essay on business intelligence

What Is Business Intelligence? Essay

Business intelligence (BI) is a process driven by the technology used to analyze collected data, convert the data into information, and put forward detailed knowledge. The process allows managers, executives, and other business leaders to generate effective and accurate company choices or decisions faster or quicker to deliver better outcomes in the required time (Stedman, 2022). There are various uses of business intelligence in business depending on the required process. First, a company such as HelloFresh utilizes digital markets to improve conversions. The centralized business intelligence has significantly saved more than 10 hours of marketing analytics through report-process automation (“Real-world applications of business intelligence”, 2022). Second, the Coca-Cola Company has maximized its operations through automation of the reporting processes and improvement of customer relationships through mobile dashboards that operate in real-time. This has enabled the company to attain a unique competitive advantage. Third, Amazon Company uses analytics to enhance its logistics and supply chain performance.

Some of the benefits of business intelligence include delivering correct data at the required or proper time. The right or correct data is a significant factor that allows organizational leaders to arrive at effective, accurate, and quick decisions in the business environment (Stedman, 2022). Another benefit of BI is that it improves worker and customer satisfaction since the manager is able to analyze their clients’ comments which provides necessary information for their workers to promote quality service for their customers. Quality service allows for better performance of the company (Stedman, 2022). Moreover, BI can lead to increased business productivity as its tools can be utilized in the analysis and selection process, leading to faster progress of these activities compared to manual tasks. Lastly, BI improves since custom reports foster communication, enabling individuals to share their knowledge with other company workers and promoting overall organizational performance.

Stedman, C. (2022). What is business intelligence? BI defined . Search Business Analytics.

Real-world applications of business intelligence . (2022). Tableau. Web.

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106 Business Intelligence Essay Topic Ideas & Examples

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Business intelligence (BI) is a crucial aspect of modern businesses, allowing organizations to gather and analyze data to make informed decisions. Writing an essay on business intelligence can be both challenging and exciting. To help you get started, here are 106 business intelligence essay topic ideas and examples:

