Business intelligence systems

BUSINESS INTELLIIGENCE SYSTEMS 6

Businessintelligence systems

Businessintelligence systems

Businessintelligence systems as examples of application software used toobtain, conduct analysis, transform and give reports on the datacollected for intelligence in business. The systems are generallyused to read data that has been stored before and this may oftenthough not necessarily take place in a data mart. The tools includespreadsheets, digital dashboards, and data mining.

Spreadsheets

Theseare computer applications that are interactive and are used for theorganization, analyzing, and the storage of collected data in a formknown as tabular. These spreadsheets are made as simulations that arecomputerized and in form of accounting worksheet paper. Thespreadsheets work on data that is arranged in columns and rows wherethe work is represented as array cells. The cells in an array arecontaining data that may be either in text or in numeric form. Inother instances, the data may be the outcome of a calculation using agiven formula.

Spreadsheetsor worksheets are often used to solve various problems in thebusiness world. One of these issues is the calculation of compoundinterest. The spreadsheet uses data that has been collected fromcalculations made on compound interest. The data is arranged in thespreadsheet using the rows and columns placed in the cells of anarray. An individual can easily identify the information from thespreadsheet. Spreadsheets simply arrange complex data in a way thatcan be easily understood and read.

Spreadsheetscan be classified as small-scale level solutions because they usuallyprogram and asses data at individual levels or even company levels.Spreadsheets can give reports that are in number form or those thatare in text form. Any type of data can be searched usingspreadsheets. The spreadsheets are designed in a way that allows anytype of information to be searched on them. Spreadsheets are usuallyused as Microsoft office programs. It is therefore clear that theworksheets interact with Microsoft office tools (Li, Hseih &amp Rai,2013).

Digitaldashboards

Adashboard is an instrument used in management information systems toshow a graphical representation the historical trends or the currentstatus of a company or a firm. The dashboards are usually in veryeasy to read, a user interface that is real-time and usually a singlepage. In other words, a dashboard is simply a company’s progressreport which is displayed on the web page of a company and can beeasily accessed. The dashboards are very essential to a firm or anorganization. They help provide a summary of the progress the companyis making. By providing the information that is accessed by anyone atany time can help, the company improves and develops itself byknowing the rate at which it is progressing.

Theproblem solved by the dashboards can be classified as an enterpriseproblem because the tool gives information on a large-scale basis,which is a representation of a whole company. Reports that aregenerated from the dashboards are usually in graph form. Thesereports are usually a graphical representation of what is going on inthe company. Dashboards that are digital, usually give a detailedsummary of what is being represented by the system. They provideinformation that is necessary for the advancement of the company(Anandrajan, Anandrajan &amp Srinivasan, 2012).

Digitaldashboards have the ability to search for data that is both numericand in text form. The information may have different types ofpresentations e.g. graphs, charts and others but the information isalways in summary form. Digital dashboards are a diagrammaticrepresentation of the needed information. This means that the diagramhas to be developed using Microsoft office tools, which clearly showsthat this type of business intelligence system can interact withMicrosoft office tools.

Datamining

Itis a subfield in computer science that is used in the computationalprocess of identifying large data set patterns. This system, extractcomplex data and transform it into simpler data that can be easilyunderstood. Another function of data mining is to automatically andsemi-automatically analyze large amounts of data to extract clustersfrom the data that are previously unknown. It applies databasemethods including spatial indices.

Thefunction of data mining is evident. The business intelligence systemis used to identify previously unknown data from a complex amount ofdata and it simplifies collected data that is very complex. Thismethod is an enterprise level solution due to the fact that it isused in instances where large amounts of data are involved and solvesproblems that are viewed to be complex. Data mining is used toretrieve information that may be numeric or even in text form (Cheng,Chiang &amp Storey, 2013).

Generatedreports are usually of information that is developed from a largeamount of data. The reports given are usually very relevant but theinformation cannot be reused in the future. Data mining does notinteract with Microsoft tools because the process has its own systemsthat have been developed to deal with the complexity of the dataassessed using data mining.

Table summary

Business intelligence system

Problem solved

Type of solution

Types of reports generated

Data that can be searched

Capability to interact with Microsoft tools

spreadsheets

Used to solve data identification issues

Small-scale level solution

Generates reports in columns and rows

Any type of data

Used together with excel tools in Microsoft

Digital dashboards

Used to show company or firm progress using tools like graphs and charts

Enterprise level solution

Reports that show progress reports

Progress charts or graphs

Generated using Microsoft word tools

Data mining

Used to simplify complex data or to retrieve clusters of data from complicated information

Enterprise level solution

Simplified data from that that was complex

Complex data

Not compatible with Microsoft tools. They have their own systems put in place

References

Anandarajan,M., Anandarajan, A., &amp Srinivasan, C. A. (Eds.). (2012). Businessintelligence techniques: a perspective from accounting and finance.Springer Science &amp Business Media.

Chen,H., Chiang, R. H., &amp Storey, V. C. (2012). Business Intelligenceand Analytics: From Big Data to Big Impact. MIS quarterly, 36(4),1165-1188.

Li,X., Hsieh, J. P. A., &amp Rai, A. (2013). Motivational differencesacross post-acceptance information system usage behaviors: Aninvestigation in the business intelligence systems context.Information Systems Research, 24(3), 659-682.