How to use Zoho Analytics for Zoho DataPrep?

Zoho Analytics connector for Zoho DataPrep




DataPrep supports importing data from Zoho Analytics using the Zoho Analytics connector. Zoho Analytics is a self-service BI and data analytics software that lets you visually analyze your data, create stunning data visualizations and discover hidden insights from your data. With this connector, you can streamline your ETL workflows, enable smooth data movement, and simplify data integration between Zoho Analytics and Zoho DataPrep.

To import data from Zoho Analytics

1. Open an existing pipeline or create a pipeline from the Home Page, Pipelines tab or Workspaces tab and click the Add data option.

InfoInfo: You can also click the Import data  icon at the top of the pipeline builder to bring data from multiple sources into the pipeline.


2. Choose the Zoho Apps category from the left pane and click Zoho Analytics. You can also directly search the option in the search box.  


3. Choose your organization from the Choose organization dropdown and select one of the available workspaces from the Choose workspace  dropdown.

4. Choose tables to import into DataPrep by selecting the check boxes. All the tables including query tables which are present in the workspace will be displayed by default. You can filter tables and query tables using the filter  menu besides the search icon. 

Notes Query table is a feature in Zoho Analytics that enables you to prepare data for easy reporting and analysis. You can combine data from one or more tables in a database to facilitate easy reporting. Click here to know more about Query tables.



5. Click the Import button. 

6. Once you have completed importing data, Pipeline builder page will open from where you can start applying transforms to the ETL pipeline. You can also right-click the stage and choose the Prepare data option to prepare your data in the DataPrep Studio page. Click here to know more about the transforms.



7. Once you are done creating your data flow and applying necessary transforms in your stages, you can right-click a stage and add a destination to complete your data flow.


NotesNote:  After adding a destination to the pipeline, you can try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline and data movement. Learn about the different types of runs here.

Schedule   

 You can schedule your pipeline using the Schedule option. You can also import incremental data from your Creator application while scheduling. Incremental data import is a method used to import new or modified records after the previous sync.

Schedule configuration

1. Select the Schedule option in the pipeline builder.

2. Select a Repeat method (hourly, daily, weekly, monthly) and set frequency using Perform every dropdown. The options of the Perform every dropdown change with the Repeat method. Click here to know more.




3. Select the GMT at which you want to import new data found in the source. By default, your local time zone will be selected.


4. Pause schedule after: This option allows you to choose to pause the schedule after n number of failures.
InfoInfo: The range can be between 2-100. The default value is 2.


Import configuration for Zoho Analytics

 For any type of run, the import configuration needs to be mandatorily setup for all the sources in the pipeline. You can configure how to import and fetch incremental data from Zoho Analytics using the Import configuration option. 
Note: Without setting up the import configuration, any type of run cannot be saved. 

1. Select the run you want to execute from the Schedule dropdown in the pipeline builder and select the Click here link to set the import configuration. 



2. Select the required option from the How to import data from source? drop down. You can choose to import all data, modified and new data, or only new data using this option.

Import all data

This option will import all available data from the source for every run.



Incremental data fetch

Incremental data import is a method used to import new or modified records in a specific data interval.

Only modified and new data

To import the modified and new data incrementally in the specified data interval, select Only modified and new data option from the drop-down. Enter the date-time column name using which the new or modified data is fetched incrementally. In Zoho Analytics, the date-time column is always shown in GMT.

Info
When importing a Date-Time column with a time zone into Zoho Analytics, the time will be adjusted to GMT+00:00.
For example: Nov 24, 2014 10:00 GMT+9:00  (or)  Nov 24, 2014 10:00 JST will be saved as Nov 24, 2014 01:00 GMT.

If no time zone is provided, the value is treated as GMT by default.




What to do when there’s no data?

During incremental import, click the Advanced link to choose what happens when the source has no new data.


  • Fail pipeline run: The import fails and no data is imported. The pipeline job is marked as failed. This is the default option.
  • Skip pipeline run: The import doesn’t run and the pipeline job is marked as skipped. Notifications aren’t sent for skipped jobs.
  • Ignore and proceed: The pipeline runs with empty data from this source.
  • Use previous data: The data fetched in the previous import is imported again.


