenance

DBA Functional
Organization:

1.     
Planning

2.     
Design

a)     
Conceptual

b)     
Logical

3.     
Implementation

a)     
Physical

b)     
Testing

4.     
Operations

5.     
Training

DBA Tasks:

1.     
Database design

2.     
Performance monitoring
and tuning

3.     
Database availability

4.     
Security

5.     
Backup and
Recovery

6.     
Data Integrity

7.     
Release Migration

 

 

 

 

 

Data Warehouse Administrator

Data warehouse:

·        
It is a
stand-alone repository of information, integrated from several, possibly heterogeneous
operational databases.

·        
It is a process,
not a product.

Data warehouse administrator roles:

·        
New role, coming
with the growth in data warehouses

·        
Similar to DBA/DA
roles

·        
Specific roles:

1)     
Support DSS
applications

2)     
Manage data
warehouse growth

3)     
Establish service
level agreements regarding data warehouses and data marts

·        
Tasks:

1)     
Involved in KPI (Key,
Performance, Indicator)

Ø  The KPI has

a)     
Measure

b)     
Innovate

c)     
Propagate

d)     
Strategize

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Comparison between DBA && DWA

Characteristics

Data Warehouse

Database

Workload

Designed to
accommodate ad hoc queries. You may not know the workload of your data
warehouse in advance, so it should be optimized to perform well for a wide variety
of possible queries.

Supports only
predefined operations. Your applications might be specifically tuned or
designed to support only these operations.

Data modifications

Updated on a regular
basis by the ETL process using bulk data modification techniques. End users
of a data warehouse do not directly update the database.

Subject to individual
DML statements routinely issued by end users. The OLTP database is always up
to date and reflects the current state of each business transaction.

Schema design

Uses de-normalized or
partially de-normalized schemas (such as a star schema) to optimize query
performance.

Uses fully normalized
schemas to optimize DML performance and to guarantee data consistency.

Typical operations

A typical query scans
thousands or millions of rows. For example, a user may request the total
sales for all customers last month.

A typical operation
accesses only a handful of records. For example, a user may retrieve the
current order for a single customer.

Historical data

Stores many months or
years of data to support historical analysis.

Stores data from only
a few weeks or months. Historical data retained as needed to meet the
requirements of the current transaction.