Harmonized Data
As you bring data into dataZoa, it is harmonized (or "normalized") so that any series can work with any other. While we preserve all the original series documentation, we load the dates and values into an idealized time series. This automatically handles the specific nuances of time series data, elimination the "data drudgery"; cleaning, aligning, pasting, re-typing and such.
Contents
Date Handling
Frequency/Periodicity
- PERIODICITIES (FREQUENCIES):
- Daily
- Weekly
- Monthly
- Quarterly
- Semiannual
- Annual
- Irregular
Date Range
- EARLIEST DATE:
- Because of the calendar discontinuity introduced at the Gregorian transition, the earliest year that can be stored accurately to the day is 1753.
- Non accurate dates can begin as early as 1/1/1000.
- LATEST DATE:
- 12/31/9999
Gaps
Date Formats
Inputs
Outputs
Data Value Handling
Missing Values Handling
Values can be "missing" for different reasons, with different implications. dataZoa recognizes several different types of missing values and treats them appropriately.
| Non-Numeric Type | Meaning | String to enter as Input | String displayed as Output |
|---|---|---|---|
| No Data | Data point is known not to exist | ##ND## | ND |
| Non-Disclosed Data | Data point exists but is not being shown | ##NDD## | NDD |
| Not Available | Data may exist but is not available | ##NA## | NA |
Calculations
In all calculations, missing data has the highest precedence; e.g. a number plus an NA yields an NA. Specialized functions in the ComputeCloud can be used for specialized handling, such as carry-forward, etc.
Tables
By default, No Data (ND) formats as a blank, while NA, and NDD data are formatted with "NA" and "NDD", respectively. To fine tune these representations, see Displays.
Charts
Missing values are typically shown as gaps.
