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 ...