How can data arise




















A single fact is an element of data, or a data element. If data are information and information is what we are in the business of working with, you can start to see where you might be storing it. Data can be stored in:. All of these items store information, and so too does a database. Because of the mechanical nature of databases, they have terrific power to manage and process the information they hold.

This can make the information they house much more useful for your work. With this understanding of data, we can start to see how a tool with the capacity to store a collection of data and organize it, conduct a rapid search, retrieve and process, might make a difference to how we can use data.

This book and the chapters that follow are all about managing information. Discuss the disadvantages of file-based systems. Explain the difference between data and information. Use Figure 1.

In the table, how many records does the file contain? How many fields are there per record? What problem would you encounter if you wanted to produce a listing by city? How would you solve this problem by altering the file structure? Figure 1. Table for exercise 5, by A. Skip to content Main Body. Discuss each of the following terms: data field record file What is data redundancy? Previous: Acknowledgements. There is a side to the overall intervention-decision-process that does not attract as much analytical attention: the issue of optimizing which intervention works best — i.

The key reason that this side of things is not often implemented is simple — lack of data. One would have to try different interventions on different populations and record the results of those different intervention strategies over a potentially long period of time.

Usually, different intervention strategies would have to be implemented on mutually exclusive groups of people. Companies do not want to invest several years of paying for different interventions, knowing that many or most may not be sufficiently profitable. The data were not available at most companies and the prospect of collecting such data for many years was viewed as too daunting.

However, nowadays, nearly all large- and mid-sized companies have sufficient data to develop a CLV model. One might make the case that when it comes to data for intervention decisions, short-sightedness is alive and well. However, advances in machine learning may help change this perspective when it comes to selecting an optimal intervention.

There are many marketing and business problems where customers take undesirable actions that can negatively impact organizations and providers. Fortunately, marketers can effectively disrupt these actions with an intervention.

Optimizing, at least for a given intervention, is now being recognized as a useful implementation in many situations. You have 1 free article s left this month. You are reading your last free article for this month. Insertion Anomalies happen when inserting vital data into the database is not possible because other data is not already there. For example, if a system is designed to require that a customer be on file before a sale can be made to that customer, but you cannot add a customer until they have bought something, then you have an insert anomaly.

It is the classic "catch" situation. Deletion Anomalies happen when the deletion of unwanted information causes desired information to be deleted as well.

For example, if a single database record contains information about a particular product along with information about a salesperson for the company and the salesperson quits, then information about the product is deleted along with salesperson information. Database Management Explore. Wiki Content.

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