ACC 202 Accounting Information Systems Introduction

Answer:

Classification Levels
Level	Hourly Pay
1	30
2	40
3	50
4	60
5	70
6	80


Employee Name	Classification Level	Hourly Pay

Paris Holton	5	70
Ricky Mortini	4	60
Jennifer Leepoz	6	80
Selina Geemak	2	40
Willard Smith	1	30
Russell Creak	6	80
Rafael Nooderly	4	60
Novak Djoker	1	30
Lara Bangle	3	50
Kath Hudson	6	80

Employee Name	Hours worked	Regular Hours	Overtime Hours	Hourly Pay	Base Amount	Over-Time	Total Pay

Selina Geemak	30	30	0	40	1200	0	1200
Russell Creak	34	34	0	80	2720	0	2720
Ricky Mortini	52	30	22	60	1800	1980	3780
Rafael Nooderly	44	30	14	60	1800	1260	3060
Paris Holton	45	30	15	70	2100	1350	3450
Novak Djoker	37	36	1	30	1080	90	1170
Lara Bangle	40	30	10	50	1500	900	2400
Kath Hudson	52	30	22	80	2400	1980	4380
Jennifer Leepoz	36	30	6	80	2400	540	2940
Willard Smith	39	30	9	30	900	810	1710

Total	409	310	99	580	17900	8910	26810

3.b:

Employee Name	Total Pay
Ricky Mortini	3780






Classification Level	Employee Name

Row Labels	Sum of Over-Time
Kath Hudson	1980
Ricky Mortini	1980
Grand Total	3960


Employees at Level 4 and Above:

	Values
Row Labels	Sum of Hourly Pay	Sum of Total Pay
Jennifer Leepoz	80	2940
Kath Hudson	80	4380
Paris Holton	70	3450
Rafael Nooderly	60	3060
Ricky Mortini	60	3780
Russell Creak	80	2720
Grand Total	430	20330


Growth of business intelligence in past decades:
Invention of business intelligence was done in early 1990s and there was evolvement over the past decades. The importance of self service in the concept of business intelligence (BI) has been identified resulting from its dramatic shift. There has been constant rise in revenue generated from the implementation of business intelligence along with the growth of tools of BI. It is expected that there will be further growth in this BI field. BI growth in terms of services offered by the adoption of technologies has resulted in its explosive growth over the years (Simkin et al. 2014).
Adoption of BI tools has been accelerated due to factors such as large amount of data acquisitions and falling costs. Many organizations implement the BI technology in their production and service departments (Tazik and Mohamed 2014). Manufacturing, retain and financial service providers make use of BI tools for functions such as ordering shipment, claim analysis, detection of fraud and targeting of grocery coupons.
It is illustrated from the present statistical data that there is a worldwide generation of revenue of $ 23.1 billion by the implementation of BI tools. BI can be defined as collection of software programs and application technologies that helps in effective and efficient performance of decision makers. Application of BI tools has led to enhancement of business decision making along with increase in demand of such tools globally. BI is a tool that strategically plans the prices of organization. BI is regarded as strategy of applying software that assist in implementing companies’ project plans.

Business tools commonly used and their characteristics:
Tools of business intelligence are software that have been designed to perform the analysis, retracement and reporting of data. Effective management and easy access of data for enterprises of varied sizes are done by using tools of BI. Emergence of BI tool helps in further enhancement of business decisions by providing user friendly interface and improved analysis of data. The two common BI tools are as follows:
Oracle Hyperion system- A centralized planning; forecasting and budgeting solutions are offered by this particular tool that integrates financial and operational planning process. The predictive capability of business is improved by the application of BI. Some of the benefits attributable to this tool involve cost ownership reduction, data integration and enhancing organization’s transparency. It helps in conducting an in depth analysis of key performance and operational indicators (Zhou 2015).
SAP Business Intelligence- The main focus of this tool of BI is to make the analysis and provide assistance in decision making. It is regarded as an efficient tool because it has the capacity of accessing multiple sources of data using single pace and single access point (Prasad and Green 2015). It helps in efficient analysis of data at higher level because of its ability of collection several data and compiling it in the report form. Capability of performing the analysis of multidimensional sources of data is one of the key functionalities of this tool.

References list:
Prasad, A. and Green, P., 2015. Organizational competencies and dynamic accounting information system capability: impact on AIS processes and firm performance. Journal of Information Systems, 29(3), pp.123-149.
Simkin, M.G., Norman, C.S. and Rose, J.M., 2014. Core concepts of accounting information systems. John Wiley & Sons.
Tazik, H. and Mohamed, Z.M., 2014, February. Accounting information system effectiveness, foreign ownership and timeliness of corporate financial report. In 5th Asia-Pacific Business Research Conference (pp. 17-18).
Zhou, Y., 2015. Research on the System for Government Accounting Information Quality Based on Information Transparency. Journal of Accounting and Economics, 3, p.001.

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