DATA focuses on providing integration by General

DATA AND SYSTEM INTEGRATION

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NAME:
POLICE MANASA REDDY
STUDENT ID:
1106642
Executive Summary
The
report focuses on the case study of General Electric project Industrial
Internet which they have proposed. This project is based on the software
Predix that is created and developed by the company. The report focuses on the
template explanation and strategies for the effective adoption, function and
operation of the project. The purpose of this report is to integrate and
manage the strategies for information system related to the project in the
company. Lastly, the report discusses the outcome which is based on the
adopted strategies for the project.

 

           

Table of Contents
Introduction……………………………………………………………………………………….2
Discussion. 2
EAI RA Templates. 3
Architecture Overview Diagram.. 3
Component Relationship Diagram.. 4
Information Management and Integration. 4
Application and Data Storage Infrastructure Design. 6
Application and Service Integration. 8
Conclusion. 9
Recommendations. 9
References. 10
 

 

 

 

 

 

Introduction

            The
Industrial Internet project, an information centric solution, is proposed by
General Electric to converge its machines, data and the internet in one
connection to provide real-time analysis (MIT
Sloan Management Review., 2018). The General Electric is a multinational
company with varied companies having different types of sectors and operations.
The company has four themes for which they want to provide connectivity to all
applications to access them at a single time. The project is to be developed to
provide not only as a remote system but effective and secure at all conditions.
The report focuses on providing integration by General Electric to manage its
information system and data in Industrial Internet project. The report also
focuses on explanations based on EAI RA templates and cloud options and
suitability.

The outline
of the report is explanation based on architecture overview and component
relationship diagram of EAI RA templates, information management and
integration strategies, and cloud infrastructure strategy, application and
service integration strategies and recommendations.

Discussion

The company
has proposed Industrial Internet for mainly industries such as oil and gas,
power generation and healthcare departments where system failures and unplanned
downtime are frequent. These conditions can result in high-risk situations and sometimes
life-threatening situations. The Industrial Internet has powerful operations
which can detect failures and critical situations and result in saving the
company from losing information (Digital and
Things, 2018). The company created its own software that is Predix to address
the needs of company in terms of overview diagram and component relationship
diagram. The other aspects are also discussed and they are strategies for
integration of multiple data sources used for different purposes by different
teams, suitability of various cloud infrastructure and integration of services
and applications.

EAI RA Templates

Architecture
Overview Diagram

Component Relationship Diagram 

Information Management and Integration

            The present scenario
of companies adopting data analytics are for decision-making purposes for their
own company in real-time environment. The company needs to extract insights
from data in operational areas such as sales department, finance department,
marketing department, procurement department and other departments. These
departments need to have its own targets for success and analysis of data
developed and integrated in each department (Shmueli et al.,
2015). The data in each department needs to be separated from other
departments to ensure security, privacy and data breaches. This needs to be started
by looking at each team individually with respect to success that defines each
department. The example includes volume of leads created by marketing
department team to be passed on to sales department team for overall target of
the company. The next example is that sales department team looks conversely to
what marketing department team looks for success and that is they look at
volume of appointments created and converted to new businesses. The information
technology department team looks to support greater use of data analytics and
turns the business process more successful in getting the right us of data in
the company. The data sources are such as networking data sources including web
analytics, marketing automation data and CRM data. The data sources are media,
cloud, web, IoT, databases in company (Talia, 2013). The media is the most popular source of data
analytics in the company. This source is found in every company and it includes
Google, Facebook, Twitter, YouTube and Instagram. This media helps to get an
insight of consumer preferences and changing trends nowadays. The next is cloud
storage which is adopted by most of the companies nowadays. Cloud storage
includes structured and unstructured data which is generated. Cloud storage provides
public and private clouds which are sourced to make and efficient and
economical data sources in the company. The next is web data source. The public
web generates data sources in the company. The public web is used to provide
free and quick information and diverse usability to the company. The public web
data provides company to enjoy the leverage of data without having to develop
their own infrastructure (Baesens,
2014). The next one is IoT. IoT is internet of things which is a
valuable source of data analytics in the company and it is machine generated
content. This is usually generated from the sensors in the company that are
connected to electronic device in internet of things. Databases data sources are
the major source in the company as database is required in every aspect and
segments in company. The databases pave the way for low investment and
information technology costs. Database sources are structured as these are
arranged formally and can be extracted without any hassle.

