Business intelligence (BI) frameworks.

Evaluate business intelligence (BI) frameworks. Compile data required to inform business insights. Conduct comparative market and operational performance analyses. Determine business outcomes using predictive analysis techniques. Analyze big data for business decision-making. Identify emerging technologies that impact analytics, business intelligence (BI), and decision support. Student Success Criteria View the grading rubric for this deliverable by selecting the “This item is graded with a rubric” link, which is located in the Details & Information pane. Scenario You have recently been hired as an Emergency Services Analyst for the city of Lincolnton, NC. In this role, you are to analyze all emergency services incident patterns, collect statistics, prepare and disseminate information, and assist with special projects. Recently, you have been tasked with conducting analysis on the emergency services data from 911 related calls from around the city. Part 1: You receive the email from your Director of Emergency Services, including an Excel file of source data, and are asked to analyze the calls from around the community. You will perform your analysis (in the same Excel spreadsheet) and provide an explanation in an email response (Word document). Download the source data file below. Emergency Call Center Data File Within the spreadsheet, perform the following: A. Prepare a dataset from the “Source Data” spreadsheet. Remove any potential errors or outliers, duplicate records, or data that are not necessary. Provide a clean copy of the data in your email response. B. Explain why you removed each column and row from the “Source Data” spreadsheet or why you imputed data in empty fields as you prepared the data for analysis.

Sample Solution

Business intelligence (BI) frameworks are a set of tools and processes that help businesses collect, analyze, and interpret data to make better decisions. There are many different BI frameworks available, each with its own strengths and weaknesses.

When evaluating BI frameworks, it is important to consider the following factors:

The specific needs of the business
The size and complexity of the business
The budget available for BI
The level of technical expertise required

Full Answer Section

Some of the most popular BI frameworks include:

Microsoft Power BI
Tableau
QlikView
SAP BusinessObjects
IBM Cognos
Compiling Data Required to Inform Business Insights

The first step in any BI project is to compile the data that is needed to inform business insights. This data can come from a variety of sources, including:

Operational data
Financial data
Customer data
Social media data
Sensor data

Once the data has been compiled, it needs to be cleaned and prepared for analysis. This may involve removing duplicate records, correcting errors, and standardizing the data format.

Conducting Comparative Market and Operational Performance Analyses

Once the data has been prepared, it can be used to conduct comparative market and operational performance analyses. This involves comparing the business's performance to its competitors and to industry benchmarks.

This type of analysis can help businesses identify areas where they are doing well and areas where they need to improve. It can also help businesses identify new opportunities for growth.

Determining Business Outcomes Using Predictive Analysis Techniques

Predictive analysis is a type of BI that uses data to predict future trends and events. This type of analysis can be used to determine the likely outcome of a particular course of action.

For example, predictive analysis can be used to predict customer churn, identify fraudulent activity, or optimize marketing campaigns.

Analyzing Big Data for Business Decision-Making

Big data is a term used to describe the vast amount of data that is being generated every day. This data can be used to gain insights into customer behavior, identify new market opportunities, and improve operational efficiency.

However, big data can be challenging to analyze. This is because it is often unstructured and noisy.

There are a number of techniques that can be used to analyze big data, including:

Machine learning
Natural language processing
Data mining

These techniques can be used to extract patterns and insights from big data that would not be possible to identify using traditional methods.

Conclusion

BI is a powerful tool that can help businesses make better decisions. By evaluating BI frameworks, compiling the data required to inform business insights, conducting comparative market and operational performance analyses, determining business outcomes using predictive analysis techniques, and analyzing big data for business decision-making, businesses can gain a competitive advantage.

We are here to help

We have crazy offers

It’s quick and easy to place an order. We have an efficient customer service that works 24/7 to assist you.It’s quick and easy to place an order. We have an efficient customer service that works 24/7 to assist you.

We are here and ready to help

Order Now