Case Study Considerations For Moving To Cloud

Real-time data warehousing creates some special issues that need to be solved by data warehouse management. These can create issues because of the extensive technicality that is involved for not only planning the system, but also managing problems as they arise. Two aspects of the BI system that need to be organized in order to elude any technical problems are: the architecture design and query workload balancing.

This research paper tackles the issues that faces Cloud Computing today and gives the experts and industry’s point of view on the matter. The aspects explored are the significant industry questions that have risen about the use of Cloud Computing, business value, organization impact, adaptability, limitations, initial cost of implementation, and the severe business security risks

Legacy systems tend to provide a significant value for companies. This is due to the fact that they still meet user needs and are capable of capturing vital business logic. The cost of replacing these legacy systems with a system designed completely from scratch is much too high, but reusing a legacy system can be equally difficult due to the fact that legacy system reuse comes with its own set of obstacles like platform, documentation, and architecture issues. Cloud Computing has come along and it provides the promise of significantly lower costs with enhanced performance capabilities

Enterprise Data Warehouses (EDW) have become the foundation of many enterprises' systems of record, serving as the catalyst of strategic initiatives encompassing Customer Relationship Management (CRM), Supply Chain Management SCM) and the pervasive adoption of analytics and Business Intelligence (BI) throughout enterprises. The role of databases continues to be an ancillary one, supporting the overall structural and data integrity of the EDW and increasing its value to the overall enterprise (Phillips, 1997). The advances made over the last decade in the areas of Extra, Transact & Load (ETL) have made it possible to create EDW frameworks and platforms more efficiently, creating greater accuracy in overall database and data warehouse performance as a result (Ballou, Tayi, 1999). The creation and use of an EDW to further drive an organization to its objectives requires that the differences between databases and data warehouses be defined, in addition to a clear, concise definition of just what data warehouse technologies are. Finally, the relationship between data warehouses and business intelligence (BI) including analytics needs analysis and validation. Each of these three areas are discussed in this analysis.

The information technology industry is growing at a rapid pace. Every business entity needs some form of IT support to ensure that business operations are continuously running. As an entity grows in size and revenue, the information system needed to support the entity needs to grow as well. Some businesses may not have enough resources to accommodate this expansion. Their building may be too small or they cannot afford to purchase the equipment. When this is the case, an organization will choose to migrate their network infrastructure to a cloud computing environment. Cloud computing allows for a company to implement a large scale network without having to incur expenses for modifying the building infrastructure. Cloud

A proof of concept ought to be huge and sufficiently critical, that it can completely speak to the key parts of the platform and application. The POC must test the basic functionality of the application in the cloud environment. The company can begin with a small database. The company also ought to do Stress testing and the performance testing using automated tools.

The growth of cloud services has begun a transition of companies to partially or completely move services and abandon on-site data centers in favor of a cloud based solution. This movement has become a phenomenon for businesses; however, before a business implements any type of cloud solutions it must consider several things.

Cloud computing is an altering technology which is enjoying increasing rates of adoption. Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources including networks, servers, storage, applications, and services that can be rapidly provisioned and released with minimal management effort or service provider interaction. The use of Cloud services is proven effective across diverse set of industries, reducing costs associated with computing while increasing flexibility and scalability for computer processes. For instance, Cloud computing services, like Amazon’s, can be used by all business types and more ideal for smaller businesses or especially ideal for businesses just starting. This report is a recommendation for moving all our company’s data center functions on to the cloud. This report outlines supporting details determining how our company could reap the most benefits by adopting cloud services from any of the high-quality cloud service providers available in the market today such as Amazon, Microsoft, Rackspace, and Verizon Terremark cloud services. The benefits of adoption cloud computing services are substantial including reduced infrastructure costs, increased scalability, availability, capacity, speed, backup and mobility. However, these benefits are not free from possible pitfalls. So, to maximize the benefits and minimize risks associated with the move to the cloud, it is

Cloud computing is revolutionizing every aspect of Information Technology. Many businesses and organizations rely on their own internal IT departments to operate their specific applications, databases, and programs. Cloud allows them to cut ties with in-house servers and receive their complete IT needs from an external Cloud provider. Cloud is faster and easier to use than traditional infrastructures, often making it more cost effective. Several private companies have already switched to Cloud and the federal government has ordered every agency to identify at least three “must move” services and shift them to Cloud by mid 2012. (Scharff, 2011)

Volume is often regarded as the primary attribute of big data. With that in mind, a large number of people define big data in terabytes—sometimes petabytes, but big data can also be quantified by counting records, transactions, tables, or files (Russom, 2011). Volume refers to the mass quantities of data that organizations are trying to harness to improve decision-making across the enterprise (Schroeck et al., 2012). The volumes of data have continued to increase at an unprecedented rate over the last couple of years. The sheer volume of data that is stored or available for storage today is exploding, it is expected that by the year 2020 40 zetabytes (ZB) of data will be stored (Zikopoulos et al. 2012) which

Data warehousing is one of the hottest industry trends - for good reason. A well-defined and properly implemented data warehouse can be a valuable competitive tool. (Perkins).

Cloud computing is currently being used by a large number of organizations. Many consider it a major development of the decade in computing. In this article I define cloud computing, various services available on the cloud infrastructure, then discuss the technological trends which have led to its emergence, its advantages and disadvantages, and the applications which are appropriate to outsource to a cloud computing service.

The purpose of a data warehouse is to make the company’s information accessible and consistent. They need to have the information immediately available and in the same format. Warehousing is of no benefit to a company if they have to wait any length of time to receive the data. A warehouse has to be an adaptive and durable source of information for the business. The warehouse has to be flexible to meet the needed changes of a business, as the business grows; it is possible that additional information will need to be collected. The warehouse needs to have the ability to expand to meet the needs of the business. Warehousing would not be beneficial to a business if they have to seek a new warehouse source each time a change was needed; it would be costly for a business. A data warehouse must be a secure stronghold that protects the information, which is regarded as an asset to the business. In today’s society it this the utmost concerned of a business to make sure that their systems are not easily hacked by outsiders and their customer’s data is secured. Lastly, a warehouse is considered the foundation for decision making. It is the data that is retrieved from the system that is compiled for presentation to the decision makers of the company.

In early 80s business world more concerned about the large amount of data that is emerging from their customer world and worried about how to store that amount of data, during that time old business instruments took a large amount of time to execute the business instead of running it and it is also costly, time consuming and risky to deals with that much big amount of data (Inmon, 2005). The concept of data warehousing dates back to the late 1980s when IBM researchers Barry Devlin and Paul Murphy introduced the term “Business data warehouse”. In 1986, Red Brick Systems founded by Ralph Kimball began to do research on improving data access (Hammergren, 2005). In 1990s executives become less concerned with the day-to-day business operations and overall concerned with overall business functions and worried about large amount of data. Due to the improvements and magnification in the information systems where large amount of data needs to be saved and retrieved, data warehousing was additionally enhanced and advanced to cope up with such immensely large amounts of data (Kelly, 2009).

Data warehouses are being used by all types of businesses, including profit and not-for-profit organizations. Their use also spans many industries, including governments. The collecting and storing of large volumes of data from all information systems within an organization provides a single source of information for management decision-making.