Unit 3: Warehouse Management and Support Processes 3.1 Introduction Warehouse and Support process are drafted to label the management and planning the data warehouse projects that are analytical to the successful execution and successive extension to the data warehouse. The system is defined to facilitate the project manager and warehouse instructor during the development projects. The software helps in building the companies goal to reduce the chances of transactional errors, minimize the material handling and optimizing the warehousing projects. There are many organizations that are into the selling of WMS (Warehouse Management System) which has pros as well as cons. There are some products which may fit to it better with the capital expenditure
Introduction Data warehouse architecture is the base of data warehouse. Three major areas of data warehouse architecture are data acquisition, data storage and information delivery. Data acquisition refers to data extraction from various source systems, data transformation in data staging area and preparation for loading data in data storage. Data storage is responsible for loading data from data staging area to data warehouse. Information delivery is responsible for delivering the information to data warehouse users.
The resource-based model introduces a different perspective - from competitive positioning model - to strategic planning by looking at the resources and capabilities of the firm. Prior to the development of the resource-based model, strategic planning consisted only of the competitive positioning model, whose origins came from Porter’s Five Forces model. However, competitive positioning looks only at the industry; it stresses the need for external
A database that does perform analytics is a warehouse database. This database warehouse takes information from all the databases and analyses their information. Optimized for delivering one-time transaction the OLTP database should have time-interval response
System development methodologies History The system development methodologies also known as SDM never came before 1960s. According to the Elliott 2004 the oldest formalized methodology is the system development life cycle (SDLC). This is well organized methodology framework for building information systems. The system development methodology is a framework which is used to plan, structure & control the process of develop or maintain information system. The methodologies that are being created for the development of the project depend on the project aims and goals.
DESCRIPTION OF DATABASE MANAGEMENT SYSTEM The database is a collection of some data and number of figures that can be treated to make information. Data represents contain facts. By using the Database Management System we can easily arrange the data in any simple manner. Database Management System will help to store the data where we can easily recover, operate and create information. EVOLUTION OF DATABASE Since, there are several advancement in the electronic industry, it paved the path for computer scientists to develop various techniques to store a large amount of data in an efficient, and sophisticated manner.
Since, it encompasses wide range of activities, which most of time transcend factories or national boundary, complex interdependencies are built into it. As the power base continues to shift from companies towards customers, customer demands have gotten more complex. Companies are looking at Big Data analytics to revamp their supply chain, thereby using Big Data Analytics as a strategic lever. Companies are collecting vast amount of supply chain related data with help of technologies such as sensors, Barcode and GPS, Jacob House (2014). Big Data Analytics offers companies the ability to leverage on the enormous amounts of information driving their global supply chains, Harvard Business review, (2013).
It all depends on which methodology they choose to develop their software product. Both these models have its own advantage and disadvantage. As discussed in the report every project should be deeply studied first and understand the requirements, then need to finalize the suitable model for the project. All these methodologies having different ways to produce a better software product, proper use of this methodologies will delivery best and quality product. 7.
Data is given from multiple dissimilar sources into the data warehouse. As the data is fed, it is transformed, reformatted, summarized, and so forth. The result of integration is that once the data exists in the data warehouse, it has a particular physical corporate image. In all the integration architecture, there are several difficulties that come up when attempting to integrate data from different sources. Data Selection Once the data elements are chosen from several sources, it is essential to examine the value of the data.