For our example, the dataset that we are going to use here is the daily Google (GOOG) Quotes price dataset over a 6 month period from July 1, 2014 to December 31, 2014. This is a good dataset to understand how we can quickly analyze simple datasets, such as these, with ELK.
The most significant fields of this dataset are Date, Open Price, Close Price, High Price, Volume, and Adjusted Price.
The following table shows some of the sample data from the dataset. The actual dataset is in the CSV format.
|
Date |
Open |
High |
Low |
Close |
Volume |
Adj Close |
|---|---|---|---|---|---|---|
|
Dec 31, 2014 |
531.25 |
532.60 |
525.80 |
526.40 |
1,368,200 |
526.40 |
|
Dec 30, 2014 |
528.09 |
531.15 |
527.13 |
530.42 |
876,300 |
530.42 |
|
Dec 29, 2014 |
532.19 |
535.48 |
530.01 |
530.33 |
2,278,500 |
530.33 |
|
Dec 26, 2014 |
528.77 |
534.25 |
527.31 |
534.03 |
1,036,000 |
534.03 |
|
Dec 24, 2014 |
530.51 |
531.76 |
527.02 |
528.77 ... |