Considerations Before Integrating Data into Datasets

This section covers expected behavior and limitations to consider before integrating data into datasets.

• Handle Numeric Values
  CRM Analytics internally stores numeric values in datasets as long values. For example, CRM Analytics stores the number 3,200.99 with a scale of 2 as 320099. The user interface converts the stored value back to decimal notation to display the number as 3200.99.
• Handle Date Values
  When CRM Analytics loads dates into a dataset, it breaks up each date into multiple columns, such as day, week, month, quarter, and year, based on the calendar year. For example, if you extract dates from a CreateDate column, CRM Analytics generates columns such as CreateDate_Day and CreateDate_Week. If your fiscal year differs from the calendar year, you can enable CRM Analytics to generate fiscal date columns as well.
• Handle Custom Time Zone Values
  Time zone support lets you view time-specific data on dashboards in a time zone that you specify for your org. By default, CRM Analytics datasets aren’t time-zone aware, so CRM Analytics treats all date-time values as being in GMT. The data you see on your dashboards is in GMT, regardless of your local time zone. When you enable time zone support, CRM Analytics converts date-time values in your datasets to the time zone selected for CRM Analytics. You can then create time zone enabled dashboards to display these converted date-time values. Users see dashboard data in the single custom time zone you set, not their personal timezone specified in Salesforce. Recipe formulas and filters with date-time fields operate in GMT.
• Handle Text Values
  Confirm that text values in a column are uniform in formatting, spelling, and language. Inconsistencies can occur within data sources and after merging data from multiple data sources.
• Handle Missing Values
  Gaps in your data can throw off analysis. Missing values are best fixed in the source application by, for example, making it a required field. However, if you can’t do that, you can use CRM Analytics to fill in missing data.
• Dataset Capacity and Limits
  Before you create any datasets, review the limits. For example, each Salesforce org has a maximum number of rows for all datasets in the org. There are also limits on the number of columns in a dataset and characters in a column.
• Reserved Dataset Field Names
  CRM Analytics data prep doesn’t support using some reserved keywords as field names in lenses and dashboards.
• How CRM Analytics and Salesforce Data Pipelines Work Together
  CRM Analytics and Salesforce Data Pipelines are unique products, but settings, limits, and assets sometimes are shared or interrelated when you use both products. These features are shared when you use CRM Analytics.