• The role of business intelligence in decision-making processes.
• The evolution of business intelligence: From traditional reporting to self-service analytics.
• How business intelligence can enhance organizational performance.
• The impact of business intelligence on strategic planning.
• Business intelligence as a competitive advantage in the digital era.
• The challenges of implementing business intelligence in small businesses.
• The ethical considerations of using business intelligence.
• The role of artificial intelligence and machine learning in business intelligence.
• The future of business intelligence: Trends and predictions.
• The benefits of real-time business intelligence.
• The impact of business intelligence on customer relationship management.
• Business intelligence in supply chain management: Improving efficiency and reducing costs.
• The role of business intelligence in risk management.
• How business intelligence can help organizations identify and exploit new market opportunities.
• The impact of business intelligence on employee productivity and engagement.
• The role of data visualization in business intelligence.
• The challenges of data quality in business intelligence.
• The role of business intelligence in fraud detection and prevention.
• Business intelligence in healthcare: Improving patient outcomes and reducing costs.
• The impact of business intelligence on marketing strategies.
• The role of predictive analytics in business intelligence.
• The use of business intelligence in financial planning and forecasting.
• The impact of business intelligence on mergers and acquisitions.
• Business intelligence in the e-commerce industry: Personalization and customer experience.
• The role of business intelligence in supply chain sustainability.
• The impact of business intelligence on project management.
• Business intelligence in the hospitality industry: Enhancing guest experiences.
• The role of data governance in business intelligence.
• The challenges of data privacy and security in business intelligence.
• The impact of business intelligence on organizational culture.
• Business intelligence in the education sector: Personalized learning and student performance.
• The role of business intelligence in talent acquisition and retention.
• The impact of business intelligence on corporate governance.
• The use of sentiment analysis in social media monitoring for business intelligence.
• Business intelligence in the transportation industry: Improving logistics and supply chain efficiency.
• The role of business intelligence in customer segmentation and targeting.
• The impact of business intelligence on organizational agility.
• Business intelligence in the energy sector: Optimizing resource allocation and reducing waste.
• The role of business intelligence in performance management.
• The impact of business intelligence on sustainability reporting.
• Business intelligence in the retail industry: Enhancing inventory management and demand forecasting.
• The role of cloud computing in business intelligence.
• The challenges of data integration in business intelligence.
• The impact of business intelligence on organizational learning and innovation.
• Business intelligence in the gaming industry: Personalization and player engagement.
• The role of mobile analytics in business intelligence.
• The use of geospatial analytics in location-based business intelligence.
• The impact of business intelligence on customer retention and loyalty.
• Business intelligence in the manufacturing industry: Improving production efficiency and quality control.
• The role of data mining in business intelligence.
• The challenges of data governance in business intelligence.
• The impact of business intelligence on organizational transparency.
• Business intelligence in the tourism industry: Enhancing destination management and marketing.
• The role of natural language processing in text analytics for business intelligence.
• The use of sentiment analysis in customer feedback for business intelligence.
• The impact of business intelligence on organizational resilience.
• Business intelligence in the real estate industry: Market analysis and property valuation.
• The role of data storytelling in business intelligence.
• The challenges of data privacy and ethics in business intelligence.
• Business intelligence in the agriculture sector: Optimizing crop yield and resource management.
• The role of business intelligence in customer journey mapping.
• The impact of business intelligence on supply chain traceability and sustainability.
• Business intelligence in the pharmaceutical industry: Drug discovery and clinical trials.
• The role of data visualization in storytelling for business intelligence.
• The use of social network analysis in relationship mapping for business intelligence.
• The impact of business intelligence on organizational change management.
• Business intelligence in the music industry: Audience analytics and content recommendation.
• The role of sentiment analysis in brand reputation management for business intelligence.
• The challenges of data quality management in business intelligence.
• Business intelligence in the sports industry: Performance analysis and fan engagement.
• The role of blockchain technology in data security for business intelligence.
• The use of location intelligence in market analysis for business intelligence.
• Business intelligence in the fashion industry: Trend forecasting and inventory optimization.
• The role of data governance in ensuring data privacy for business intelligence.
• The challenges of data integration in multi-cloud environments for business intelligence.
• The impact of business intelligence on organizational learning and knowledge management.
• Business intelligence in the food and beverage industry: Demand planning and supply chain optimization.
• The role of sentiment analysis in customer sentiment analysis for business intelligence.
• The use of machine learning algorithms in anomaly detection for business intelligence.
• Business intelligence in the telecommunications industry: Network optimization and customer experience.
• Business intelligence in the environmental sector: Monitoring and conservation efforts.
• The role of natural language processing in sentiment analysis for business intelligence.
• The use of predictive analytics in demand forecasting for business intelligence.
• Business intelligence in the entertainment industry: Audience analytics and content recommendation.
• The role of social network analysis in influencer marketing for business intelligence.
• The challenges of data quality management in big data for business intelligence.
• Business intelligence in the automotive industry: Supply chain optimization and customer personalization.
• Business intelligence in the travel industry: Personalized recommendations and revenue management.

These essay topic ideas and examples cover a wide range of areas within business intelligence. Select a topic that aligns with your interests and expertise, and conduct thorough research to write a compelling essay. Remember to support your arguments with relevant data, examples, and case studies to provide a comprehensive analysis of the chosen topic. Good luck with your business intelligence essay!

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What Is Business Intelligence (BI)? Types, Benefits, and Examples

Yarilet Perez is an experienced multimedia journalist and fact-checker with a Master of Science in Journalism. She has worked in multiple cities covering breaking news, politics, education, and more. Her expertise is in personal finance and investing, and real estate.

Investopedia / Yurle Villegas

What Is Business Intelligence (BI)?

Business intelligence (BI) is a process driven by technology that analyzes business data in order to provide information that can be actioned so that executives and managers can make better-informed business decisions.

Business intelligence is a broad term that encompasses data mining , process analysis, performance benchmarking, and descriptive analytics . BI parses all the data generated by a business and presents easy-to-digest reports, performance measures, and trends that inform management decisions.

Key Takeaways

• Business intelligence represents the technical infrastructure that collects, stores, and analyzes company data.
• Business intelligence parses data and produces reports and information that help managers to make better decisions.
• Software companies produce BI solutions for companies that wish to make better use of their data.
• BI tools and software come in a wide variety of forms such as spreadsheets, reporting/query software, data visualization software, data mining tools, and online analytical processing (OLAP).
• Self-service BI is an approach to analytics that allows individuals without a technical background to access and explore data.