Do not import data

The data is imported only once. The second time, the rules gets applied on the same data and gets exported.



10. Click Save to save the import configuration.

To export data to Zoho Analytics

1. Open an existing pipeline or create a pipeline from the Home Page, Pipelines tab or Workspaces tab. You can bring your data from 50+sources.

2. On the Pipeline Builder page, once you have completed creating your data flow and applying the necessary transforms in your stages, you can right-click a stage and select the Add Destination option.



3. You can search for Zoho Analytics under the All destinations tab or filter it using the Zoho Apps category, and click on it.




4. Choose the Organization and Workspace in Zoho Analytics to which you want to export your data. 

5. If you want to create a new table select the New table option. You can choose the required Organization, Workspace and click Export. 
Note: For schedule and backfill run, the first export will be done to a new table and the same table will be treated as an existing table for the subsequent exports and your data will be exported when the target match passes. You can view the target match errors once you run the pipeline or you can directly open the stage from the Pipeline builder page.



6. Choose Existing table if you want to export data to an existing table. Select one from the list of tables available in Zoho Analytics.
Note: Exporting data to system tables is not supported.



7. Choose one of the below options to determine how to handle the data being exported to Zoho Analytics:
  1. Add rows at the end - Using this option, you can add only the newly imported records at the end of your data in Zoho Analytics.
  1. Delete existing rows and add  - This option will delete the existing records in your table and add records newly.
  1. Add rows and replace if  already exists  - Using this option, you can update the records that match the selected column and insert those records that do not match the selected column.



Note: You can select a column to match existing records only when you choose the Add rows and replace rows if already exists option.

8. You can choose to include columns containing personal data by selecting the Include columns with personal data check box.
 
9. Save the destination configuration.

Check target matching before executing pipeline

Navigate to the DataPrep Studio page of the stage where Zoho Analytics is set as the destination.



Click the target matching icon  at the top right corner and choose the Show target option. Make sure the target matching is done to avoid export failure. Click here to know more about target matching.


Now, after checking the target matching, you may want to try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here.
Info: Each run is saved as a job. When a pipeline run is executed, the data fetched from your data sources will be prepared using the series of transforms you have applied in each of the stages, and then data will be exported to your destination. This complete process is captured in the Jobs page.
Note:
1. The rows whose values match their respective data types will be exported.
2. Rows with data type mismatch are not exported and error details will be notified through mail and in the notification panel. 
3. Pipelines containing invalid data cannot be exported to Zoho Analytics. Please ensure the stages configured with Zoho Analytics as the destination contain valid values before scheduling.

10. If the manual run succeeds without any errors, your data will be exported successfully. If the manual run fails throwing the below target match error, you can fix them by completing the target matching steps. 

Target matching is a useful feature in DataPrep that prevents export failures caused due to errors from the data model mismatch.
 



Target matching during export to Zoho Analytics

Target matching happens before the data is exported to the destination. Target matching is a useful feature in DataPrep that prevents export failures caused due to errors from the data model mismatch. Using target matching, you can set the required table in Zoho Analytics as the target and align the source dataset columns to match with your target table. This ensures seamless export of high quality data to Zoho Analytics.
Note: Target matching failure is not an export failure. Target matching happens before the data is actually exported to the destination. This way the schema or data model errors that could cause export to fail are caught beforehand preventing export failures. 

When target match check fails

1. If the target match check fails during export, you can go to the DataPrep Studio page, click the target matching icon  at the top right corner and choose the Show target option. The target's data model is displayed above the existing source dataset. The columns in the source dataset are automatically aligned to match the columns in the target dataset, if found.



Target matching displays the different icons and suggestions on the matched and unmatched columns. You can click on these suggestions to quickly make changes to match the existing column with the target column. To make it easier for you to fix the errors, the target module in your Zoho Analytics is attached as a target to your data. You can view the mapping of your data with the table in the DataPrep Studio page along with the errors wherever there is a mismatch. You can hover over the error icons to understand the issue and click on them to resolve each error.
Note: All columns are displayed in the grid by default. However, you can filter out the required option by clicking the All columns link.
2. Click the View summary link to view the summary of the target match errors. The summary shows the different model match errors and the number of columns associated with each error. You can click on the required error columns and click Apply to filter out specific error columns. 



