Business Intelligence Desain And Development – In order to make strategic decisions about products to display in our store, we need to carefully analyze sales and click data. This type of data analysis is one type of business intelligence.
If there is one thing that is abundant in today’s world, it is information. At the core of any information system is a database that stores customer data. For example, who bought what, when, how much, and so on. It is useful to know about the structure of the exchange processes so that it is not a complete mystery how the data is captured.
Business Intelligence Desain And Development
However, it is important to know how to classify and analyze the data captured in order to make management decisions. For example, after summarizing thousands of records we may find a product that sells specifically to women of a certain age and living in a certain area. That meaningful information may be applied in supply chain and marketing efforts.
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If anything in the world today there may be too much information. Sorting that data into meaningful information is an important skill. There are a number of tools available to perform data analysis. These include accounting programs such as Excel and database systems such as Access. Learning to use these tools will improve your marketing.
Many information systems projects are thought of as having a life cycle that goes through stages from analysis to implementation. The diagram below shows the stages we will touch on in the current chapter:
To demonstrate the power of summary data, we will first show how it can be used for website marketing. Amazing stats can help encourage repeat business. The same marketing principles work even for non-profit organizations.
Kiva is a website that allows you to make small loans (usually less than $500) to entrepreneurs in developing countries. The field of small loans is known as microfinance. Making very small loans (usually less than $500) to entrepreneurs in developing countries. Most loans are paid in six months to a year. . Microfinance institutions are a vital resource in helping Third World citizens rise out of poverty. Surprisingly, the repayment rate of the world’s poor is between 95 and 98%, which is much higher than the US debt repayment rate. More than 80% of Kiva’s loans are made to women entrepreneurs. They put profits back into businesses and improve the lives of their families.
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Kiva works by pooling resources so for example 50 people can lend $10 each up to $500. As part of its marketing efforts Kiva has been keeping up to date with quick facts about their activities. For example, they report that they have nearly half a million lenders who have collectively loaned $161 million over the past three years. These fast facts are gathered from web data after scanning millions of records representing business intelligence. Not only does the information serve a marketing purpose, but it is also an internal card to track the progress of Kiva’s mission and the impact of decisions.
The Kiva Facts and History page is a business intelligence report. Note the sentence that appears under “Last Census,” which announces that the census is updated at night (between 1 – 3 am). This is one of the business intelligence systems. Searching for millions of records puts the system in a rush where these tasks are often performed during peak hours.
Example Kiva is a form of business intelligence Delivering accurate, useful data to the appropriate decision makers within the time required to support effective decision making. . Business Intelligence (BI) is the delivery of accurate, useful data to the appropriate decision makers within the required timeframe to support effective decision making.
This definition of all the work we have done in Excel will qualify as a trade secret as our output contains accurate and useful information to support effective decision making. However, business intelligence is commonly understood to include the classification and analysis of large data such as those found in corporate databases. Retrieving and analyzing information stored in databases is the subject of this chapter. It is likely that at many points in your career you will be asked to participate in this type of analysis.
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Business intelligence is part of the big picture information system architecture. Most existing systems can be classified as either business systems, collaborative systems, or business intelligence systems. Business processes – taking orders for example – feed their data into the data warehouse, which is then asked to support business intelligence.
For example, let’s say our goals are to develop a clothing business that produces high quality products while reducing costs. We further decide to measure product quality by the percentage of products rejected by inspectors at each station. (Think of those inspector 99 tags you get in the pockets of your new clothes. The clothes you’re wearing are the ones the inspector has accepted. Is this an overzealous inspector? tend to produce more objections than others?
Let’s say that our analysis determines that the high rejection rate comes from only one factory in Southeast Asia. We report the problem to the authorities. They send a team to review the plant. The review found child labor, abusive situations, and very low morale at the plant. Shocking situations are quickly reversed and rejection rates return to average.
The business intelligence component of the information systems architecture. Note that business intelligence systems typically operate outside of the database – the company’s database. Every business system contains one or more databases. The contents of these databases are regularly copied to the data warehouse to enable BI analysis. The copying process is called extract, transform, and load (ETL).
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Periodic reports are a type of BI reporting that we are very familiar with—summary reports that are distributed at regular intervals. It is by far the most popular form of business intelligence. Most businesses have compiled standard reports that are pre-set and published to assist management in decision-making. For example, universities use enrollment reports to gauge which departments may need to hire more faculty. Credit card companies will request reports of people with high credit scores to target credit card ads. Also, companies can target college students with good future earning potential. Marketers can look at sales figures for different stores and regions to determine where there are opportunities to run sales promotions.
Dynamic reports are similar to regular reports but with one major difference. They are interactive and allow the user to drill down to find out where the summary numbers are coming from. Look at static reports but online and interactive. A manager who is interested in the location of a few specific numbers on his dashboard overviews senior management data—sometimes depicted using dials and needles similar to a car dashboard. In a car you may not need to know your exact RPMs but you do need to know you are red lining. Also, top management may not need to know exact sales numbers but they need to know if sales are out of the norm. it can come from a reduction in the number discovery process that participates in the creation of a finite number. A withdrawal is like checking your ATM balance and then calling the number to get a list of withdrawals from your account. to display the details of that number of contributors. It’s essentially a fact-finding journey where the information found at each step gives you clues about where to look for the next information. For example, if sales in North America are down, then dig to find out if there is a problem in the Midwest region. Then dig deeper to find out what’s going on in Cleveland, Ohio.
Data mining The process of fishing for data patterns using computing power because you don’t really know what to look for. uses computer programs and statistical analysis to look for unexpected patterns, correlations, trends, and clustering of data. In essence, it is fishing through the data to see if there are any interesting patterns. One of the most frequently cited examples of mining was the discovery that beer and diapers are routinely purchased on the same trip to the grocery store. After further investigation the marketers discovered that Dad takes some beer on his trip to the grocery store to buy diapers. Marketers can use this information to place the two items closer together in the store.
The business intelligence process of dynamic reports is shown here. The top part of the diagram shows how data gets into the database system through the extraction, conversion, and loading process. Dynamic reporting starts with an executive dashboard that provides a high-level view of the business. The dashed red arrows represent digging to find the cause of the data pattern. In this example, the decline in sales in North America has been followed ever since
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