Understanding Business Intelligence (BI)

The need for BI was derived from the concept that managers with inaccurate or incomplete information will tend, on average, to make worse decisions than if they had better information. Creators of financial models recognize this as “garbage in, garbage out.”

BI attempts to solve this problem by analyzing current data that is ideally presented on a dashboard of quick metrics designed to support better decisions.

Most companies can benefit from incorporating BI solutions; managers with inaccurate or incomplete information will tend, on average, to make worse decisions than if they had better information.

To be useful, BI must seek to increase the accuracy, timeliness, and amount of data.

These requirements mean finding more ways to capture information that is not already being recorded, checking the information for errors, and structuring the information in a way that makes broad analysis possible.

In practice, however, companies have data that is unstructured or in diverse formats that do not make for easy collection and analysis. Software firms thus provide business intelligence solutions to optimize the information gleaned from data . These are enterprise-level software applications designed to unify a company’s data and analytics .

Although software solutions continue to evolve and are becoming increasingly sophisticated, data scientists still need to manage the trade-offs between speed and the depth of reporting.

Some of the insights emerging from big data have companies scrambling to capture everything, but data analysts can usually filter out sources to find a selection of data points that can represent the health of a process or business area as a whole. This can reduce the need to capture and reformat everything for analysis, saving analytical time and increasing the reporting speed.

Types of BI Tools and Software

BI tools and software come in a wide variety of forms. Let's take a quick look at some common types of BI solutions.

• Spreadsheets: Spreadsheets like Microsoft Excel and Google Docs are some of the most widely used BI tools.
• Reporting software: Reporting software is used to report, organize, filter, and display data.
• Data visualization software: Data visualization software translates datasets into easy-to-read, visually appealing graphical representations to quickly gain insights.
• Data mining tools: Data mining tools "mine" large amounts of data for patterns using things like artificial intelligence, machine learning, and statistics.
• Online analytical processing (OLAP): OLAP tools allow users to analyze datasets from a wide variety of angles based on different business perspectives.

Benefits of Business Intelligence

There are many reasons why companies adopt BI. Many use it to support functions as diverse as hiring, compliance , production, and marketing. BI is a core business value; it is difficult to find a business area that does not benefit from better information to work with.

Some of the many benefits companies can experience after adopting BI into their business models include faster, more accurate reporting and analysis, improved data quality, better employee satisfaction, reduced costs, increased revenues, and the ability to make better business decisions.

BI was derived to help businesses avoid the problem of "garbage in and garbage out," resulting from inaccurate or insufficient data analysis.

If, for example, you are in charge of production schedules for several beverage factories and sales are showing strong month-over-month growth in a particular region, you can approve extra shifts in near real-time to ensure your factories can meet demand.

Similarly, you can quickly idle down that same production if a cooler-than-normal summer starts impacting sales. This manipulation of production is a limited example of how BI can increase profits and reduce costs when used properly.

Examples of BI

Coca-Cola Bottling had a problem with its daily manual reporting processes: they restricted access to real-time sales and operations data.

However, by replacing the manual process with an automated BI system, the company completely streamlined the process and saved 260 hours a year (or more than six 40-hour work weeks). Now, the company's team can quickly analyze metrics like delivery operations, budget, and profitability with just a few clicks.

What Is Power BI?

Power BI is a business analytics product offered by software giant Microsoft. According to the company, it allows both individuals and businesses to connect to, model, and visualize data using a scalable platform.

What Is Self-Service BI?

Self-service BI is an approach to analytics that allows individuals without a technical background to access and explore data. In other words, it gives people throughout the organization, not just those in the IT department, to have control over the data.

What Are the Disadvantages of Self-Service BI?

Drawbacks to self-service BI include a false sense of security in end-users, high licensing costs, a lack of data granularity, and sometimes too much accessibility.

What Is IBM's BI Product?

One of IBM's main BI products is its Cognos Analytics tool, which the company touts as an all-inclusive, AI-powered BI solution.

Part of the responsibilities of executives and managers is to make their companies more efficient, profitable, and competitive, along with improving the workplace environment for employees. Companies can do this with technology-driven processes, known as business intelligence, allowing them to achieve these goals faster and correctly.

