TJG Web Services has developed TJGXMLCMS, a suite of tools that
facilitate management of presentation and content. The
development of relational databases and NoSQL databases has created
new opportunities for research design (Xu et al., 2016). TJG
Web Services embarked on the development of content management tools
that integrate NoSQL databases with SQL databases. The ability
to query datasets within SQL and store the data in NoSQL provides
data analysts with the ability to access data for the needs of data
analysis (Berger, Berlak, & Reinhart, 2016). The addition
of XML provides the ability to store content and configuration in a
business domain format. The NoSQL datasets provide a simple
data store where data exports into various programming applications
for programming and analysis. Three primary features of the
interface are the ability to query SQL data, the ability to convert
the results to XML format, and the ability to store the XML results
in a web interface. The SQL data can be queried in a number of
SQL formats including various relational database management system
engines and standard SQL (Schweinsberg & Wegner, 2016).
The scope of this project was to develop interfaces between SQL,
XML and CSV. XML and CSV were developed for the web interface
layer (Berger et al., 2016). The interfaces are modular to be
able to update to the latest specifications and suit different
purposes. The designs of the interfaces have abstracted
business domain logic from presentation to support modularity.
Data management included testing of various data formats for their
ease of use. Data management also included test data formats
for extracting, transforming, and loading data. The application
has an assortment of user and application interfaces for the
exchanging data between layers.
The purpose of the TJGXMLCMS was to develop functional interfaces
for the exchange data between various formats: SQL, XML, and CSV
(Schweinsberg & Wegner, 2016). Three stages of TJGXMLCMS
development included data management, application management, and
research and design. The stages were coordinated for
incremental development of the application.
TJGXMLCMS facilitates presenting data from a number of sources.
Supporting forces include an increasing demand for data analysis
tools, an increasing amount of data being stored, and an increasing
variety of data formats available for data analysis (Kroon-Batenburg,
Helliwell, McMahon, & Terwilliger, 2017). Data scientists
require a variety of tools that can provide ease of use and
functionality for a variety of purposes. Organizations are able
to store more information with flash storage and cloud services.
More data formats are available with new database management
systems. TJGXMLCMS supports content management of emerging data
The design of the TJGXMLCMS application included an analysis of
requirements from industry and research in the field to be able to
gather and analyze needs (Memon et al., 2016). TJGXMLCMS
supports facilitation of ongoing validity and reliability of the
requirements with ongoing quality assurance measures.
Maintenance also includes testing the interface with new database
The Nominal Group Technique (NGT) is a possible technique for
identifying project requirements. The Nominal Group Technique
involves the steps of generating, recording, ranking, voting on, and
prioritizing ideas (Rankin et al., 2016). The nominal group
technique ensures that all members of the group get a fair chance at
presenting their ideas. Each member of the group writes down
their ideas privately and the moderator can display the ideas on a
story board. The members vote on the ideas and prioritize the
ideas. The group can take action on the ideas with the highest
priority. The Nominal Group Technique facilitates the process
in software development for identifying which feature of the
application to develop next. The modularity of TJGXMLCMS allows
for rapid development of new features.
The models designed for this interface include a conceptual
diagram, a logical diagram, and a physical diagram. Figures 1-3
explain the models designed in the interface. The physical
diagram also explains the query information and various style sheets
for formatting the XML.
Figure 1 Logical Diagram
Figure 2 Logical Diagram
Figure 3 Physical Diagram
The XML structure for TJGXMLCMS provides for the management of
text and image content in the presentation of the content management
system. The XML populates the features of the presentation
layer. The structure for the xml files for TJGXMLCMS is
displayed in Figure 4:
Figure 4 TJGXMLCMS XML structure
The analytical plan provides an outline of the project. The
analytical plan includes forecasting and scenario planning for the
project (Hoch, 2016). Forecasting methods will assist in
determining the success of the project by identifying trends in the
demand for these tools. Forecasting examines trends in data
management, the amount of data being stored, and the types of data
being stored. Forecasting also examines the various types
of DBMS available and their popularity. Scenario planning will
guide the project for different implementations for the final project
such as comparing industries and sizes of organizations.
