Big Data Integration: Enterprise Systems, Amazon and Consumer Patterns

This report delves into the realm of big data integration within enterprise systems, exploring how organizations leverage vast datasets to gain competitive advantages. The report begins by outlining the core attributes of enterprise systems, such as business logic and database integration, and then highlights the exponential growth of data generation. It then identifies five key overlapping points between different enterprise systems, including CRM, SCM, and ERP. A significant portion of the report is dedicated to examining Amazon's use of big data to uncover consumer patterns, including personalized recommendations and price optimization. Furthermore, the report discusses the new knowledge generated by organizations through big data analysis, emphasizing its role in increasing efficiency and understanding local preferences. The report also explores the role of new systems in evaluating data, such as faster information delivery and improved quality assurance. The report concludes by emphasizing the importance of integrating all required data into a single system, using Amazon as a case study to illustrate the potential of big data in the retail industry and its impact on consumer behavior.

Running head: BIG DATA INTEGRATION
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Name of the Student
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Author Note:

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Table of Contents
Introduction..........................................................................................................................2
Discussion............................................................................................................................2
Five Overlapping points between the Systems................................................................2
Amazon using big data and uncovering new consumer patterns.....................................3
New knowledge generate by the organization.................................................................4
Role of New System for evaluating data.........................................................................4
Conclusion...........................................................................................................................5
References............................................................................................................................6

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Introduction
Enterprise System are generally created so that it can easily satisfy the requirement of the
business. Some of the common attributes of the enterprise system are inclusive of business logic,
distributed transaction, integration of legacy system and accessing the relational databases
(Appelbaum et al., 2017). The whole amount of data that is being generated ultimately results in
huge number of storage concerns. User makes use of around 2.5 quintillion data which is being
generated on each and every day. The given data amounts to 90% of whole data generated in past
two year’s record.
In the coming section, five overlapping points in between different enterprise systems
like customer relationship management, supply chain management, and enterprise resource
planning. The next part deals with the use of big data in Amazon for uncovering consumer
patterns.
Discussion
Five Overlapping points between the Systems
Enterprise system are found to be helpful for business for reducing any kind of cost
related to information technology (Wang, Kung & Byrd, 2018). It merely helps in reducing any
kind of manual input of data. Enterprise system are certain number of attributes that bring certain
number of benefits like support to teamwork, increase quality of work, and better employee
collaboration and efficiency.

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Record Loss: CRM application makes use of remote internet connection for saving the
customer record (Duncan, Whittington & Chang, 2017). Salesforce stands out to be popular
CRM application which is provided through internet connection on organization domain.
Training Materials: If the organization stands to be small, then there is huge number of
training issues. Large organization need to focus on training schedule for most of the employees.
Effectiveness of System: Benefits of ERP system completely decreases if it has any kind
of resistance for sharing details in between given business units and departments (Bhimani et al.,
2017). As a result of strong changes in the implementation of ERP system in work culture.
Lack of Coordination in between the departments: The biggest drawbacks of SCM is
that it can work if and only if there is proper coordination between various departments of
organization. This system merely fails if the departments are at loggerheads.
Complicated: SCM requires the involvement of multiple departments so it stands to be
bit complicated, which can hamper the normal working of organization.
Amazon using big data and uncovering new consumer patterns
Amazon stands out to be leader in collecting, processing, and analysis of some personal
information. Each of the customers aim in understanding the point how most of the customer
spend their money (Müller, Fay & vom Brocke, 2018). In addition, Amazon makes use of
predictive analytics for target making along with increasing customer satisfaction. Big data has
helped amazon in growing into an online retail organization.
Personalized recommended system: Amazon stands out to be leader in collaborative
filtering engine. Amazon aims to keep items that are purchased earlier and new items that are