            There are five
components in data strategy and they are identification, storage, provision,
integration and governing. The identification is done by constructing and
sharing data across the company whether structured or unstructured content. The
storage is important to retrieve data in future for various purposes in the
company (Jaseena and David, 2014).
The two types of data that are stored are internal, for example customer
details, and external, for example third party data. The data is stored in
separate locations from where the data can be easily accessed by the company in
future without creating any copy and any misuse. The provision is that all data
must be packaged and prepared for efficient sharing among the company’s
workforce for standard business process. The integration of data is costly in
company as it involves not only data extraction transformation or loading
process but also moving and combining data across the system (Davenport and Dyché, 2013). The
governing is to establish, manage and communicate information policies and
procedures for effective usage of data across the company.

            The data
integration is challenging for information technology department in companies
due to high cost. The data integration function works as each application
creates its own integration logic and the data contained in each application
differ across each application in the company (Gal, 2015). The data sources such as client data,
pricing data, sales data and client contacts data are perceived and valued by
different applications such as sales department and campaign management
department.

Application and Data Storage Infrastructure Design

            The cloud
storage is the most necessary asset for every company. The different service
models of cloud storage are IaaS, PaaS and SaaS (Rittinghouse and Ransome, 2016). The different
deployment models are private cloud, public cloud, community cloud and hybrid
cloud. The private cloud is the one where the services and infrastructure are
maintained and efficiently managed by the company or third party person. The
public cloud is the one where the services stored off-site and it is accessed
over the internet by the company. The community cloud is the one which exists
where various organizations share access to a particular private cloud having similar
security functions and considerations. The hybrid cloud is the one where
company takes advantage of both private and public cloud services for its
operations (Herbst, Kounev and
Reussner, 2013). The service model IaaS is Infrastructure as a Service
is buying or renting company’s computer system power and disk space frm
external providers for business use. SaaS is Software as a Service and it is
the most common among the other models in businesses as it is accessed using a
browser on the internet (Mishra et al., 2013). PaaS is Platform
as a Service is described as a crossover of both SaaS and IaaS service models.

            The suitability
of cloud storage models are based on services and operations. SaaS is the most
familiar and accessible service for customers in real world. SaaS is basically
used to reduce the cost of company by removing technical staff to manage install,
manage and update software and also cost of licensing software is reduced. This
is used on subscription based model. PaaS is provides platform for software to
be developed and deployed for company. PaaS provides an environment where
clients can deal with server software as well as server hardware efficiently (Wang et
al., 2017). This provides scalability for the company on business
side. PaaS expands its services when demand grows for resources in company.
IaaS is used for company where they need to have complete control over their high
performing applications when there is scaling up or down is based on traffic
networks.

            The cloud adoptions
in General Electric were due to six reasons (The
cloud advantage, 2015). They are speed in implementation and innovation,
end-to-end security, low costs, ability to scale, ubiquitous and global
visibility and failure of isolation with micro services. The speed provided by
cloud storage is efficient and rapid. The security provided by cloud storage is
rapid as they patch the vulnerable with latest updates frequently with reduced
variations. The lower cost of cloud storage is due to reduction in large scale
of big data platform. The ability to scale of cloud storage is advanced and
pave ways for customers and businesses to specify the right amount that is
needed for their usage by scaling up and down based upon requirement changes.
The ubiquitous and global visibility of cloud storage is to provide operation beyond
the geographical boundaries for global business optimizations and operations.
The failure isolation with micro services of cloud storage provides reusability
of software.

            The company
developed its own cloud software that is Predix (GE
Digital, 2018). The cloud infrastructure strategies for the company are
given in the following discussion. The first one is that cloud computing needs
to be more developed and advanced to be adopted by the company as it has trust
issues regarding security and legacy systems. The second one is to deliver
greater business agility, scalability and support by the information technology
department that will be a high priority in coming future. The third one is to
tackle with the challenges related to recruiting, training, and retaining of
cloud architects, developers, engineers, support staff and service
professionals within the company. The fourth one is to measure the
contributions of expenses by the cloud storage and managing the cost to
maintain the overall financial outcome of the company (Hwang, Dongarra and Fox, 2013). The fifth one is
creation of cloud decision framework to keep a track on technology evaluations
and company investments aligned with business strategies developed for business
growth. The sixth one is mitigating risk and liability for future business
operations as they can be cause several risks to company and they should be
looked upon.

