Describe some examples of CRM and ERP implementations based on cloud computing technologies.

 CRM and ERP

CRM (customer relationship management) and ERP (enterprise resource planning) systems are two industry categories that are thriving in the cloud, with CRM being the more mature of the two. Cloud CRM programs provide small businesses and start-ups with a terrific way to get fully working CRM software without big upfront expenditures and by paying monthly fees. Furthermore, CRM is not a task that needs a certain set of requirements, and it can be readily migrated to the cloud. Cloud CRM software has grown in popularity as a result of this feature, as well as the ability to view your business and customer data from anywhere and on any device. Cloud-based ERP systems are less mature, and they must compete with well-established in-house solutions. Finance and accounting, human resources, manufacturing, supply chain management, project management, and CRM are all integrated into ERP systems. Their purpose is to give a unified perspective and access to all activities required to keep a complicated company running. The move to cloud-based models is more challenging because of the enterprises they target: the long-term cost advantage may not be evident, and the conversion to the cloud may be challenging if firms already have significant ERP installations.
Examples
Salesforce.com, Microsoft Dynamics CRM, NetSuite

Comments

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

Discuss classification or taxonomy of virtualization at different levels.