Tableau. " Coca-Cola Bottling Company Empowers the Enterprise with Tableau Mobile Dashboards to Drive Bottom Line ."

Microsoft. " What Is Power BI? "

IBM. " IBM Cognos Analytics with Watson ."

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What is business intelligence?

The following are some business intelligence techniques:, what can business analytics do, why is business intelligence important, companies can use business intelligence to:, how business intelligence works, difference between business intelligence and business analytics, business intelligence tools, difference between traditional and modern business intelligence.

Business intelligence means to utilize data analysis for business operations. The “intelligence” part stems from the fact that effective BI collects and analyzes both internal data and external market factors.

While the best   data analysis   (analytics) developers are indeed math and coding geniuses, you do not have to be a fan of calculus to utilize analytics. In the past, you might have at least a spreadsheet whiz to accumulate and model data in your field, but now there are software tools for nearly every field, depending on what you hope to do. BI doesn’t replace decision-making, it aids your decisions.

Business intelligence is a technical term that refers to the set of data and calculation and analysis functions in the context of business processes. More than indicating a specific "thing", it is an all-encompassing term that concerns the processes and methods for collecting, storing and analyzing data taken from operations or business activities to improve performance. All these elements create an overall picture of the company, helping people make better and more incisive decisions.

• Data mining
• Performance metrics and benchmarking
• Descriptive analysis
• Statistical analysis
• Data visualization
• Data preparation

This term "includes the applications, infrastructure, tools and best practices that enable information to be consulted and analyzed". It was invented in the 1960s in the context of decision support systems; it was further reworked and developed in the 1980s. Business intelligence has emerged as a method to transform data into concrete results, hand in hand with IT models for planning and decision-making processes. Despite having changed over time, it has always played an important role.

One does not have to jump feet-first into BA. You can examine the possibilities and employ the tools and strategies that will first make the greatest impact on your business. For example, if you are looking for hard data regarding the effectiveness of marketing strategies, you would focus your business analytics in marketing.

Analytics can also:

• Create a visualization of data to aid decisions
• Generate insightful historical reporting of past data
• Set up predictive models that allow you to see the likely outcome of desired changes
• Model prescriptively, which can allow for optimization of factors impacting your business

For example, with a model of a business, you can see how small changes in supply, pricing, or marketing might make the greatest impact on revenue, allowing you to concentrate efforts and resources on the most effective solutions.

In simple words, business intelligence shows the data present and passed in the business context to help people make better decisions. Thanks to the performance benchmarking, it makes possible a more efficient and easier company management. It also facilitates the identification of market trends, aimed at increasing sales or revenues. Exploited profitably, it can also be useful in compliance procedures and hiring. With business intelligence, it is possible to optimize any aspect of business management.

The digital revolution has created a massive influx of information, which shows no signs of slowing down. Data is everywhere, it is generated continuously, and it is deeply rooted in the processes of small and large companies. Today everyone expects to be able to access new information and use it for daily decisions, as well as to satisfy their curiosity about new opportunities to be seized.

• Identify areas or ways to increase profits
• Analyze customer behavior
• Compare the data with the competition
• Monitor performance
• Optimize operations
• Predict the success of new initiatives
• Identify market trends
• Identify any problems

The example of a dashboard of economic indicators shows the long-term drivers of the US economy.

Companies have many questions and many goals. To answer these questions and monitor performance against these objectives, they collect the necessary data, analyze it and determine the actions to be taken to grow their business.

For example, Charles Schwab, a financial consulting firm, used businessintelligence to get an overview of all branches in the United States and to evaluate performance metrics and identify areas of opportunity. Having access to a centralized business intelligence platform enabled Schwab to obtain a single view with all branch data. Now branch managers can identify customers who would like to change their investment plan.

In turn, executives can see if the performance of a geographical area is above or below average and see branches with the best results in the same area with a click. All this translates into greater opportunities for improvement and more targeted assistance for customers.

From a technical point of view, the raw data is collected by the company activity, to then be processed and stored in the data warehouses. Users can then access the data and move on to the analysis to answer the questions regarding the company.

Business analytics, or business analysis, is a branch of business intelligence. According to Gartner's glossary of IT terms,   "business analytics includes data mining, predictive analysis, applied analysis, and statistics". In other words, it is part of a company's broader business intelligence strategy.

