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Data Warehouse Management
Improve roadmap planning process with
David Bowman’s information management guidelines for data warehouse
management assessment
This
site is designed for Information
Technology professionals who need to improve roadmap planning process
and
require guidance and direction to help teams consistently produce error
free results.
It provides a checklist of information management guidelines for data
warehouse management assessment.
What is Data
Warehouse Operations?
Data warehouse operations requires a
dedicated production
operations staff with appropriate tools for monitoring production,
tracking incidents and responding to customer calls.
It also requires a
specialized solution delivery methodology, quality assurance
process and change management methodology.
Data
Warehouse Management Assessment Process
Should determine the organizational
readiness for information
management by comparing the current data warehouse management
situation with the following checklist of information management
guidelines.
 Performance
Monitoring
- Should provide visibility to workload
executing in the data warehouse
environment;
- Should provide aggregated resource e.g.
CPU,
I/O, memory, locks, etc, with drill down to individual
users, queries, etc.
- Should provide historical play-back of
performance trends; and
- Should include common tools such Database
Performance Analyzer, from solarwinds.
Workload
Management
- Should provide gatekeeper, dynamic
workload prioritization, and
governors to manage workload executing in the EDW
environment;
- Should evaluate the priority and resource
requirements for incoming queries and assess available resources for
execution to decide if a query should be run immediately or
be deferred;
- Should efficiently allocate resources
within the platform according to query demands aligned to defined
service level goals for each query; and
- Should provide governors to
monitor for queries that exceed resource expectations or have
performance issues.
Usage
Analysis
- Should provide automated tracking and
reporting of data warehouse usage by user and application;
- Should track resource consumption;
- Should track detailed tracking down to
the level of specific
tables and columns within the data warehouse; and
- Should track the use
of historical data e.g. detailed data usage helps the database
management team design archiving
strategies and partitioning strategies.
Capacity
Planning
- Should analyze trends in resource
utilization and service level compliance combined with workload
profiling for current and future applications as
input to modeling/simulation tools for capacity planning;
- Should provide what-if
analysis to perform sensitivity analysis across a range of
workload assumptions;
- Should suggest
optimal investment strategies in terms of CPU, memory, disk spindle,
etc. configurations for maximizing performance for each dollar spent.
Impact
Analysis
- Should provide the capability to
determine
the impact of any changes to source systems, target database structures
in
the data warehouse, or business transformation rules;
- Should
provide a
listing of all extract programs, transformation rules, target table
structures, and business intelligence tool impacts resulting from a
change e.g. a column
length
increases from six bytes to twelve bytes; and
- Should typically be provided by the data
integration technology e.g Informatica.
Incident
and Problem Tracking
- Should log all incidents in a logging
tool with
classification and a description of the incident;
- Should provide search capabilities so
that new
incidents can be easily linked and tracked along with existing and
previous incidents;
- Should provide the capability to report
patterns of
repeated root causes; and
- Should consider common tools such Service
Desk
Manager, from CA Technologies.
Defect
and Change Request Tracking
- Should provide the capability to document
and track all defects and change requests;
- Should provide the capability to document
and track all production incidents;
- Should provide the capability to review
and categorize change requests to ensure completeness of the
documentation e.g. defects should not be closed without adequate
documentation of root cause; and
- Should consider common tools such as
ServiceDesk Plus, from ManageEngine.
Data
Quality Management
- Should provide the capability to automate
data profiling;
- Should provide the capability to measure
data quality defects;
- Should provide the capability to create
alerts when data quality does not meet requirements;
- Should provide the capability to report
on trends;
- Should provide the capability to track
defects versus target service level
agreements; and
- Should consider common tools such as
Informatica Data Quality, from Informatica.
Service
Level Agreements
- Should be documented in
detail for performance, availability, data currency, and data
quality;
- Should be negotiated with business users
and should be used
as the basis for capacity planning and architecture considerations;
- Should be used to measure performance of
actual service level delivery; and
- Should be reviewed
with business on a quarterly basis.
Release Management
- Should be a key component of data
warehouse management.
- Should provide a single point of control
to coordinate new hardware and
software releases into the EDW environment; and
- Should provide coordination
among various teams e.g., database administrators, data integration
technical services, business intelligence technical
services, etc. to ensure compatibility of all configuration items and
that releases are coordinated
Security and
Administration
- Should provide a centralized function to
administrator user ids, passwords, roles, etc; and
- Should ensure that LDAP, or an
equivalent standard, is used to manage a centralized directory of
security and authorization information
Service Desk
- Should provide assistance to business end
users in
using analytic applications and accessing the business intelligence
environment; and
- Should ensure that end users do not get
direct
access to business intelligence developers without some form of triage
through a service
desk function.
Change Management
- Should provide a formalized team
process to manage change in the hardware and
software environments;
- Should provide the capability to assess
all
changes and recommend how, when or if to proceed with
changes;
- Should plan the change; and
- Should plan the change back out the event
of
unexpected results.
Business Intelligence Technical
Services
- Should fix business intelligence
incidents and problems that cannot be handled by the service desk; and
- Should have trouble shooting skills
combined with extensive business intelligence tool experience.
Data Integration Technical Services
- Should fix data integration incidents and
problems that cannot be handled by the service desk; and
- Should have trouble shooting skills
combined with extensive data integration tool experience.
Software Support
- Should maintain the software
infrastructure in the environment; and
- Should manage software upgrades and
patches
to operating systems, databases, etc.
Dedicated Production Staff
- Should share some production support
staff with the operational systems;
- Should provide specialized support;
- Should include key operational resources
for data warehouse, and business intelligence support
- Should have more thorough knowledge of
the data warehouse applications and
databases than shared production support resources.
Summary...
Data warehouse management requires a
dedicated production
operations staff with appropriate tools for monitoring production,
tracking incidents and responding to customer calls.
This site provided a checklist of information management guidelines for
data
warehouse management assessment.
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