CIS499 Information Systems Capstone Assignment 4

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CIS499Assignment3_Final_revised.docx

DATABASE AND DATA WAREHOUSING DESIGN 1

DATABASE AND DATA WAREHOUSING DESIGN 7

Project Deliverable 3: Database and Data Warehousing Design

Instruction:

The ACME Company has a vast database of data that generally ranges from terabytes. A data warehouse is a federated repository for all data collected by an enterprise’s various operational systems and therefore, the best option for use in this case. A data warehouse is similar to a relational database that can be housed on an enterprise mainframe or as it is today in the cloud (Rouse, 2018). At any moment, one visit to a website generates thousands of rescue records. Some of the data may not be updated, but cannot be excluded until a few months later; it will be used for analysis. This analysis generated future business prospects. And this analysis depends on how data are collected and how it should be organized to give a clear picture of the analysis.

As the CIO of ACME, it is my responsibility to look for a data warehouse vendor who can increase our analytics operations.

The requirement for the storage of data:

The number of new concepts and tools which has been developed and integrated with the new technology is called Data Warehousing. To understand more simply, a data warehouse is a storage space for storing a huge amount of information in an organization (George, Kumar & Kumar, 2015). It is a relational database designed specifically to manage queries and analysis rather than processing transactions (Jukic, Vrbsky & Nestorov, 2016). It is a well-organized organization, management, and reporting of data. The main features of the data warehouse allow you to save, collect and filter data in different systems at higher levels. It typically contains historical data derived from transaction data, but may also contain data from other sources. It helps the organization consolidate analysis data from multiple sources of transactional working time separation. In addition to that, the environment includes an ETL data warehouse, which is the extraction, transport and upload solution, OLAP, which is the online processing engine analysis, analysis tools and other tools to address the process of data collection. And finally, deliver to business users. The data stored in these stores must be stored in a reliable, secure and easily manageable way. The need for data storage arises when companies become more complex and start producing and collecting a huge amount of data that is difficult to manage traditionally.

Data integration:

ACME’s information is voluminous and complex and is complemented by various internal and external systems. It is also necessary to analyze the data through different location, time and channel systems. Therefore, data integration is needed here so that all data is organized and stored in one place. It also reduces the time and length of the reporting process, due to the number of steps involved: extracting and retrieving data from a single source, then sorting and combining data, and then enriching data, by running reports on this topic uprooted. Data archiving is not only a reliable data storage platform but also a very powerful and excellent data integration platform. The data stored in the data warehouse is completely integrated, variable, volatile and object-oriented. It helps companies get a 360 ° view of the organization.

ER Diagram:

The main entities that form the basis of the company are the independent components that facilitate the correct collection of data and send it to the data. The customer is a recipient of the company's service.

The user visits the page. Web data analysis detects page details. A page can have multiple visits. Recording the information about an unexpected error status code must be done. A status code can have many visits to the page. The registered user information is the backbone of the "customer return" data source. A registered user can have more than one visit. When the data is saved, it must also be stored in the Time Period. At any time, there may be more visits to the system. The registered user receives a payment for his comments.

Site URLs can be social networks, online forms, and customized Web pages.

Data Flow Diagram:

Mapping data source system, data warehouse, and specified data mart:

References

George, J., Kumar, V., & Kumar, S. (2015, July). Data Warehouse Design Considerations for a

Healthcare Business Intelligence System. In World congress on engineering.

Jukic, N., Vrbsky, S., & Nestorov, S. (2016). Database Systems: Introduction to Databases and

Data Warehouses. Prospect Press.

Rouse, M. (2018, November). TechTarget.com. Data Warehouse. Retrieve from:

https://searchdatamanagement.techtarget.com/definition/data-warehouse

Online FormsWeb Page

Customer

Feedback

SEO

Relational Database

Extract, Transform and Load Processes

Operational Data Store (ODS)

Data WarehouseData MartData Mart

Data Mart

Online Forms

Web Page

Customer Feedback

SEO

Relational Database

Extract, Transform and Load Processes

Operational Data Store (ODS)

Data Warehouse

Data Mart

Data Mart

Data Mart

Client

PKclient_ID

Pages

PKpage_ID

StatusCode

PKstatusCode_ID

PagesVisit

PKpageVisit_ID

Visit

PKvisit_ID

Registered Users

PKuser_ID

ServerLog

PKlog_ID

TimePeriod

PKperiod_ID

VistFact

PKvisitFact_ID

Payment

PKpayment_ID

InteractionTypes

PKinteraction_ID

Ref_Calender

PKreporting_Time

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

1 ..*

* ..*

1 ..*

Table

Data GranualityCollection systemIntegration ProcessOperational Data StoreStaging/Verification DatabaseIntegrated Data Warehouse Page VisitCountOnline logging dataData integrity CodeREPORTINGVisitPageTimePeriodPageVisitVisitFactData Mart

Data Granuality

Collection system

Integration Process

Operational Data Store

Staging/Verification Database

Integrated Data Warehouse

Page Visit Count

Visit

Online logging data

Data integrity Code

Data Mart

R E P O R T I N G

Page

TimePeriod

PageVisit

VisitFact

DATABASE AND DATA WAREHOUSING DESIGN

1

Project Deliverable 3: Database and Data Warehousing Design

DATABASE AND DATA WAREHOUSING DESIGN 1

Project Deliverable 3: Database and Data Warehousing Design