The business analysis does not have to be a linear process, because the answer to a question will most likely lead to developing new questions and so on. On the contrary, it must be considered as a cyclical process, which includes the phases of data access, identification, exploration, and sharing of information.

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Many self-service business intelligence tools simplify the process of analyzing and understanding the data autonomously even for those who do not have a technical background. Business intelligence is often presented in the form of data visualizations. People are attracted to visual stimuli and immediately notice patterns or color differences. The visualizations illustrate the data in a more accessible and understandable way.

Collected in dashboards, they allow you to tell a story and highlight trends or patterns that would not be easily recognizable with manual analysis of raw data. This accessibility makes possible further reflections on the data, leading to a greater impact on the company.

In the past, business intelligence tools were based on a traditional model. It was a top-down approach in which business intelligence was managed by the IT department and static reports were used to answer most of the analysis questions, if not all.

Therefore, if someone had a further question about the report received, his request was put at the bottom of the reporting queue and the process had to start all over again. As a result, reporting cycles were slow and frustrating and people could not take advantage of current decision data.

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Home — Essay Samples — Business — Business Analysis — The Concept Of Business Intelligence

The Concept of Business Intelligence

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Words: 631 |

Published: May 19, 2020

Words: 631 | Page: 1 | 4 min read

Business Intelligence (BI)

Definition of business intelligence.

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Business Intelligence and Analytics, Essay Example

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In their 2011 study “Business Intelligence and Analytics: From Big Data to Big  Impact” authors Chen, Hsinchun, Roger HL Chiang, and Veda C. Storey,  assess the relationship between business intelligence and management in top industries. Business intelligence and analytics (BI&A) has developed to become one of the most important factors in industries today that can influence the success and growth of a business. The authors published their article in the MIS Quarterly Special Issue on Business Intelligence Research in the hopes of providing managers in industries and researchers in academia updated information on practices in Business Intelligence Analytics and its evolution. The current research in BI&A is assessed for its value and the added opportunities it provides to business managers for expansion. A bibliometric study of six critical BI&A publications, researchers, as well as research topics were taken from over a decade of relevant industry and academic publications. The following will take a deeper look at their study in an attempt to better understand the contribution BI&A research makes to management practices as a whole.

The significant development of Business Intelligence and Analytics is highlighted in the opening parts of the study. The authors note that, “ based on a survey of over 4,000 information technology (IT) professionals from 93 countries and 25 industries, the IBM Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s” (Hsinchun, Chiang, and Storey, 1165). In another survey, on Business Analytics carried out by Bloomberg Businessweek, the study evaluated the state of business analytics, finding that “97 percent of companies with revenues exceeding $100 million were found to use some form of business analytics. A report by the McKinsey Global Institute predicted that by 2018, the United States alone will face a shortage of 140,000 to 190,000 people with deep analytical skills” (Hsinchun, Chiang, and Storey, 1165). The study further found that there would be a decline from 1.5 million data Savvy managers, capable of analyzing big data and using it to make effective management decisions. This means that managers as whole are in decline, specifically those that have the necessary skillset to use data management tools and understand analytics. The reason why this is an important issue is that it allows managers to make more effective informed decisions that drive performance.

The study is keen to point out the advantages of utilizing data management on the internet and in social media. From the early 2000s, the Internet first started to offer specialized analytics and data collection research with search. The authors note that, “the HTTP-based Web 1.0 systems, characterized by Web search engines such as Google and Yahoo and e-commerce businesses such as Amazon and eBay, allow organizations to present their businesses online and interact with their customers directly” (Hsinchun, Chiang, and Storey, 1167). The authors attribute the ability of these companies to interact with their client’s directly to the porting of RDBMS-based business content and product information, in addition to logs of detailed and IP-specific user search. This data is collected through server logs, cookies and interaction logs. The authors refer to this pool of data as a “goldmine of understanding,” because it essentially enables companies to track the data users to a new gold mine for understanding customers’ needs and identifying new business opportunities (Hsinchun, Chiang, and Storey, 1167). In addition to being a valuable tool for customer engagement, business intelligence analytics serves a significant need within small and large businesses who seek to efficiently manage employee operations. The data retrieved through web analytics have a wide range of practical applications within management. The authors point to networks that are established specifically for the purpose of communicating with staff, as well as networks that are embedded into the infrastructure of company operations, such as systems that assist with logistics, manufacturing or distribution. The internet as a whole has also expanded the reach of businesses to enable them to advertise and sell internationally, in ways never before utilized by small and medium enterprises. Most importantly, web analytics has made managing advertisement campaigns more affordable. Through the analysis of click stream data, utilizing tools like Google Analytics, companies are now able to know distinct interests of their consumers, and tailor products to exact consumer needs.

