This paper describes and expands discussions on the functions and issues related to Data Warehouse Administration, Security And Future Trends. A data warehouse is simply a system which stores a large piece information and it’s used for reporting and analyzing data. It integrates data from multiple different sources of information and transforms them into a multidimensional representation for decision support application that is also characterized by a complex life cycle (Kimball & Ross, 2013). This system is capable of storing a large amount of information which is in most cases significant in managerial decision making. Data warehouse administration refers to time variant, subject oriented, integrated and collection data that supports management decision making. Data warehouse security issues attached to the process of making sure all data are safe though it’s a bulk/huge information stored. Data security is concerned with sustainability and reliability of information. The future trend of data warehouse simply entails the changing pattern in the improvement or creativities involved in data warehouse system.
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The Data Warehouse Administration role specifies the requirements and approach needed for keeping the system, utilization and continuing updates in the data warehouse (Harris, 2013). The Warehouse Administration approach is designed purposely for pointing out areas like the scheduling and version control, data governing, audit, security and data warehouse usage. The workflow in the warehouse administration, tool requirements, evaluation, and testing are also addressed here. Modules are established and built for version control, scheduling, recovery and backup, version control, data governing, audit, security and data warehouse usage. In addition, several administration and monitoring tasks are addressed and this is one of important functions of data warehouse administration.
The warehouse administration is a stable and predictable source of data that is suitable for decision making of an entity/company. The only issue that can arise from this function is that in case there is malfunctioning of the system otherwise its best for that function. The data warehouse administration is a system that entails management and administration of data. It is made up of both software and hardware that communicate and, which have been designed and optimized for cross records analysis hence significant role of Data warehouse administration functions (Harris, 2013). It’s a system that allows many different users to access key data irrespective of the owners of the data, independent of the information technology staff, and independent of their skill as traditional computer programming. This creates motivational aspects to the users of this system because they can feel that part of ownership and work better.
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The monitoring task includes approval to access suitable data levels, identifying repetitive queries, calculating metrics monitoring usage, governing queries, for example the transaction of any financial references (Doan & Ives, 2012). Defining access thresholds, adding or removing users, any users can be denied access incase the user has checked out from an organization or expelled. Also, updating access authority, authority are given to those responsible for update so that they can do the update. To offer successful continual support as well as warehouse maintenance, there should be on automation of the administration functions in every possible way.
As the data warehouse stores a large volume of information, the security of this particular information is very crucial for the reliability and sustainability of these data. The gradual change in the technological aspects have prompted change in security as well (Kimball & Ross, 2013). Eventually data warehousing has improved immensely as a discipline of technology over time, initiatives that execute data warehousing enterprises continue encoutering difficulties with the dynamic technological environment. The data warehouse is assumed to offer support current prospects, such as supply chain management and customer relationship management, and it has direct impacted to the rise of e- business. In addition, vendors of Data Warehouse that have developed new and more sophisticated technologies acquired and combined together associated merchants, number of packaged software applications in the context of the average commercial enterprise has experienced rapid growth, allowing quick information delivery as well as data sources options.
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With the huge storage activities of warehouse, there are several issues/challenges that are associated with future trends in data warehousing. As far as technology discipline is concern, the trend is positively emerging and most large enterprises have completed some form of data warehousing initiative, either an enterprise-wide data warehouse or one or two departmental one and hence varying degrees of success are achieved. For instance, many organizations are now in the process of reengineering or totally rebuilding their data infrastructures. Harris (2013) argues that almost one-third of data warehousing efforts through 2001 are yet to be done with. The areas of challenges in trending data warehouse includes the following : Some organizations have failed to create the killer apps that actually deliver the benefits of the data warehouse to the end users, Another issue is not architecting the data warehouse for performance, scalability and reliability, Many enterprises do not take future needs into account when building their initial data warehouse and fail to anticipate the demands of warehouse operations, the quality of data issues are often not taken serious in initial data warehouse implementations, Enterprises do not focus attention on the negative impact of poor data quality until after their data warehouse is already up and running. Besides, many data warehousing projects simply fall into the late-and-over budget trap (Harris, 2013). Enterprises fail to anticipate the scope of their data warehousing projects and do not implement proper project planning. These trends includes Exploding Data Volumes, Integrated Customer View, More Complex Queries, and Fusion with CRM, Hub Versus Relational Databases, Active Data Warehouses, Outsourcing, and Proliferation of Data Sources.
Regarding the future of data warehousing, it is likely that the data warehouses will continue adjusting their position as a result of Hadoop. Following this occurrence, competition will become a common thing especially due to emergence of data lake architecture that operates on the platform of Hadoop. Cost savings on storage and software are some of the advantages that are provided by these data lakes. The context of newer organizations will become more interesting; because they will be provoked to adopt data lake approach based on economic consideration that they provide software and storage benefits. For instance, in line with the findings of Kimball and Ross (2013), HortonWorks, MapR as well as Cloudera have already started embracing this strategy. It should, also, be clear that data warehousing will face a lot of changes whose effects originate from the sphere of data warehouse automation. Harris (2013) points out that productization of data administration and data modelling will be inevitable in order to speed up the implementation period. And just like all other issues that relate to enterprise computing, it should be clear that the possibility of data warehousing fading off is inevitable. Furthermore, there will be increased logical and physical consolidation of data as a way of decreasing costs. Finally, the prospects of organizations essential for achieving return in regard to their investments in data in warehousing may diminish given lack of coordination with big data.
In conclusion, this paper described and expanded discussions on the functions and issues related to data warehouse administration, security and future trends. The Data Warehouse Administration role specifies the strategy and requirements for the maintenance of the system, use and ongoing updates to the data warehouse. The warehouse administration is a stable and predictable source of data that is suitable for decision making of an entity/company. With the huge storage activities of warehouse, there are several issues/challenges that are associated with future trends in data warehousing. These trends includes Exploding Data Volumes, Integrated Customer View, More Complex Queries, and Fusion with CRM, Hub Versus Relational Databases, Active Data Warehouses, Outsourcing, and Proliferation of Data Sources.
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