Running head: SOFTWARE DELIVERY PRACTICES 2 SOFTWARE DELIVERY PRACTICES 2 SOFTWARE DELIVERY PRACTICES Harrisburg University Krishna Marepalli 170068 PMGT 571 91 Background The Illinois state has families and children department where I work as a project coordinator and manager for the data warehouse management project. In the department, I am responsible for bridging communication between the various departments of the children affairs and the data management business of the state. I also facilitate qualitative and accurate data provision to the child support systems and agencies through well analyzed and interpreted data files. Being responsible for the above data management business requires and accurate data analysis systems and methodologies that will help implement the data management and delivery with accuracy and provide the required data in qualitative nature. The Existing waterfall methodology challenges The waterfall methodology is one of the most used and sought out method in data projects. The waterfall methodology requires every step to be dealt with completely before proceeding to the next step in the data project. The necessity to deal with each step completely before moving forward to the next step will ensure few breakdowns in the data project and case of any, it will easy to trace back the breaking points. (Ur Rahman & Williams, 2016) In developing the data project using the waterfall methodology, challenges are inevitable. In this case for data warehouse management project, it happened that we rolled out the data warehouse project using the epic by epic basis. In this case, the epic business simply implies delivering quite a large number of tasks completed for different domains such as the financial domain, policy domains and financial domains. In the rollout, we adopt the waterfall methodology and while rolling out, we experienced some of the challenges which included: · One of the challenges was heavy documentation of the tasks that we rolled out since they were rolled out in large amounts. This is ultimately tedious for the customers since they have to handle large amounts of files to access the data or domains that they want. (Ur Rahman & Williams, 2016) · Another challenge is that the customers had to wait for longer times for the reports to be released since they were rolled out in large amounts. (Ur Rahman & Williams, 2016) · Due to the fact the project was rolled out in large amounts, it faced the challenge of inadequate testing which leads to some misunderstandings of the needed requirements to successfully implement the domains provided in the data warehouse project. · Also, there were increased costs of delivering the data warehouse projects due to the much re-working that was needed and fixing the bugs that develop later in the project implementation. (Ur Rahman & Williams, 2016) · Lastly, the rollout was faced with bureaucracy issues since it needed sev ...

1. Running head: SOFTWARE DELIVERY PRACTICES 2
SOFTWARE DELIVERY PRACTICES 2
SOFTWARE DELIVERY PRACTICES
Harrisburg University
Krishna Marepalli
170068
PMGT 571 91

2. Background
The Illinois state has families and children department where I
work as a project coordinator and manager for the data
warehouse management project. In the department, I am
responsible for bridging communication between the various
departments of the children affairs and the data management
business of the state. I also facilitate qualitative and accurate
data provision to the child support systems and agencies
through well analyzed and interpreted data files. Being
responsible for the above data management business requires
and accurate data analysis systems and methodologies that will

3. help implement the data management and delivery with
accuracy and provide the required data in qualitative nature.
The Existing waterfall methodology challenges
The waterfall methodology is one of the most used and sought
out method in data projects. The waterfall methodology requires
every step to be dealt with completely before proceeding to the
next step in the data project. The necessity to deal with each
step completely before moving forward to the next step will
ensure few breakdowns in the data project and case of any, it
will easy to trace back the breaking points. (Ur Rahman &
Williams, 2016)
In developing the data project using the waterfall methodology,
challenges are inevitable. In this case for data warehouse
management project, it happened that we rolled out the data
warehouse project using the epic by epic basis. In this case, the
epic business simply implies delivering quite a large number of
tasks completed for different domains such as the financial
domain, policy domains and financial domains. In the rollout,
we adopt the waterfall methodology and while rolling out, we
experienced some of the challenges which included:
· One of the challenges was heavy documentation of the tasks
that we rolled out since they were rolled out in large amounts.
This is ultimately tedious for the customers since they have to
handle large amounts of files to access the data or domains that
they want. (Ur Rahman & Williams, 2016)
· Another challenge is that the customers had to wait for longer
times for the reports to be released since they were rolled out in
large amounts. (Ur Rahman & Williams, 2016)
· Due to the fact the project was rolled out in large amounts, it
faced the challenge of inadequate testing which leads to some
misunderstandings of the needed requirements to successfully
implement the domains provided in the data warehouse project.
· Also, there were increased costs of delivering the data
warehouse projects due to the much re-working that was needed
and fixing the bugs that develop later in the project
implementation. (Ur Rahman & Williams, 2016)

4. · Lastly, the rollout was faced with bureaucracy issues since it
needed several approvals from different departments of the
government. (Ur Rahman & Williams, 2016)
Organization of the work and the process of work delivery
The organization of the work and the process of delivery for the
project was organized in a manner that is described below.
Data warehouse Project.
Data projects are subjected to various processes for them to be
termed as complete data project. These data projects processes
include;
· Gathering the requirements. The information that is needed for
completion of the data project is gathered first before the actual
work begins. Initially, the teams that are responsible for the
development of the projects gather the requirements using
various methods such as interviews and conducting relevant
workshops. ("Best Practice for Social Work and ICT," n.d)
· Process of designing the project. After gathering the
requirements for the data project development, the next step is
to design the project to achieve a desirable outcome. Mapping
processes establish the impression which will be like the end
product hence allowing for adjustments to suit the needs of the
customer. ("Best Practice for Social Work and ICT," n.d)
· Process of Construction. This is the main stage of the data
warehouse development. After gathering the requirements and
designing the project, software engineers embark on
construction the desire projects with the use of the requirements
gathered and the design that was agreed upon. This process
involves the development of the required reports so that he end-
user of the product can be able to test and determine the
suitability of the product.
· Product testing by the user. In this stage, the product is
subjected to user acceptance testing before it is released for use.
The testing is usually done using the agreed procedures for user
testing acceptance before the beginning of the project and the
defects that are detected are reported through the agreed
channel also.

5. · Release of the Data warehouse project. The release of the
project will involve prior communication to the end-users
through various communication channels that are suitable.
("Best Practice for Social Work and ICT," n.d)
· Training. After the project is released to the end-user, training
is carried out by the software developers to equip the end-users
with the knowledge of using the software. The training is
intended to align the usability of the client and the constructor’s
design.
Changing the management and the control process of the data
warehouse project
The manager of the project maintains constant monitoring of the
project to deal with any issues that may arise during the usage
of the project. If any additional requirements may arise in after
the release of the project, the clients will have to contact the
developers to determine if the requirements will be updated or
not. Thereafter, the developer hands over the full control of the
project to the management which is then given the
responsibility of maintaining the software. (Gonzalez-Torres,
2018)
Tools used
The process of developing the data warehouse software utilized
some tools. One of the most utilized tools in the construction of
the software is the Microsoft Project plan that was used in
outlining the plan for the project that was being constructed.
Jira was another tool that was important in the data warehouse
construction project. (Gonzalez-Torres, 2018)

6. References
Best Practice for Social Work and ICT. (n.d.). Social Work &
ICT, 8-19. doi:10.4135/9781446269541.n2
Gonzalez-Torres, A. (2018). A SURVEY ON THE TOOLS
USED IN SOFTWARE DEVELOPMENT AND THEIR
MAPPING TO THE CURRICULUM OF COMPUTING
DEGREES. INTED2018 Proceedings.
doi:10.21125/inted.2018.1746
Ur Rahman, A. A., & Williams, L. (2016). Software security in
DevOps. Proceedings of the International Workshop on
Continuous Software Evolution and Delivery - CSED '16.
doi:10.1145/2896941.2896946
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