The article addresses the history of Big Data to Big Impact noting that there have been several global trends that have emerged out of BI&A practices. One key development is extremely fast IT connections that have increased the acquisition of big data providing managers with extensive more material to make sound business decisions. This expansion happened from the 1970’s to the present. The authors attribute this development to “the development and deployment of business-related data standards, electronic data interchange (EDI) formats, and business databases and information systems have greatly facilitated business data creation and utilization” (Hsinchun, Chiang, and Storey, 1168). The study notes that BI&A has resulted in improvements in security and public safety, while at the same time introducing new risks. They credit the September 11 th , 2001 terrorist attacks to the urgent need to expand data acquisition and management in the public sector. From the development of this technology, the market has expanded to allow for five main forms of analytics. These tools include,” (big) data analytics, text analytics, web analytics, network analytics, and mobile analytics—all of which can contribute to BI&A 1.0, 2.0, and 3.0” (Hsinchun, Chiang, and Storey, 1168). The authors define data analytics, specifically as Business information technology that focuses mainly on statistical analysis and data mining. They also reference text analytics which falls into the management and tracking of company communications, such as e-mail, social media, and computational linguistics. Web Analytics research is also referenced and the author place a major importance on the role it plays in cloud computing. Network analytics is mentioned, as it plays a key role in monitoring and tracking the effectiveness of network on which major infrastructural systems in corporations rely. This is especially true of hospitals which rely on networks to store medical records, but also to maintain efficiency within operations. Managers that can effectively structure and run networks are in high demand in the medical field for this exact reason. The final type of analytics mentioned in the study is mobile analytics. The authors point out that this is a growing aspect of both networking and e-commerce, as more people are making transactions with mobile devices, or engaging with brands through their smart phones and tablets. It is essential that managers are knowledgeable in all fields of analytics and data acquisition and management because through doing so they can develop sound strategies towards gaining a competitive edge in their markets. These tools are also ideal for managing large teams as well as corporations as a whole.

In sum, the reason why business intelligence and analytics and the study of the field contributes significantly to management practices as a whole is because they allow managers to make more informed decisions. As the technology continues to develop, a wide range of opportunities will emerge. Currently, Business Intelligence and analytics serves as one of the key fundamental aspects of knowledge acquisition for the formation of corporate strategy, but the technology also serves as a tool for project management, communications, and a supplement for key company operations. For example, there are many companies like Amazon, and other web based merchants, that handle their logistic with the help of cloud computing technology. Companies also manage their scheduling, training, hiring and salary distribution primarily online. It is standard practice to have a working database through which employees as well as customers interact with a particular company. This article sheds a perfect light on some of the most relevant development within business intelligence management. One of the most valuable details mentioned in the article is the increasing need for managers who know how to analyze and implement big data. The report showed that by 2018 there will be a decline of 1.5 million managers in the U.S. capable of utilizing these data acquisition and analysis tools due to increased complexity within the field. One of the most critical aspects of business is the dissemination of information, and this article demonstrates that the process in business is virtually all online.

Chen, Hsinchun, Roger HL Chiang, and Veda C. Storey. “Business Intelligence and Analytics: From Big Data to Big Impact.” MIS quarterly 36.4 (2012): 1165-1188.