Scenario planning will also be a tool for arranging long term
planning of the project. TJGXMLCMS development employs both
forecasting and scenario planning to further advance the capabilities
of the application.
Anticipated Results, Conclusion, and Further
TJGXMLCMS development included a set of performance benchmarks
that guided the efficiency of the application. The anticipated
results of the project were to provide a product that was easy to
learn, adapt for a variety of situations, and modifiable to meet
future requirements (Gao, Xie, & Tao, 2016). The final
product should be able to meet the demands of a competitive market
and provide data scientists with a toolset, capable of meeting
increasing demands of big data and data analysis. TJG Web
Services should deliver the toolset within certain constraints of the
project such as cost, time, and personnel. The final product
should be low in cost, delivered within a short time frame, and
requiring a small number of personnel from the organization.
The final product should meet the demands of the growing market of
data science personnel.
Factors that affect the success of the project include increases
in market competition, changes in application development
methodologies, and the difficulty in creating a unique product that
is usable and reliable (Memon et al., 2016). The various needs
of data science personnel across different industries, and different
types of organizations are also potential limitations. TJG Web
Services mitigates the risks of potential limitations of TJGXMLCMS
with the design of data quality assurance (Gao et al., 2016). Data
quality assurance provides oversight on the design and development of
the final product. Data quality assurance also provides
guidance on product development by implementing various testing
strategies such as quality development.
Other societal factors that can influence the success of the
product can include the internationalization of the final product and
the ability to market the product to different industries and
different types of organizations (Memon et al., 2016). The
product should be able to translate to different languages and should
be scalable to handle datasets for large organizations that have
demands in terabytes or petabytes of storage. The storage
demands should not limit the functionality of the application in
speed and performance and the final product should be from errors.
The product should also provide a command line interface that allows
data science personnel to perform the same actions from within the
application on the command line. The final product should also
be available on a variety of operating systems.
C., Berlak, J., & Reinhart, G. (2016). Service-based Production
Planning and Control of Cyber-Physical Production Systems.
J., Xie, C., & Tao, C. (2016). Big Data Validation and Quality
Assurance--Issuses, Challenges, and Needs. Paper presented at the
2016 IEEE Symposium on Service-Oriented System Engineering (SOSE).
C. (2016). Utopia, scenario and plan: A pragmatic integration.
Planning Theory, 15(1), 6-22.
L. M., Helliwell, J. R., McMahon, B., & Terwilliger, T. (2017).
Raw diffraction data preservation and reuse: overview, update on
practicalities and metadata requirements. IUCrJ, 4(1).
S., Riedel, M., Memon, S., Koeritz, C., Grimshaw, A., &
Neukirchen, H. (2016). Enabling Scalable Data Processing and
Management through Standards-based Job Execution and the Global
Federated File System. Scalable Computing: Practice and
Experience, 17(2), 115-128.
N. M., McGregor, D., Butow, P. N., White, K., Phillips, J. L., Young,
J. M., . . . Shaw, T. (2016). Adapting the nominal group technique
for priority setting of evidence-practice gaps in implementation
science. BMC medical research methodology, 16(1), 110.
K., & Wegner, L. (2016). Advantages of complex SQL types in
storing XML documents. Future Generation Computer Systems.
J., Shi, M., Chen, C., Zhang, Z., Fu, J., & Liu, C. H. (2016).
ZQL: A Unified Middleware Bridging Both Relational and NoSQL
Databases. Paper presented at the Dependable, Autonomic and
Secure Computing, 14th Intl Conf on Pervasive Intelligence and
Computing, 2nd Intl Conf on Big Data Intelligence and Computing and
Cyber Science and Technology Congress
(DASC/PiCom/DataCom/CyberSciTech), 2016 IEEE 14th Intl C.
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