Topic 7 is designed to help you understand the value of data and data management tools and how they can be applied. Very little of what we do today as an Information Society would be possible without the massive investment in database tools, techniques, and technologies … most of the knowledge we come across in our daily lives is stored in some sort of a database structure. Please read topic 7 so you can understand that there are different types of databases for different reasons. I have to say, you cannot solve our challenge without a complete understanding of database technologies — you just can’t do it. Pieces of what you learn in this topic will really allow you to solve it.
The topic begins with an overview of the importance of data. Without data, computers are of little value. The worth of a computer or an information system is measured in terms of its ability to support the processing, transmission and/or accessing of data. In fact, data management can be the key to success or failure for an organization. Many companies run into difficulties because they lack the appropriate data to make effective decisions, and/or the way their databases are constructed inhibits the ability to analyze and manipulate data in a timely, cost-effective manner. It goes on to lay out the basic terminology associated with databases … this is a critical bunch of information as it really gives you the basics.
From there, it goes on to discuss the characteristics of databases and on to a very importnat lesson related to database management systems. Make sure you finish out your reading as it gets into some fairly complex stuff … the key here is that databases are the main ingrediant in so much of what you as a knowledge worker will need to know to solve large-scale IT challenges. Don’t miss reading this topic! When you finish your reading, respond to the discussion activity below … and remember, your challenge asks you to decide on a database sytem to power your solution — the information in this topic should be a starting point for you to do just that.
At times, we collect data from our employees, peers, customers, and friends. As knowledge workers, we are expected to sort through data and come up with meaningful information. There are many things that can jeopardize the meaning that we intend to pull from data, especially when data comes from surveys or some type of human-generated information (interviews, reports, journals, or books). The respondents’ truthfulness, the quantity of responses, possible bias, and time constraints can lead us to “stories” that might not be valid. Can you think of some other problems that may occur when trying to extract meaningful data? How do you plan to only extract valid and reliable data so as to create meaningful information?