Business Intelligence and Analytics Capabilities - Essay Example

Implementation Plan for the Building up of Bi and Analytics Capabilities in your Chosen Organization Name Institutional Affiliation Date Introduction Business Intelligence has become a fast growing tool that managers and people in senior management positions use when making crucial decisions concerning the organization (Michalewicz 2007). The importance of BI is much alive in its software version. This software and BI system is critical in the formulation of strategy and monitoring the implementation of the foresaid strategies. Many corporate bodies are currently using BI systems. This is due to their reliability and accuracy. Sometimes service providers or specific staff working in the organization can install them. Sadly, they are quite costly and very few corporate organizations .in fact, research has it that BI is one of the leading intelligence gathering tool that is preferred by many large corporate entities. The growth of BI system is closely associated with the technological advancements witnessed in the modern society. For any organization to audit its progress especially in line with the goals and objectives regarding its growth, it is imperative that they must begin to use the intelligence gathering system called BI (Michalewicz 2007). The role of BI in decision-making and the techniques that are used to make them forms the basis for this paper. BI and Analytics User Groups Figure (1) below gives a range of users of these tools in relation to the information they require. Figure (1): BI User classification People who produce information in an organization make up one category of users of BI and Analytic tools (Williams & Williams 2007). They use these tools to come up with models, dash boards and reports used by the consumers or themselves. They work on content production, road map design and are highly influential when selecting BI tools to be used b y an organization. Selection is based on tools being used and those that should otherwise be used for data analysis. Casual users also known as information consumers o n the other hand use the data produced to come up with their own spreadsheets that match their line of business. This data is then manipulated for ease during presentation or for creating a business plan model. These users also use BI to develop interactive reports and make it possible to be exported and viewed in Microsoft applications such as Excel (Data Warehousing Institute 2003). BI and Analytics Tools and their Application According to MüLler & Lenz (2013), Bi and analysis tools are used in a wide range of businesses. Customers are in demand for BI tools that do not require IT and scientific knowledge and skills. This has led to more companies decentralizing and spreading data discovery through an entire organization as opposed to previous installed base software used. Many BI tools have been developed to cater for customer needs. Figure (1) below is a summary of some of the tools classified according to their performance levels. Figure (1): BI and Analytic tools. IBM is a BI and analysis tool that has a wide coverage. It includes management of performance, advanced analytics and service organization that can be used in any geography, industry and domain. This tool is used in large centered deployments that focus on producing global reporting and centralizing BI deployment platforms. It is highly ranked in relation to usage of centralization of deployment platform. Tools under IBM include SPSS modeler, Impromptu and Cognos PowerPlay and ManyEyes. Microsoft on the other hand produces decentralized and centralized BI tools to cater for its large number of customers in terms of their need for analysis of data. Power BI part of the tool looks into analysis and preparation of self service data that focuses on business and user. Management of data, administration and reporting on the other and are conducted using Sharepoint and SQL Server. Microsoft products are business and user enabled in order to share contents of analysis in standalone software that does not require other applications like excel. This puts it at a high level in terms of delivery (Weber, Grothe & SchäFfer 2012). Actuate also referred to as Open Text includes an elaborated platform for analysis and reporting tools. It has a record in personalization of data delivery for external data analysis with its main strength being the developers of embedded analysis applications. It delivers applications that are data driven to a wide range of customers that is used for parametric as well as static reporting. SAP on the other hand is a BI and analysis tool that has a wide capability delivery. SAP Business Objects platform deals with BI deployment in large IT firms while for decentralization of data discovery, SAP Lumira is employed. They offer a simpler BI component strategy with a variety of differentiation potential. This tool can also be used in mobile devices. However, SAP is not preferred by many customers with its ratings standing at below average (Thierauf 2001). SAS provides a wide range of components that are well integrated in its BI and Analysis package. It is used for predictive modeling as well as statistics analysis and is highly innovative. It offers a large application domain and also vertical analysis applications can be carried out using this tool. Their product is highly functional and delivers quality in data analysis. It has a high frequency of data deployment. Some of its products include SAS Office Analytics, SAS EBI and SAS Visual Analytics. The other tool, Oracle has diversity in capability because its analytics and BI portfolio is equipped with a vast range of products. It is used in data deployment for large scale businesses. They have both hardware and software products such as Oracle BI Foundation Suite, Oracle Essbase and Oracle Endeca Information Discovery. It offers fragmented products that are used in record reporting and can be integrated into the system according to what the customers require (Simon & Shaffer 2001). Data to be used in BI and Analytics Marketing Information- this department uses data dealing with the needs and requirements of the user. Data is analyzed to ensure that needs are met, quality is delivered, development is streamlined and there is a good relationship with the customers. BI and Analytic tools are used on retail marketing analysis. Customer information which entails demographic location, tastes and preferences, history of purchases is collected. This data is then analyzed and a recommendation is made from each customer (Kudyba & Hoptroff 2001). Also, data concerning in store customer behavior is important. It helps a marketer come up with an environment in which a customer can make purchases at ease. This encourages the customer to increase their purchase because the retailer provides a mix of products and uses shelves so that a customer chooses for themselves exactly when they need. Such analysis and product mix can be derived at using data analysis. Data should also be collected that brings out the