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Essay On Business Intelligence

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Topic: Business , Internet , Disabilities , Company , Employee , Innovation , Intelligence , Information

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Business Intelligence (BI) is the way in which data can be stored and later used as business information. BI includes technologies, applications and means for collection, integration, analysis and presentation of business data. It is used for delivery of appropriate data at proper time and in a precise arrangement. BI offers user friendly information to users who can work, team and resolve on contentious issues. Business Intelligence has several advantages; BI has made decision making a lot easier by allowing leaders access to opinions at any given point of time and place. Latest information is accessed via the desktop or over the internet. Business Intelligence has enhanced managerial efficiency by making data sharing among employees, clients and associates easily accessible. This data is shared over an improved, secured and administered web ambiance. The managers have a centralized site to conduct their supervision. An organization that employs BI has its premeditated planning simpler where familiar equipments are used. Supervision of the work is easier and makes expansion of an entire firm more lucrative. Business Intelligence increases employees’ insight through fully integrated Business Intelligence by making use of well known and accessible tools. When data is easily obtained and interaction of people is free, investigation and assessment of information is achieved and hence knowledgeable business plans can be implemented. Finally, training requirements of a firm are reduced by using business tools that are common, extensively backed and easily accessible. BI enables people to interconnect with information they choose to.

On the other hand, Business Intelligence has its disadvantages in the firms that use it. These disadvantages include;

BI leads to piling of Historical Data about a firm’s deals which is the revealed in a way that permits professionals indecision making. This information however is in small portions that the firm actually needs to work with. The user may also not need the historical data as the market is in frequent allocation. Business intelligence can also appear to be expensive in the low as well middle enterprises as they only have basic transactions. Another disadvantage of BI is that it can be quit complex in data implementation making it so intricate for any business technique. This has been predicted by business experts to throttle any business. There is a limited use of BI as like any other technology, it was first established in the affluent firms and the low and middle enterprises do not consider it to be highly essential due to its complexity. BI is not affordable for many companies. Business Intelligence takes around 18months for data warehousing to completely implement the system and many firms in the fast paced industrial scenarios are not patient enough to wait for its execution.

Finally on BI diasadvantages, Commercial settings can turn out to be muddled where business intelligence has been used.

In conclusion, firms should not employ the use of BI for data storage for the sake of it because it does not result in its worth but in vice versa effects. Firms should therefore give due thought to the BI before its implementation.

Business MapsofIndia. Web November 2012 Association of Modern Technologies professional, 2012. Web November 2012 www.itinfo.am/eng/business-intelligence/ BI for software manufacturers: build vs. buy, 2008. Web November 2012

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D'Amore-McKim School of Business

Business analytics.

Our STEM-designated MS in Business Analytics will not only teach you to analyze data efficiently but, more importantly, will also teach how to leverage data to make effective strategic business decisions confidently. You'll learn from business school faculty who are thought leaders in their fields and build the skills needed for long-term business success.

Data is essential in today’s business world—but it only has true meaning in context. More and more companies are seeking the right professionals who can capture, analyze, and translate the right data. That’s why the experience-driven approach to our program is so valuable.

The Online Master of Science in Business Analytics program at the D’Amore-McKim School of Business focuses on the ever-changing and dynamic tech economy. Our programs support skilled leaders using new technologies and data analytics to inform their decision-making. You'll tackle a rigorous curriculum and learn from expert faculty and business trailblazers. Through in-class case studies, your professors will share real company data as you explore questions such as how to build sales, enhance marketing, or strengthen a company’s infrastructure.

You'll gain exposure to data mining, statistical and quantitative analysis, multivariate testing, and predictive modeling.

Designed to meet the needs of working professionals, this 100% online program includes experience-powered learning opportunities—allowing you to take the knowledge and insights you gain in the classroom and easily apply them the next day in the workplace.

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After successfully completing your MS in Business Analytics, you can apply your credits earned toward an eligible MBA at Northeastern. As a Northeastern alum, you’ll qualify for the Double Husky Scholarship and receive a 25% reduction in your tuition for your remaining MBA courses.

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D’Amore-McKim’s MS in Business Analytics program prepares you to interpret and apply data and make data-driven decisions in an increasingly competitive and technology-driven business environment.

• Core courses will introduce you to data mining, statistical and quantitative analysis, multivariate testing, and predictive modeling.
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By enrolling in Northeastern, you gain access to a network of more than 275,000 alumni and 3,350+ employer partners, including Fortune 500 companies, government agencies, and global nongovernmental organizations. Our current students and faculty across strategically located regional locations further foster a lifelong, global community of learning and mentoring.

Depending on your background, the MS in Business Analytics program will help you prepare to differentiate yourself and take on roles in the fields of financial services, transportation and logistics, retail, and more.