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being purchased (Wang et al., 2018). All the collected information is required for recommending
additional products than the customer purchased product.
One-Click Oder: Big data highlights that customer shop elsewhere if there products are
delivered lately. Amazon has come up with one-click ordering system. In this method, one-click
is completely patented feature where individual places the order first and after there is need for
entering shipping order and payment methods.
Price Optimization: Big Data is also used for managing the price at Amazon so that it
can attract much more customers and increase the profit by a value of 25% (Hilbert, 2016). Price
are completely set by activities on website, availability of product, order history, and profit
margin.
New knowledge generate by the organization
Big data can be stated as the large datasets which can be used for reveal some of the
patterns (Bennett, Ravikumar & Paltán, 2018). It helps in analyzing human behavior and their
interaction. Recently a big revolution has come into picture with development of internet,
wireless network, social media, and related technology.
Big Data Increases Efficiency: Digital technology stand out to be the best tool for
boosting the efficiency of business (Duncan, Whittington & Chang, 2017). Using some of the
tools will help in doing the task without any kind of travel expenses.
Focusing on local preferences: It helps in focus on the local environment which they
cater to. Big data stand out to be best tool which helps in understanding the preference of local
client.

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Big data helps in hiring right employees: Most of the recruiting organization like
Amazon can easily scan candidate resume and LinkedIn profiles for some keywords.
Role of New System for evaluating data
Integration of big data into ERP can have list of benefits like
Delivery of information at faster rate: Some of the big data system like Hadoop aims to
create node-level of operating transparencies (Bhimani et al., 2017). All the benefits will help the
manager to look for ERP big data capabilities.
Better Scheduling: At the time of implementing big data system, all the given
information will be immediately available (Wang et al., 2018). There is requirement of much
more data from multiple mobile enterprise field services.
Increase Quality Assurance: All the discipline associated with the raw materials need
altering and integration of components for creating the finished products (Müller, Fay & vom
Brocke, 2018). Integration of ERP big data along with providing quality process help the
manufacture to proper storage and complete of monitoring of data in real-time.
Conclusion
The above pages helps us in concluding that this report is all about Enterprise system. It
merely highlights five overlapping point in the given systems. There is need of single system for
integrating all the required data. For this particular task, we have consider “Amazon” as the retail
industry, which uncovers the different consumer patterns. There is need for analysis of new
knowledge that is being generated by this particular organization. There is requirement for
analyzing the system which will help the organization to make use of the given data.

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Organization around the globe makes use of enterprise system for gaining competitive
advantage. The system is very much useful in increasing the productivity of employees and
reducing any kind of duplication of data.

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References
Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and
enterprise systems on managerial accounting. International Journal of Accounting
Information Systems, 25, 29-44.
Bennett, A., Ravikumar, A., & Paltán, H. (2018). The Political Ecology of Oil Palm Company-
Community partnerships in the Peruvian Amazon: Deforestation consequences of the
privatization of rural development. World Development, 109, 29-41.
Bhimani, J., Yang, Z., Leeser, M., & Mi, N. (2017, September). Accelerating big data
applications using lightweight virtualization framework on enterprise cloud. In 2017
IEEE High Performance Extreme Computing Conference (HPEC) (pp. 1-7). IEEE.
Duncan, B., Whittington, M., & Chang, V. (2017, August). Enterprise security and privacy: Why
adding IoT and big data makes it so much more difficult. In 2017 international
conference on engineering and technology (ICET) (pp. 1-7). IEEE.
Hilbert, M. (2016). Big data for development: A review of promises and
challenges. Development Policy Review, 34(1), 135-174.
Müller, O., Fay, M., & vom Brocke, J. (2018). The effect of big data and analytics on firm
performance: An econometric analysis considering industry characteristics. Journal of
Management Information Systems, 35(2), 488-509.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and
potential benefits for healthcare organizations. Technological Forecasting and Social
Change, 126, 3-13.

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Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data
analytics-enabled transformation model: Application to health care. Information &
Management, 55(1), 64-79.

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Link to dataset
https://www.kaggle.com/c/coupon-purchase-prediction/data