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Data Management Architecture The rapidly changing business environment warrants organizations to stay up-to-date and ready for any challenges as...
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I want a three-page Literature Analysis/Review paper on business intelligence

with ten sources in MLA format. I have attached full instructions and a sample of what I want. I want excellent quality with perfect English.

1. Data Management Architecture The rapidly changing business environment warrants organizations to stay up-to-date and ready for any challenges as well as available opportunities. The current global environment also affects the consumers and government decisions impacting the decision making process adopted by the organizations. In such an environment business can be adaptive to environment, reactive to the environment, anticipative to the future changes or they can be proactive to the changes. To meet the current business needs, almost all the organizations uses computer based system which generates tons of data. The data captured, is utilized by businesses in order to make informed decisions. The business intelligence as a whole combines the data-warehousing, analytics, performance and user-interface. The first step to business intelligence is data warehousing and in the following text the report will throw light on key components of data warehousing. 1.1. KEY CONCEPTS OF DATA MANAGEMENT ARCHITECTURE As discussed earlier, this section will discuss about the key components of data management architecture including data warehouse, data lake and data mart. 1.1.1.Data Warehouse The data warehousing is basically a process of taking raw data and transforming it into an organized information and present it in a user-friendly way so that the businesses can take fact based decisions[Kim04]. In 1999, William Inmon had defined the data warehouse as a subject oriented collection of non-volatile data having time as variable in order to support the business decisions. In short, the data warehouse is a system which captures, reports and analyses the data and is also considered as the key component of the Business Intelligence[Ded16]. It is a central resource which collects data from varied sources and stores collected data at a central place which then can be used for analytics and decision making[RJM14]. 1.1.2.Data Lake In 2010, the CTO of Pentaho, James Dixon has described the data lake in an easiest way, he has pointed in one of his blog, that if the data-mart can be taken as the packaged water – clean and pure water ready for consumption, then the data lake can be described as the water-body in its natural state[Dix10]. He further added that the data sources can be termed as the streams to fill the lake and then the end users can come into lake to examine and take samples. In a nutshell, with the help of data lakes businesses can store as much data as possible in its natural state for future usage. It takes data from varied sources and stores the data for future processing and decision making[Tan15].
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1.1.3.Data Marts As discussed in the previous section of data lakes, data marts are like bottled water – clean, pure and ready for consumption. The data marts are the last layer or the access layer in the data warehousing concept which allows the end users to access the data set. It is basically a subset of the data warehousing and usually they are oriented towards specific task (line of business or teams)[Inm00] 1.2. USE OF THE DATA WAREHOUSE, DATA LAKE AND DATA MART IN AN ORGANIZATION The data flows from varied sources in an organizations and may not be consistent. To make them unified and consistent with the business requirements data warehouses are used. The data warehousing process is divided into three main categories: Extract, Transform, and Load. The process is also known as “Schema on Write” as the data entered into data warehouse is given certain structure or schema[Lev16]. The data warehouse is widely used in the banking industry, as the analysis of the transactional data can provide great insights into consumer spending, banking usage, and merchant classifications. The data warehouse being the structured data storage facility makes it the apt tool for the industry[Tha16]. On the other hand, the data marts provide insights into the line of business or departments or the specific teams. It may restrict the usage of data to a specific department of the business. For example, in a manufacturing setup, the data of the financial transactions may be restricted for the shop floor employees. To provide such an arrangement data marts are used. If we consider data warehouse as the central repository, then the data marts can be termed as the local repository accessible for specific line of business or department[Lev16]t. Recently the data lake concept has been coined by Mr. Dixon which has caught the attention of the IT professionals. Unlike the data ware house, it is used for storing voluminous data into its raw formats. It allows the data storage at lower cost at the same time it provides agility and flexibility to access and transform. It uses a process of Extract, Load, and Transform as against the data warehouse’s process of ETL. One of the biggest example of data lake is the cloud storage services. Bibliography Dedic, N. & Stainer, C., 2016. An EvaluaTon of the Challenges of MulTlingualism in Data Warehouse Development. ICEIS 2016, p. 196. Dixon, J., 2010. Pentaho, Hadoop, and Data Lakes. [Online] Available at: h±ps:// [Accessed 23 July 2017]. Inmon, W., 2000. Data Mart Does Not Equal Data Warehouse. [Online] Available at: h±ps://±p:// %20Warehousing/ArTcles/Data%20Marts/dataWarehouse_com%20%20ArTcle_DM%20VS%20DW.htm [Accessed 23 July 2017].
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Task 1 Data Management Architectures (Worth 30 Marks) For Task 1 you are required to conduct a critical literature review of the related concepts of data warehouses, data lakes and data marts in order to complete two sub tasks. Task 1.1) Define and discuss the concepts of (1) a data warehouse, (2) a data lake and (3) a data mart drawing relevant and reputable literature (about 450 words). Task 1.2) Explain how a data warehouse, a data lake and a data mart would be used in an organizaTon and in your answer provide some real world examples of how each would be used in an organizaTon (about 450 words).
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Subject: Business, Management

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