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Business Intelligence Model

Business intelligence can be viewed as those activities that an organization can use to gather market information as well as the activities in which their competitors are involved in. Business intelligence can also refer to those technical computers based procedures which are applied in the identification, extraction as well as examination of the business data.

Some of the business data that are usually analyzed in business operations include revenue on sales based on either departments, or the product in question. It may also include data related with incomes or costs. In the contemporary business world, the need for business intelligence has significantly increased. This is more so based on the fact that the level of competition has significantly increased. In order to succeed in such an environment, there is need for every organization to have effective business intelligence practices.

One of the models in business intelligence is associated with the supply chain. This is of great importance in development of SCI solution especially in the big companies. The main objective of this method is coming up with a typical SCI remedy that will provide collaborative as well as the global analysis.

International companies have significantly benefited from the business intelligence in its supply chain. It has played a significant role in improving their integrated supply chains. This entails a number of aspects in the supply chain including the reasons for certain deviations and their causes among others. This has also helped companies in understanding other information on sales like the time to fill the orders, inventory days of supply, order backlog among others (Williams & Williams 2007).

As an organization conducts its supply chain processes, it generates a wide range of data which can be of great significance in business intelligence. Through automation, an organization is able to generate useful raw data on delivery, return, planning and other processes. However, the organization is faced with a big challenge on determining the best method in making appropriate decisions. After collection of the raw data, then an organization uses various metrics and key performance indicators (Glatthorn & Joyner 2005).

In the supply chain intelligence model, the Supply Chain Operations Reference-model or SCOR plays a pivotal role as it provides necessary information in the management of the supply chain process (Ranjan 2009). This method has been for long been useful in providing appropriate information in making necessary decisions in the supply chain.

The SCOR model helps in building the relations between the manufacturer and the consumer, manufacturer to the supplier, as well as the suppliers and suppliers. It also helps in understanding the relations between the customer and the manufacturer as well as customers’ customers. This information is of great importance in making important decisions in an organization’s supply chain.

As already noted, business intelligence has a number of benefits to an organization. One of the main advantages of the business intelligence is that it contributes to improving an organization’s competitive advantage. This makes an organization better off compared with its competitors. This aspect enables organization to survive in highly competitive environment.

Business intelligence also helps an organization in making well informed business decisions (Glatthorn & Joyner 2005). This is the main factor that helps in building an organization’s competitive advantage. For instance, an organization may use business intelligence to identify the parts of the market where there is a shortage of a certain product. This information will help an organization in making supply decisions. For instance, this may involve increasing the volume of certain product supplied in such areas. This will enable an organization to increase its sales. Business intelligence also enables an organization to make perfect forecasts about the future.

Effective business intelligence practices helps the managers and decision makers to come up with the most competitive business strategies. This is based on the accuracy and well timed information. This implies that an organization is able to make the right decisions and in the right time. This helps in increasing the organization’s performance.

Through business intelligence, an organization is able to identify the kinds of products or services that customers are most likely to purchase (Williams & Williams 2007). The line managers will also be able to identify the time in which customers are most likely to purchase a certain product. This plays an important role in making distribution and manufacturing decisions. Business intelligence will also help an organization to identify the reasons that may cause their customers to shift to their competitors’ products (Ranjan 2009). Again, this information is of great importance as it guides the managers in making necessary decisions.

In conclusion, this discussion has clearly shown that business intelligence has a pivotal role in every organization. Through business intelligence, an organization is able to reveal the place of an organization in relation to its competitors, potential of the firm, customer behaviour in spending and the dangers associated with such behaviour to the organization and the political environment that affects an organization’s operations. This helps an organization in making the most effective operations decisions, which significantly determines the performance of an organization. It is therefore advisable for any organization to ensure that it applies business intelligence effectively in order to maintain a high level of performance.

Reference List

Glatthorn, A. A. and Joyner, R.L. (2005). Writing the Winning Thesis or Dissertation: A Step-by-Step Guide. 2 nd Edition . Thousand Oaks, CA: Corwin Press.

Ranjan, J. (2009). Business Intelligence: Concepts, Components, Techniques and Benefits. Journal of Theoretical and Applied Information Technology, 2005. pp. 60-70.

Williams, N. and Williams. (2007). The Profit Impact of Business Intelligence . San Francisco: Morgan Kaufmann Publishers.

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