Payroll and Time

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Payroll and Time Attendance Focus GroupMeeting
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Decision Support Payroll and Time Attendance
Increment March 4, 2003
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Agenda

• Decision Support Overview
• DS Pay/TA Increment Overview
• DS Terms and Definitions
• Requirements Overview
• Focus Group Overview

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I. Decision Support Overview
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Decision Support Mission
To support integrated and secured management
reporting, analysis and decision making
By providing the University with the
infrastructure and services to access data and
metadata

• The DS Mission Statement implies these functions
• Data Warehouse Environment
• Support and Maintenance
• Training
• Meta data

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Decision Support Who we are
We are a recently formed University unit to
manage business and administrative data as an
asset, so that it increases in value to colleges,
departments and administrators. We are
implementing proven technology (data warehousing)
to manage data as an asset AND enable easy access
to data for colleges, departments and
administrators. When the UI-Integrate Project
closes, the Decision Support unit will continue
to tailor the data warehouse to meet business
requirements
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Decision Support What we do

• Build an environment to provide easy access to
  data
• Based on user requirements
• Thats where you (Focus Groups) come in!
• Support, maintain and enhance that infrastructure
• Provide Data Education and Metadata
• Provide Business Objects Tool Training

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Data Warehouse Environment
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DS Timeline Highlights
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Requirements-Driven

• Each Decision Support increment will have many
  requirements, expectations and constraints.
• Decision Support takes a requirements-driven
  approach to development of the data warehouse
  environment.
• For increments deployed in parallel with
  UI-Integrate there exists an implied scope.
• Decision Support is mindful that the data
  warehouse is the data access point for Banner
  data therefore, Banner data drives some of
  the requirements questions.

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Business-Relevant Data

• The data warehouse contains business-relevant
  data that is
• Designed to support analysis and management
  reporting
• Transformed to increase ease of use or to
  capture/enforce business rules
• Aggregated or pre-calculated for performance
  considerations

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Non-Business Relevant Data

• The data warehouse is NOT intended
• To contain a copy of Banner
• To contain Banner rules and processing tables
• For auditing the operational environment
• Remember The Data Warehouse has no
  Banner-like application to interpret the data
  or enforce business rules

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II. Payroll and Time Attendance Increment
Overview
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Increment Goals

• Purpose
• Add Payroll and Time Attendance data to the
  Data Warehouse
• To Support
• Reporting and analysis requirements of
  Administration, Colleges and Departments
• UI2 Pay/TA project reporting deliverables
• Go-Live Date
• December 2003

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Increment Scope

• In Scope
• Banner
• History/Change Data
• Detail Data
• Legacy Data
• Out of Scope
• Audit-level detail
• Archive data
• Quality control reports

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Increment Process

• Work planning
• Estimate timeline, resources, DS focus group
  selection
• Analysis
• Gather information, do preliminary interviews,
  outline draft scope and timeline
• Kick off focus group sessions (ongoing through
  implementation)
• Review UI2 reports created against the Data
  Warehouse
• Design
• Work with focus groups and Banner experts
• Begin initial Universe design, begin mapping and
  ETL development, and finalize the data model

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Increment Process

• Construction
• Finalize source to target mappings, finalize ETL
  development and begin to system test
• Implementation
• Begin end user testing, integration testing and
  implement training
• Deployment
• Go live

