Being a market leader today requires competitive advantage over rival organizations. By investing in data warehouses, organizations can better predict the trends in market and offer services best suited to the needs of their customers. A Data Warehouse (DW) can be defined as a subject-oriented, non-volatile database having records over years [1,2]. DWs support the strategic decision-making process and help to answer questions such as "Who was our best customer for this item last year?"[3].
Different DW systems consists of different components, however, some core components are shared by most DW systems. The first component is the data sources. DW receives input from different data sources (such as Point-Of-Sales (POS) systems, Automated Teller Machines (ATM) in banks, checkout terminals etc). The second component is the data staging area. The data comes from data sources and it is placed in the staging area, where the data is treated with different transformations and cleansed of any anomalies. After this transformation, the data is placed in the third component which is known as storage area, which is usually a Relational Database Management System (RDBMS). This process of data extraction from data sources, transformation and finally loading in storage area is regarded as Extract, Transform and Load (ETL). The saved data from the storage can be viewed by reporting units. Different On-line Analytical Processing (OLAP) tools assist in generating reports based on the data saved in the storage area [4,5,6,7,8].
We believe that testing should be ingrained in DW development. Thus, each of the DW components should be tested. One of the main challenges in testing the DW systems is the fact that DW systems are different among organizations, each organization has its own DW system that conforms with its own requirements and needs, which leads to having differences between DW systems in several aspects (such as database technology, tools used, size, number of users, number of data sources, how the components are connected, etc.)[9]. Another big challenge that is faced by the DW testers is regarding the test data preparation. Making use of real data for testing purpose is a violation of citizen’s privacy laws in some countries (for example, using real data of bank accounts and other information is illegal in many countries). For a proper testing of a DW, presence of a huge amount of test data is necessary. In real-time environment, the system may behave differently in the presence of terabytes of data [10].
This testing level will also occur during the early development of the application but not until each of one of the subsystem’s unit functions have been fully tested and are ready to be implemented. While all three subsystems, financial, appointments, and patient records may not be tested in tandem each should be able to have basic testing performed with the use of test cases for input. Once they have completed testing, we could then use the same or similar test cases for the integration level testing of all subsystems.
Data warehouse developer is responsible for maintaining the practices of modeling, dimensional data, relational structures, and other reporting techniques. Candidates possessing an inner desire for long term employment opportunities in a team oriented fast paced wonderful environment. They need to be qualified with Information Systems, Computer Science and other related fields. It would be preferable to possess minimum of 7 years’ experience with warehouse design and analysis experience with complete knowledge about data modeling and warehouse methodologies. Job requirements for Albertsons Data warehouse developer jobs-
The company can make use of SAP BW/4HANA warehouse in order to perform any analytical operations on real time data. Using this data warehouse the company can generate reports which will be helpful: • For the business managers to know more about their product manufacturing and distribution costs. These reports will provide them with necessary information so that they can build new ways to reduce overall
Smith, W., & Jewett, D. (2009). Tableau software and teradata database the visual approach to the active data warehouse. In Retrieved from http://www.tableausoftware.com/learn/whitepapers
The system of ETL is in general utilized to join in the data from numerous applications in the systems, characteristically established as well as reinforced by a number of existing vendors or others held on distinct hardware of the computer. The distinct systems comprising the actual data is most repeatedly accomplished as well as run by a number of employees. Referring to example of system used for cost accounting, it is evident that this system would thereby collate the information flow from payroll, transactions as well as acquiring. In the process of ETL, the initial phase comprise of the data extraction from the number of sources in the existing systems. In numerous circumstances this refers to the actual challenging factor of the process of ETL, subsequently the data extraction appropriately initiate the efficacy platform for by what means succeeding developments would further advance. The second phase of transformation in ETL process implies a chain of guidelines along with the necessary functions applied on the data after extraction from its source to develop the output data for effectively loading (Wyatt, L., Caufield, B., & Pol, 2009). A number of sources of data need precisely slight or sometimes absolutely no data manipulation. The last phase of data loading on the target end typically referred as the data warehouse. On the basis of the necessities of the businesses, the ETL overall process differs extensively. A number of data warehouse possibly will overwrite the present data by means of collective information; commonly, appraising the data which is extracted carried out based on the frequency of day-to-day, week on week, or month on month.
In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
"Although fully searchable text could, in theory, be retrieved without much metadata in the future, it is hard to imagine how a complex or multimedia digital object that goes into storage of any kind could ever survive, let alone be discovered and used, if it were not accompanied by good metadata" (Abby Smith). Discuss Smith's assertion in the context of the contemporary information environment
... different layers such as ETL stage, SIF, BDW and how data is processed to generate reports according to the requirement. The processing of information from raw data to different processing stages culminating in coherent information is fascinating.
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
It is main operations where companies can provide tailored services for their customers in order to gain competitive advantage. The WMS is a database driven computer application which used to improve the efficiency of the warehouse and ensure the accuracy of inventory by recording warehouse transactions. It aims to control the movement and storage of raw materials within a warehouse and process the associated transactions where including shipping, receiving, put-away and picking the materials or finished goods. It used to improve the efficiency of the warehouse maintain accurate inventory by recording warehouse transactions (Ramaa.A, 2012) . This paper has highlighted the findings of the study carried out to evaluate performance levels of the WMS and enhance productivity of the manual warehouses by developing a WMS framework and cost benefit analysis. There was a metrics for measuring the performances of warehouse based on order fulfillment, inventory management and warehouse productivity which may use to audit warehouse performance and assess to WMS potential. From results of the case study showed, the cycle time of the process, non-value added time, manpower required has reduced with the WMS. Besides, with the WMS, the time scheduling for the products has become possible, and this has reduced the waiting time of the suppliers. In addition, the warehouse will has prior
Software development follows a specific life cycle that starts with designing a solution to a problem and implementing it. Software testing is part of this software life cycle that involves verifying if each unit implemented meets the specifications of the design. Even with careful testing of hundreds or thousands of variables and code statements, users of software find bugs. “Software testing is arguably the least understood part of the development process” and is also a “time-consuming process that requires technical sophistication and proper planning” (Whittaker 71) It is important to comprehend this concept by understanding the different characteristics and aspects of software testing, and then to examine the techniques, procedures and tools used to apply this concept. This will enable the user to realize the problems faced by software testers and the importance of software testing.
Databases are becoming as common in the workplace as the stapler. Businesses use databases to keep track of payroll, vacations, inventory, and a multitude of other taske of which are to vast to mention here. Basically businesses use databases anytime a large amount of data must be stored in such a manor that it can easily be searched, categorized and recalled in different means that can be easily read and understood by the end user. Databases are used extensively where I work. In fact, since Hyperion Solutions is a database and financial intelligence software developing company we produce one. To keep the material within scope I shall narrow the use of databases down to what we use just in the Orlando office of Hyperion Solutions alone.
The dynamics of our society bring many challenges and opportunities to the business world. Within the last decade, hundreds of jobs have emerged particularly in the technology sector to help keep up with the ever-changing world and to compete on a larger and better scale than the competition. Two key job markets and the basis of this research paper are business intelligence or BI and data mining or DM. These two fields play a very important role in small to large companies and are becoming higher desired sectors within the back offices of the workplace. This paper will explore what the meaning of BI and DM really is, how they are used and what we can expect as workers and learners of the technology and business fields for the future.
The Database Management System (DBMS) is software that enables the users to define, create, maintain and control the access to the database. It is a software that interact with the user’s applications programs and it database. Meanwhile, information retrieval system is a system that involved the activity that the systems obtain the information. The obtaining information action need the information from it resources.