sentiments of the consumer. This enables the retailer to make some decisions regarding product marketing like coming up with micro-segments or personalizing service and product delivery (Kudyba & Hoptroff 2001). Financial information- Data analysis should also be carried out on the finance department. Data on allowances should be put on record to check for optimization of usage of finances. Unusual patterns on spending can be revealed by analyzing the financial flow of an organization. Such data is usually very large and companies need to utilize BI and Analytic tools to not only collect but also process such huge data chunks. This information can also be used to develop the behavior of the customer. This is made possible by the data available on competitors and customers. Competitor information can be got from real identities but their anonymity is reserved. Such information helps an organization to come up with models for customer requirements, marketing as well as maintain data privacy (Turban 2008). HR information Vitt, Luckevich & Misner 2008 observer that Data analysis deals with information consistency and completeness and the ability to change and be quickly developed. The human resource department is of importance from any organization to succeed. Information as regards to the competency of staff and management levels should be analyzed to come up with the right staff. This is because there are roles which some people can perform that others are incapable of delivering. In such cases, staff allocation is done by the BI and Analytic tool depending on the requirements. Architecture of a BI System According to Turban (2008), business intelligence is a strategy that not only deals with technology and tools but also incorporates data combination using methodology for its cohesion and solidification. The part of data in BI is referred as data warehousing. This involves development of data that has been sources, enriched, scrubbed, put in formats that are ready for access and is conformed so that its presentation is made easy. Figure (3) below gives an architecture diagram of data analysis. Figure (3): corporate information architecture BI is a delivery area tool. Operational BI deals with analysis and reporting of data through direct operational system. The platform is built to deliver large capabilities of business intelligence management using web based, centralized administration. This helps an entity to find a solution of any possible issue before it impacts on the business using the system thresholds and metrics put into place. These tiers are separable using network firewalls depending on the business function. Its architecture comprises of application, data and web server tiers. These tools are dev eloped according to the roles they play in BI data analysis. The system software on the other hand comprises of an individual analyst’s client applications, client service application specific server and a centralized facility for mega data management (Vitt, Luckevich & Misner 2008). Training and system support options For business intelligence to be effectively integrated into any company, its users must fully utilize and accept its usage (Vitt, Luckevich & Misner 2008). In order for the users to readily accept it however, they should be consulted during the early dev elopement stages. Therefore, training needs to be offered to business users and the requirements to have such a system in to place. This is because such a system requires a high knowledge on operation otherwise there will be failure in analysis or results delivered will be lacking in quality and correctness. Senior management should also be rained on how to use BI and Analytics tools so that they can make informed decision on the choice of the best tool among the vast types that matches their company’s requirements and role. These tools are used by all staff in an organization to conduct data analysis at their skill levels. Therefore, all staff within an organization, both external and internal should be trained on BI and Analytics tools usage according to the data they are meant to analyze (Vitt, Luckevich & Misner 2008). Conclusion BI and Analytics tools are essential for an organization to achieve its financial as well as operational goals. This is through the avail ability of comprehensive tools for data analysis which makes it easy for employees to have knowledge of their working environment, business processes as well as their applications. Data can be easily understood because these tools put it in a multi-dimensional presentation. This gives business advantage to the users compared to their competitors using the older means of data analysis. A thorough understanding of BI equips a company with ability to deliver quality reports in interactive manner and also enables sharing of information. It gives the organization information on what has already been done and what they should do to gain optimum results. When such a system has been implemented, the less time is spent analyzing data. This means that employees get more time to attend to customers and more profit margins can be realized. However, it is of importance to note that the infrastructure and architecture implementation of this tool is very expensive. Employee training may also strain a company and some of the staff might find it hard to use the application. However, the end benefit of having it overrides its financial constraints for big data analysis (Vitt, Luckevich & Misner 2008). References Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Bottom of Form Top of Form Data Warehousing Institute. (2003). Business intelligence journal. Seattle, WA, 101communications. http://www.tdwi.org. Kudyba, S., & Hoptroff, R. (2001). Data mining and business intelligence a guide to productivity. Hershey, Pa, Idea Group Pub. http://www.books24x7.com/marc.asp?bookid=2901. Michalewicz, Z. (2007). Adaptive business intelligence. Berlin, Springer. http://site.ebrary.com/id/10152655. MüLler, R. M., & Lenz, H.-J. (2013). Business Intelligence. Berlin, Heidelberg, Imprint: Springer Vieweg. Simon, A. R., & Shaffer, S. L. (2001). Data warehousing and business intelligence for e-Commerce. San Francisco, Morgan Kaufmann. http://www.books24x7.com/marc.asp?isbn=1558607137. Thierauf, R. J. (2001). Effective business intelligence systems. Westport, CT, Quorum Books. http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=69283. Turban, E. (2008). Business intelligence: a managerial approach. Upper Saddle River, N.J., Pearson Prentice Hall. Vitt, E., Luckevich, M., & Misner, S. (2008). Business Intelligence. Redmond, Microsoft Press. http://encompass.library.cornell.edu/cgi-bin/checkIP.cgi?access=gateway_standard%26url=http://techbus.safaribooksonline.com/9780735626607. Weber, J., Grothe, M., & SchäFfer, U. (2012). Business Intelligence. Weinheim, Wiley. http://public.eblib.com/choice/publicfullrecord.aspx?p=1120316. Williams, S., & Williams, N. (2007). The profit impact of business intelligence. Amsterdam, Elsevier/Morgan Kaufmann. http://www.myilibrary.com?id=74696. Bottom of Form Top of Form Read More