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Timeline
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III. DS Terms and Definitions
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Definitions Data Collections
  Data Warehouse A collection of integrated,
subject-oriented databases where each unit of
data is relevant to some moment in time. The data
warehouse contains atomic (detailed) data and may
also contain summarized data. What is included in
a data warehouse environment varies widely but is
generally acknowledged to one or more databases,
metadata, a delivery/access method and a
commitment to extract, transform and load (ETL)
data from multiple source systems. Paraphrased
from Inmon, 1996 Enterprise Data Warehouse An
Enterprise Data Warehouse (EDW) is a non-volatile
data store containing historical, detailed data
that spans a number of subject areas. This data
store is fed by transactional data on a regular
basis from a variety of data sources. In the eyes
of the end-user, the EDW is a read-only
environment. At the University of Illinois, the
EDW is one component of the overall Data
Warehouse. The Data Warehouse contains both the
EDW and specialized Data Marts.   Data Marts A
set of data designed and constructed for decision
support purposes reflecting the design principles
of a data warehouse provided to serve the needs
of a homogeneous user group.    
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Definitions Points of Decision
Data Update Update the information in the data
warehouse with the changes to the data found in
the operational system, without saving the
previous state and without providing the
capability to report the change. Data update
processing merely identifies a change in the
record and overwrites the old record with the new
values.   Denormalized A data storage design
that combines all pertinent data in as few tables
as possible. Frequency Of Update The time
period between updates of data sets in a data
mart or data warehouse, i.e. daily, weekly,
monthly, etc.   Track History Allow visibility to
the before and after values of a record when
changed in the source. For example, if marital
status for an employee changes from S to M in
the operational system on 8/1, you can query to
data warehouse to see that before 8/1 the marital
status was S and after 8/1 it is
M. Transformation The modification of source
data prior to its insertion into the target. 
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Definitions Roles
Usage Expert Usage Experts (UEs) are individuals
with the background and knowledge of how the
organization utilizes and analyzes data. Primary
focus should be on the consumption of data for
reporting and analysis. UEs assist Decision
Support in structuring the data appropriately to
meet reporting and analysis purposes by
explaining how data is used by the organization
to make decisions.  Source System Expert Source
System Experts (SSEs) are individuals with
knowledge of the source system applications and
underlying data elements. These individuals
understand the functioning of applications that
capture data. They best understand data issues,
including relationships and constraints with data
elements. They often know the data quality
issues facing the data warehouse development
effort.  Subject Matter Expert Subject Matter
Experts (SMEs) are individuals with the business
and organization knowledge to articulate the
business meaning and business use of data. These
individuals understand best the basic business
meaning of the data. These individuals also have
an understanding of the policies and procedures
of the organization as it relates to the
collection and processing of data. SMEs also
have basic understanding of the applications used
to support business processes that collect the
data. They assist with identifying data by
business-recognized terms, and providing the
business rules and calculations applied to data.
They have stewardship over the data for the
organization.
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Definitions Reports
Operational Reports Operational reports usually
include detailed, transaction-based data. Often,
these reports contain calculated fields and
summary totals. Users rely on operational
reports to help them successfully complete
business processes and resolve exception
situations. Operational reports can be run on
demand or in a daily, weekly, monthly, or annual
job stream. Normally data for operational
reports comes from a single database or source.
Examples of these reports are class rosters, ISIR
financial aid suspense printouts, lists of
students that have an open balance greater than
30 days, monthly UFAS statement, and payroll
distribution reports. The operational reports
identified as critical and high priority will be
developed by the UI-Integrate project.
  Analytical Reports Analytical reports usually
summarize or aggregate data to aid managers in
identifying trends, analyzing volumes of data, or
performing planning or forecasting. It is common
for analytical reports to pull data from a
warehouse or data mart, which may contain data
from a variety of source systems. Examples of
these reports are historical admissions trend
analysis, longitudinal study of graduation rates,
employee retention analysis and multi-year
comparisons of financial activity. Analytical
reports will be developed by the user community.
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IV. Requirements Overview
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HR Requirements Gathering
Decision Support
Who
UI-Integrate
Decision Support
HRIS
Goal
Context for Data Warehouse
Configure Banner and design UI2 reports
Build Data Warehouse
Identify reports to be developed by HRIS
What
High Level Requirements Interviews
Conference Room Pilots (CRPs) Requirements
Interviews
Detailed Requirements (Interviews, Focus Groups
Electronic Review Groups)
In-house interviews and discussions
Time
When
2000 - 2001
2000 - 2002
2000 - 2003
2003
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DS Requirements Process
Increment Scope
DS Updates
First Approximation of
Requirements and data
Requirements
model/design
Findings
Interview Narratives
High-level Business
Focus
DS Asks questions that
Question Map
DS Records and
refine requirements and
Group
Verifies
data model/design
First Approximation of
Enterprise Data Model
Elements
UI-Integrate
Focus Group reaches
Documents (As-Is
consensus
Narratives, CRP To-Be
Documents, etc.)
At Each Milestone
First Approximation of
Data Mart Elements
(as appropriate)
Electronic Review Group
UI-Integrate Report
Specifications
Work Completes
Focus Group Sign-Off
Data Model Approval
Banner and Other
Source System
Information (data
Construction and
models, etc.)
DSST Review Sign-Off
Implementation
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Focus Group

• Purpose
• To ensure that the needs of the user community
  are considered in the detailed design of the Data
  Warehouse.
• Tasks
• Attend a series of working meetings. (Varies from
  2-9 meetings, depending on task.) Group is asked
  to sign off on resulting design.
• Validate requirements gathered by the DS team,
  provide clarification if needed and identify any
  gaps
• Review proposed model and provide input on
  design, such as need for history tracking
• Provide input on detailed data to brought into
  the Data Warehouse.

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Electronic Review Group

• Purpose
• To provide input on requirements deliverables,
  created by interviews and Focus Group process
• To allow wider participation than Focus Group
  size permits
• Tasks
• Receive deliverables by email
• Respond within a fixed period with
  suggestions/input
• Not a sign off or approval but chance for input

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V. Focus Group Overview
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Focus Group Purpose
The Focus Group provides the DS team access to a
representative cross-section of the user
community in order to pose a variety of detailed
requirements questions and gain insight into how
the Data Warehouse might be used.
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Focus Group Objectives

• Primary Objectives
• Provide input into detailed requirements for
  source data
• Validate and identify business requirements
• High-level business questions
• Data hierarchies, groupings, and measures
• Data marts
• Review completed data model
• Identify legacy data requirements (per campus)
• Review security issues and plans
• Review the EDW Requirements document
• Become familiar with data in the EDW
• Other topics
• Plans for electronic review and UAT
• Business Objects overview

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Focus Group Role and Responsibilities

• Focus Groups are critical to the success of the
  DS increment.
• Focus Group members represents his/her
  constituency as the group
• Describes how the data will be used, the business
  rules to be applied, useful calculations or
  aggregations, etc.
• Verifies the functionality and detailed
  requirements of the Decision Support increment
• Confirms that the Decision Support environment
  satisfies the requirements as appropriate for the
  release
• Provides the greatest voice for the outcome of
  the release.

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Role of DS Members
DS members of the Focus Group are a part of the
DS increment team that develops the data model to
represent the validated Data Warehouse
requirements. If DS is unable to fulfill any
validated requirement, the DS members will
explain to the Focus Group the reasons why DS
cannot meet the requirement at this time.