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ShivakumarRampallyFinanceandCustomerRelationshipManagementMindmap10022020.pptx
CRM-AID Finance and Customer Relationship Management Mind Map
Shivakumar Rampally - GR012051
Cloud Computing -202050 –CRN125
Prof - Dr. Afshin Zarenejad
New England College
Introduction & Business context
High Level Mind Map
Mind Map
Business Life Cycle
Business Web Application
Application Data Store
Application Request and Load Balancing
Compute in GCP
Storage in GCP
Data Bases
Big Data / Data Analytics
Benefits of GCP
Conclusion
References
Contents
Introduction
To build robustly scalable centralized financial system supporting the Customer Relationship Management Application for Financial Organization.
Mind Map
Mind Map 1/3
Phase 1
API Gateway acts absolute proxy between the client application and backend business systems.
API Integrations helps the interfaces to integrate with multiple system to perform interoperability of the data form the direct API services.
Pub/Sub is the module that available in Data Analytics which uses the API services to translate, transform and orchestrate the data from source of truth for data analytics.
Bigdata analytics is done by involving the components like Big Query, Pub/Sub, and ETL (Thodge, 2018, p. 131).
Data Flow is used for analyzing the streaming data both in batch process and real-time process .
Cloud storage is used for storing all the structured data and acts as a source of truth for CRM and Finance (Geewax, 2018 p. 10).
Mind Map 2/3
Phase -2
In GCP Cloud Networking products are used to protect user, development environments, end user interaction with end applications by enabling potential networking security model.
This implementation is done in 3 layers such as
Technical Administrator ( Connect)
Development and Management Tools -Scale, Secure and Monitor (Thodge, 2018, p. 89).
Deployments (Accelerating Continuous Integration and Continuous Delivery)
Mind Map 3/3
Phase -3
Identity and Access Management is an application framework which applies the electronic digital policies and processes the digital identities.
IAM allows the administrators, management portal resources to control access privileges to an application, systems from being using a critical information in an organization (Hunter and Porter, 2018, p. 57).
IAM protect the critical infrastructure on first stage of inspection by identifying the identities of a user for a software application and devices (Hunter and Porter, 2018, p. 57).
Cloud IAM is used for permission management and Cloud Key Management for encrypting the keys in GCP on multi environments (Hunter and Porter, 2018, p. 60).
Cloud Load balancing is used for check health of each servers and ingesting to input Cloud CDN to maintain the continual delivery of business operations (Thodge, 2018, p. 121).
Business Use Case Life Cycle
Compute in GCP
Google Cloud Compute Engine is an IaaS service that provides various services like VM’s, Disks, and Network that hosted on Google on-premise, cloud and hybrid infrastructure as per the business needs.
App Engine in GCP provides a serverless applications to build highly scalable and fully managed application platform (Hunter and Porter, 2018, p. 110).
In CRM –AID it is used as a shield VM’s to protect the application loads, virtual data attacks, and malicious insiders.
This is more suitable to process the persistent data in object store for batch jobs and fault tolerant activities (Hunter and Porter, 2018, p. 163).
Storage in GCP
GCP provides an efficient and effective cloud storage products such as
File Storage – it offers an option to store the data in a spectrum way in a redundant process (low latency, highly scalable and secure).
Persistent Disk – it provides read only and rapid backup options while access and processing data in and out multiple machines (Thodge, 2018, p. 60).
It scales data transformation, transition and orchestration performance by block storage in VM’s and containers.
Databases
Cloud Datastore - It is a highly scalable cloud service and completely managed by NoSQL data base service in Google Cloud Platform.
It provides the users to store, save data efficiently through one single click operation both through public and private network access based on the business need (Thodge, 2018, p. 60).
One key advantage of Cloud Storage service is it is a fully Distributed Hierarchical Key/Value Storage catering with schema less database (Thodge, 2018, p. 60).
Cloud SQL is another service of GCP databased which is fully Managed MySQL service for hosting relational databases on Google’s containers .
Data Analytics / Big Data
GCP provides variant data analytics services in which we have choose BigQuery, Cloud Pub/Sub Data Proc.
BigQuery is a serverless Data Analytics service which is operated over the highly scalable and scaled data analytics platform engine, this is supports the data retrieval from cloud storage and querying capabilities on high volume of data using SQL (Thodge, 2018, p. 62).
Cloud Pub/ Sub and Dataproc is robust service that Managed big data supporting services like Hadoop, Spark to process large datasets (Thodge, 2018, p. 77).
Business Web Application
Application Data Storage
Application Request and Load Balancing
Benefits of GCP
Google Cloud Computing Platform provides various modules to an organizations based on the industry technological needs and services.
Reduced IT Infrastructure setup
Better pricing comparing to AWS, Azure and other Cloud Providers
Provides Private Fiber Network
High availability with improved performance service
Redundant Backups for shared resources
Conclusion
Google Cloud Platform is a best suite for hybrid cloud infrastructure setup it offers multiple services for hybrid computing with services like compute, storage, networking, IAM, Security and AI.
The main advantage of GCP is highly scalable, reliable with all the customized and generic application needs.
It is easy to use for all the services developers, administrators, Management IT professionals.
References
Geewax, JJ. (2018). Google Cloud Platform in Action. p. 10.
Hunter, T., Porter, S.(2018). Google Cloud Platform for Developers. Build Highly Scalable Cloud
Solutions with the Power of Google Cloud Platform. p. 57 – 60.
Thodge, S. (2018). Cloud Analytics with Google Cloud Platform. An End-to-end Guide to Processing
and Analyzing Big Data Using Google Cloud Platform. p. 53 – 70.
Thank You!
Q&A ?