Application and Service Integration

            The integration strategy for
application and services are discussed in the following paragraph. There are
two types of application integration and they are automating business process
by connecting two or more applications and creating composite application in
the company (Bussler, 2013).
The first one is solely dependent within an organization where it is sometimes
referred to as enterprise application integration and when done between two
organizations then referred to as business-to-business integration. The second
one is to provide a common front end to a group that has applications existed
in the company and easier ad effective to use for the company. Business process
automation provides benefits that include four significant points. They are
faster process, cheaper process, accurate process and visible process. These
are the benefits provided within the organizations. The business process
automation across the organization also provides benefits for business process to
span faster, cheaper and more accurate in terms of business-to-business
integration. The other application integration is composite application. The
benefits it provides are that employees can do their jobs more efficiently and
effectively and it also provides cross-application functions. The strategies
for service integration are addressing systematic and effective procedural
barriers for collaboration of business processes (Charter and Tischner, 2017). The next one is to
integrate services a collaborative group of service providers are needed. This
is used to meet the needs of particular client individually. The next is a
clear establishment phase where every member of the company agrees on the scope
and structure of the business arrangements for future operations. The next is an
agreement about the groups that are targeted to assess the business program and
the process to assess the program. This is done to integrate the services for
business purposes through target groups (Hoffmann, 2017). The last one is a case plan structure model to
be used for guiding assessment and the structure of the case plan. This is the
final strategy which results in the case plan model for integrating services in
the company.

Conclusion

            The above discussions conclude that
the project of the company is valuable and effective in terms of security,
cost, speed and real-time monitoring and analytics. The report focuses on the
various aspects of project adoption and implementation using the templates
given in the discussions. The strategies for data collection from different
sources and for different purposes are discussed. The cloud options are also
evaluated for different purposes and their suitability for these different
purposes. Cloud infrastructure strategy focuses on how cloud strategy is
necessary for business purposes and how it can be adopted effectively for
future use. The integration of services and applications suggest that
applications and services need to be managed and maintained properly.
Therefore, it can be deduced that the strategies evaluated and described in the
above discussions need to be taken into account for integrating and managing
the company’s information system. Adding to this, evaluation of what data to be
fed into the project is also to be taken into account.

Recommendations

·        
To begin with the project the company should begin to inventory
and share best security practices by establishing common security across the
organization.

·        
To reorient the overall business strategy of the company to
leverage the full potential of latest advancement in the project.

·        
To re-examine and update the company’s data protection and
liability policies timely by policy-makers in the company.

·        
To have active participation from stakeholders in the areas
related to security, interoperability and management of system risks in the
company.

 

References

Baesens, B.,
2014. Analytics in a big data world: The essential guide to data
science and its applications. John Wiley & Sons.

Bussler, C.,
2013. B2B integration: Concepts and architecture. Springer Science
& Business Media.

Charter, M. and
Tischner, U. eds., 2017. Sustainable solutions: developing products and
services for the future. Routledge.

Davenport, T.H.
and Dyché, J., 2013. Big data in big companies. International Institute
for Analytics, 3.

Digital, G. and Things, E.,
2018. Everything You Need to Know About the Industrial Internet of
Things. online GE Digital. Available at: https://www.ge.com/digital/blog/everything-you-need-know-about-industrial-internet-things
Accessed 1 Jan. 2018.

Gal, A., 2015,
August. Big data integration. In Keynote speech at international
conference on open and big data (OBD 2015).

GE Digital., 2018. GE
Announces Predix Cloud – The World’s First Cloud Service Built for Industrial
Data and Analytics. online Available at:
https://www.ge.com/digital/press-releases/ge-announces-predix-cloud-worlds-first-cloud-service-built-industrial-data-analytics
Accessed 1 Jan. 2018.

Herbst, N.R.,
Kounev, S. and Reussner, R.H., 2013, June. Elasticity in Cloud Computing: What
It Is, and What It Is Not. In ICAC (Vol. 13, pp. 23-27).

Hoffmann, E.,
2017. User integration in sustainable product development:
Organisational learning through boundary-spanning processes. Routledge.

Hwang, K.,
Dongarra, J. and Fox, G.C., 2013. Distributed and cloud computing: from
parallel processing to the internet of things. Morgan Kaufmann.

Jaseena, K.U.
and David, J.M., 2014. Issues, challenges, and solutions: big data
mining. NeTCoM, CSIT, GRAPH-HOC, SPTM–2014, pp.131-140.

Mishra, A.,
Mathur, R., Jain, S. and Rathore, J.S., 2013. Cloud computing security. In

The cloud advantage., 2015.
ebook General Electric. Available at:
https://www.ge.com/fr/sites/www.ge.com.fr/files/The-Cloud-Advantage-whitepaper.pdf
Accessed 1 Jan. 2018.

Wang, L.,
Ranjan, R., Chen, J. and Benatallah, B. eds., 2017. Cloud computing:
methodology, systems, and applications. CRC Press.