4.Evaluate FIVE (5) disadvantages of proposing the big data and cloud technologies inreference to the answers given in (2).5.Recommend the relevant solutions to mitigate the disadvantages as evaluated in (4). Case Study – Big data technologies-based application is used to process, analyzeand store the supply chain industry data.The ever-increasing importance of supply chain industry has brought together numerouschallenges. Specifically, challenges are in collecting, processing, analyzing, and storingof data. These are due to the digitalization and automation devices have generate hugeamount of data in the supply chain's applications.The supply chain industry applications collect data from multiple participants such asmanufacturers, retailers, vendors, etc. The data is useful for planning, sourcing anddevelopment, execution, delivery and return of products.Currently, most of the supply chain applications still utilize traditional data processingsystems to monitor and manage the real-time logistics tracking such as for sales numbers,inventory levels, delivery time, vendor, and shipping details, to name a few. In addition,most of the applications do not employ machine learning algorithms for prediction in thesupply chain applications.Based on the above case study, answer the following questions.

based on the given case study , here are the answers for question 4 and 5

Evaluate FIVE (5) disadvantages of proposing the big data and cloud technologies in reference to the answers given in (2). Recommend the relevant solutions to mitigate the disadvantages as evaluated in (4).

Evaluate FIVE (5) disadvantages of proposing the big data and cloud technologies in reference to the answers given in (2). Recommend the relevant solutions to mitigate the disadvantages as evaluated in (4).

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

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Concept explainers

Fundamentals of Big Data Analytics

Big data analytics is the process of using advanced analyzing techniques against huge variant data sets to uncover hidden pattern or knowledge. It helps in organization's decision making process. Big data can be organized in any of the following formats.

Question

4.
Evaluate FIVE (5) disadvantages of proposing the big data and cloud technologies in
reference to the answers given in (2).
5.
Recommend the relevant solutions to mitigate the disadvantages as evaluated in (4).

Case Study – Big data technologies-based application is used to process, analyze
and store the supply chain industry data.
The ever-increasing importance of supply chain industry has brought together numerous
challenges. Specifically, challenges are in collecting, processing, analyzing, and storing
of data. These are due to the digitalization and automation devices have generate huge
amount of data in the supply chain's applications.
The supply chain industry applications collect data from multiple participants such as
manufacturers, retailers, vendors, etc. The data is useful for planning, sourcing and
development, execution, delivery and return of products.
Currently, most of the supply chain applications still utilize traditional data processing
systems to monitor and manage the real-time logistics tracking such as for sales numbers,
inventory levels, delivery time, vendor, and shipping details, to name a few. In addition,
most of the applications do not employ machine learning algorithms for prediction in the
supply chain applications.
Based on the above case study, answer the following questions.

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