Building a data warehouse for cash management and forecasting in public finance

 

Building a data warehouse for cash management and forecasting in public finance

Paper details:

REVISION HERE:

The data warehouse star schema is not accurate. Important information is missing and the proposed data warehouse cannot
be used for cash management and forecasting purposes. The challenge of this research is specifically to create and design a
data warehouse where all relevant data regarding revenues (forecasted, planned and actual), expenditures (planned and
fact), daily limits, accounts status (held at 8oA) are stored and organized in a such a way that can be used for the purpose using
BI techniques. The proposed schema is not accurate and need to be substantially revised. Please take into account that BoA
will offer information on the status of the TSA account and foreign currency accounts. Data about collected revenues will be
extracted from the AGFIS system (the table contains the main data that are needed), revenue forecast will be provided by
taxation and customs institutions and debt department, whereas planned revenues (planned and forecasted are two different
things) will also be provided by taxation and customs, but they are not the same with planned. The data warehouse should
store information on expenditures. Executed expenditures will be extracted from AGFIS, whereas planned expenditures have
two different sources: ‘I. from AGFIS system, regarding the monthly planned expenditures, prepared by the budget department
at the beginning of the year (broken down at the level of articles), 2. from budget institutions in their daily cash flow plan
(containing expected payments amounts and expected date and other relevant information as described in the table) and
monthly cash flow plans (containing total of expected payments for each month and other relevant information described in
the table). Another important information that is missing in both versions submitted till now is the data about the daily cash limit
(which is explained in detail in the description document). The article on cash management and forecasting provided also
explains the data and the processes to help you understand and prepare the research. Please let me know if additional
information or explanations are needed. The database schema can be a star schema, hybrid or other, the important is that it
can contain all the information and is structured and organized in such a way that all the data can be used for further analysis,
such as time series, neural network, what if analysis and so on. If the data warehouse is built wrongly than all the research is
useless. I hope you understand the importance.

I also commented that the references should be highlighted in the text in order to identify which part of the text refers to a
book, or website etc., in the reference list.

Again, the diagram of the data warehouse schema has overlapping objects and the relations do not point to the specified
attributes.

the excel document is only for illustrative purpose, if it helps understand the data collection and the analysis. I have t

the major part of the information and deleted several pages that are not needed, in order not to create confusion. Thimthe excel document is only for illustrative
purpose, if it helps understand the data collection and the analysis. I have translated
the major part of the information and deleted several pages that are not needed, in order not to create confusion. This excel
document has been used by the MoF staff for cash management and forecasting

CF March 2011 Englishxls [MATERIAL]

The main details of the paper are specified in the word document: “research description”