This week's material covered the concept of data warehousing and OLAP database design.
Compared to the last two weeks of material, I am finally starting to understand how SQL and databases work on a large scale, in addition to learning more about the technical details of SQL. After reading about data warehousing, I realized that I have always pictured large scale databases as "warehouses" of some sort, even before I knew anything about SQL or database design. I find how data is processed separately in a "warehouse" which is then sliced and diced into cubes, and then finally "served" to users sending multiple queries as a fascinating and efficient way as to how data is moved around the Internet and private servers and databases. In hindsight, some of the simple databases I had to design for a previous Android class could've been much improved if I had known about the concepts of data warehousing -- mobile applications often involve large numbers of users sending multiple queries at the same time, and efficiency is key especially when dealing with the limited power and bandwidth available to mobile devices compared to large server clusters or even powerful PCs.
Learning about OLAP gave me good insight into efficient database design, and how to think about processing data and displaying it to the end user in an efficient and clear manner. Our group has to implement an OLAP database into the second part of our project, and I'm eager to see what we can do in order to return statistics based on our database of performing artists and certain metrics.
Compared to the last two weeks of material, I am finally starting to understand how SQL and databases work on a large scale, in addition to learning more about the technical details of SQL. After reading about data warehousing, I realized that I have always pictured large scale databases as "warehouses" of some sort, even before I knew anything about SQL or database design. I find how data is processed separately in a "warehouse" which is then sliced and diced into cubes, and then finally "served" to users sending multiple queries as a fascinating and efficient way as to how data is moved around the Internet and private servers and databases. In hindsight, some of the simple databases I had to design for a previous Android class could've been much improved if I had known about the concepts of data warehousing -- mobile applications often involve large numbers of users sending multiple queries at the same time, and efficiency is key especially when dealing with the limited power and bandwidth available to mobile devices compared to large server clusters or even powerful PCs.
Learning about OLAP gave me good insight into efficient database design, and how to think about processing data and displaying it to the end user in an efficient and clear manner. Our group has to implement an OLAP database into the second part of our project, and I'm eager to see what we can do in order to return statistics based on our database of performing artists and certain metrics.
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