Target match error summary

  1. The Target match errors section shows the errors and the number of columns associated with each error. 
  2. The section at the top lists the error categories along with the number of errors in each category.
  3. You can click them to filter errors related to each category in the panel.
  4. In the default view, all columns are displayed. However, you can click any error category and get a closer look at the columns or view the error columns alone by selecting the Show only errors checkbox. 
  5. Your filter selection in the Target match error summary will also be applied on the grid in the DataPrep Studio page. 

Target matching errors

The errors in target matching are explained below:
  1. Unmatched columns : This option shows all the unmatched columns in the source and target.
    Note:
    1. The non-mandatory columns in the target can either be matched with a source column if available or ignored.
    2. The columns in the source that are missing in the target need to be matched or removed to proceed exporting. 
    When using the unmatched columns option, you can toggle the Show only mandatory columns option to see if there are any mandatory columns(set as mandatory in the target) and include them. You can also fix only the mandatory columns and proceed to exporting.


  1. Data type mismatch : This option displays the columns from the source having data types that do not match the columns in the target.
  2. Data format mismatch : This option displays columns from the source having date, datetime and time formats that differ from those in the target.
  3. Constraint mismatch : This option displays the columns that do not match the data type constraints of the columns in the target. To know how to add constraints for a column, click here.
  4. Mandatory column mismatch: This option displays the columns that are set as mandatory in the target but not set as mandatory in your source.

    Note: The mandatory columns cannot be exported to the destination unless they are matched and set as mandatory. You can click the  icon above the column to set it as mandatory. You can also use the Set as mandatory (not null) check box under the Change data type transform to set a column as mandatory.
  5. Data size overflow warnings : This option filters the columns with data exceeding the maximum size allowed in the target.

3. After fixing the errors you can go to the Pipeline builder page and run your pipeline to export your data. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here

Limitations

1. You can import a maximum of 10 million records at a time.
2. You can export a maximum of 10 million records at a time.

FAQs

1. What should I do when the target match fails while exporting to Zoho Analytics?

When your pipeline run fails due to target match errors, please do the following steps to fix them: 
  1. In the Job summary page, click the Edit pipeline option on the top right corner. This will take you to the Pipeline builder page.
      

Notes
Note: Zoho CRM is shown in the screenshot for illustration purposes. The same will apply to all connectors.

b. Right click the last stage (to which you’ve added Zoho Analytics as destination) and choose the Prepare Data option. This opens the DataPrep Studio page.

      

c. Click the Target matching icon  at the top right corner just above the data grid. 

d. Choose the Show target option. This shows the Zoho Analytics module as the target and lets you align source columns to match it. Errors and  warnings are highlighted with red and yellow icons.
      
     
e. Click the All columns drop down and choose Error columns option. Then click the red or yellow icons to match your stage columns with the Zoho CRM module fields.

This adds the required data types and constraints to your stage columns so they match your target columns in Zoho Analytics.

Info
Note: The target columns from Analytics are named as per the API names. So please make sure to name your stage columns the same way. This is required for the system to detect and rightly map the columns to your Analytics fields as per API standards.

Once target is successfully mapped with no more error columns, you’re good to proceed with running the pipeline.

2. What do the different icons displayed during target matching indicate?

The icons displayed during target matching indicate the status of column mapping and validation:

  • Grey icon → Additional columns present in the source will not be included for export.

  • Yellow icon (source and target columns matched) → The column can accommodate values exceeding the size limit in the target. Click to update constraints.

  • Yellow icon (column available in target but not in source) → This is not a mandatory column in the target. You can either match this column with a source column, if available, or ignore this warning.

  • Red icon → This is a required column in the target, but there are no columns left in the source to match. A matching column is required in your data.

  • Green icon → Target matched.


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