Management Information Systems: Data and Databases

Management Information Systems: Data and Databases


The chapters assigned for this module cover data and databases. Businesses of all sizes face issues with data. Whether it’s tracking customer transactions, inventory or maintaining information mandated by the government, the amount of data that companies must deal with is massive and can create problems. Managing all this data can be a problem. Here are some specific difficulties that companies face when managing their data, First the amount of data that companies have to deal with a increases exponentially over time. The number of customers that a organization has, the amount of sales and orders that those particular customers have increase over time. Companies may also have data scattered throughout the organization. The marketing department may have data they’re maintaining. The production department may have other data and so. It’s a challenge to put all that data together. There are also new sources of data being developed. Then there is big data which we’ll discuss in this chapter. Data also degrades over time. People move and change their address. Companies go out of business. So data must be maintained accurately overtime. These are just some of the difficulties that organizations face with data. Even though we haven’t gotten too far in this class you’ve probably guessed that information systems are going to be able to help customers manage data. One very useful tool the company can use is a database management system. A database management system is a program that is used to create and administer a database. Some examples include Oracle, Microsoft SQL server, MYSQL and Microsoft Access. A database management system is not a database, it manages databases. It allows us to create databases and we’ll explain that a little bit more as we continue. Here are some definitions. First is database. A database is an organized collection of data. In theory it would not have to rely on a computer. A rolodex file or phone book could be considered a database. For our purposes a database is going to consist of tables relationships and meta data. We’ll explain those terms later. Here are some of those definitions. The best way to define these terms is to look at a database hierarchy We’ll start small and work our way into the larger aspect of a database. The first element of a database is a field. A field is simply a piece of information such as last name or first name. Those are fields. Now, if you put all the fields pertaining to one particular person, such as an employee or a student, all those fields together once they are filled in become a record. Within a database a table is going to be a collection of Records. For instance i might have a table called employees in the table called employees I would expect to find all my employee records. I wouldn’t expect to find a customer in the table called employees. A database is a collection of tables and the relationships among the tables and metadata. We’ll define relationships and metadata in the next few slides. Here is a visual explanation of the field. In this image we see an Access database form You can see blanks in this form. There is a blank for firstname, lastname, and student ID. Each of these blanks represents a field within the database. We defined a record as a collection of related fields. They’re all related to the same entity, whatever you’re tracking. Here is an image of a John Doe’s record. We have his name and his address. All the fields that were storing about John Doe become John Doe’s record. A table holds records, so using the example from the previous slide, all the students in this database will be stored in a student’s table. Here we see an example of the attendance table. We have information about attendance records and all of the records in this table have the same fields. A table stores records. In our discussion of the database hierarchy we did find a database is a collection of tables and here we see a list of all the tables that are in the students database we’ve been looking at. So here we have tables for filters, Guardians, settings, student attendance, and students. Another term that we threw out previously was metadata. Metadata is data that describes the data in the database. That seems a little bit confusing. Metadata simply says we have a first name field, we have a last name field and we have an address. Metadata is the descriptions of fields telling us what might go into a particular field. It’s not the data itself. It is simply the names and descriptions of the fields within the database. Here we see visual representation of meta data. We don’t see the actual first names that were storing, we just see the field names: first name last name and so on. we also have the data type which is what kind of information is stored in each of those fields. The description lets us know what that field called first name actually stores. You may recall we defined a database as a collection of tables, metadata and relationships. Here you see a visual description of a database relationships. In a relational database management system the database contains relationships. Relationships are links between the tables that are related in some way. In this example you can see a link between the student table and the student attendance table. You can also see that there is a link between the students table and the Guardians table. One of the questions you might be asking yourself right now is what’s the big deal about database relationships>Why do we want them? There are several reasons why we want to create relationships within our database. First separating information into a separate table minimizes redundancy. With the previous slide as an example, let’s assume that instead of having a separate Guardians table we created fields within the student table for guardian information. That would work fine for only one student, but if for instance a parent or guardian had more than one student at the school we would end up having to type in the gaurdian’s complete information for every student associated with that parent. By creating a separate Guardians table we would only have to enter that parent’s information once. Then you simply type the Guardians ID into the student record and that would create a link between the individual student and the parent. We enter the parent information only once not every time for each child they might have in the school. Eliminating redundancy also improves database accuracy. If we had one parent’s information entered separately into five different student records, we might not get all of those updated if their address or phone number changed. By relating tables we could change the parent information once in the Guardians table and because we’ve only included a link to that table in the students table that information would be automatically accurate for all children. If we were to make any changes in the one time that the parent information would be accurate in the parents table. A database application is different than a database. A database application is a database that has a user interface built into it. For example an application would include forms and would often also include buttons that a user could click on, or a a link a user click to click on to get to a different form or use a specific report. Using only a database would require that the user would create a new form or a new report every time he or she wanted to see specific information in the database. A database application makes a database “user friendly”. If for instance you use blackboard, QuickBooks or even YouTube you’re really using a database application. In the world of business, especially when you’re dealing with information systems, big data is also something you should be familiar with. Big data, as a term implies, includes massive amounts of data and as this chart on the slide shows, big data might include information from your own organization. It could include data from other sources like government data, or transactions on facebook Information such as what’s trending today, what are people searching for on google, or all amazon transactions. All of that would be examples of big data. Big data is so large, so massive, that it cannot be managed by traditional database management systems. Big data might be structured like a list of transactions and orders placed in amazon, but it could also be unstructured like Facebook posts or tweets or even Google searches. Big data is used to predict patterns or trends and it’s very useful in marketing or other types of research.

Danny Hutson

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