T11L01-Analyzing Data in Access.pptx

T11L01-Analyzing Data in Access.pptx - Analyzing Large Data...

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Analyzing Large Data | Lesson 1 - Analyzing Data in Access CS1100 Analyzing Large Data Topic 11 Lesson 1 - Analyzing Data in Access
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Analyzing Large Data | Lesson 1 - Analyzing Data in Access CS1100 Large Data Sets Excel has some inherent limitations: 1,048,576 rows by 16,384 columns Pivot tables can analyze more data in the 64-bit version (up to the size of virtual memory), but raw data is limited to the above row and column restriction Loading of large files close to the limitation is very slow Managing and manipulating large numbers of rows is cumbersome 2
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Analyzing Large Data | Lesson 1 - Analyzing Data in Access CS1100 Example: Loading a Large Data Set The Excel file "Bird Strikes" contains information about bird strikes of aircraft. Load the file and answer these questions: What's the total number of rows? How many bird strikes did each airline experience? On which day were the most bird strikes? How many bird strikes happened to helicopters? Which airlines had the most bird strikes? How many bird strikes occurred during "Approach"? These questions are difficult to answer in Excel, although Pivot Tables can be helpful. 3
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Analyzing Large Data | Lesson 1 - Analyzing Data in Access CS1100 A Better Approach: Databases Large data sets are better stored in databases and then filtered and exported to Excel for numerical and statistical analysis. Other types of queries are better answered in the database through the database's query mechanism. Microsoft Access is an example of a database similar to many other relational database management systems.
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  • Spring '15
  • VieraProulx
  • Relational model, types of queries

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