Oracle® Cloud

Known Issues for Oracle Data Visualization Cloud Service

E66330-08

February 2019

Known Issues

Learn about the issues you may encounter when using Oracle Data Visualization Cloud Service and how to workaround them.

Documentation Accessibility

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Supported Browsers

This topic describes the minimum requirements for web browsers that Oracle Data Visualization Cloud Service supports.

Web Browser Version

Microsoft Internet Explorer

11 and later

Microsoft Edge

38 and later

Google Chrome

54 and later

Mozilla Firefox

45 and later

Apple Safari

10 and later

Known Data Visualization Issues

If you encounter an issue visualizing your data, check here for a workaround.

Issues Importing Data Flows Containing Operators and Multiple Conditions from Oracle Analytics Cloud or Oracle Data Visualization Desktop

In Oracle Analytics Cloud or Oracle Data Visualization Desktop, you can export projects that include data flows containing join conditions with operators and multiple conditions using AND or OR.

Oracle BI Cloud Service and Oracle Data Visualization Cloud Service don’t support these join functionalities. If you import such projects, Oracle BI Cloud Service or Oracle Data Visualization Cloud Service changes the join operator to “equals” and treats multiple join conditions as AND.

Oracle RightNow Cloud Service Has a New Name

Oracle RightNow Cloud Service is renamed to Oracle Service Cloud.

The Data Visualization’s Create New Connection and Add a New Connection dialogs are updated to reflect this name change.

List Visualization Doesn’t Work Properly

If you use the List visualization in your projects, then you might encounter the following issues.

  • If you have a canvas with multiple List visualizations with the Use as Filter setting enabled and the user makes selections in more than one List visualization, Data Visualization can enter into a loop where the List visualizations update each other multiple times. Sometimes this loop is endless. To work around this issue, you can break the endless loop by disabling the Auto Apply Data setting and removing the list visualizations or changing the visualization type.

  • If you added the List visualization from the Finger Pane's Visualizations tab, then you can’t deselect the items in the List visualization. To work around this issue, disable the Use as Filter setting for the List visualization added from the Finger Pane’s Visualization tab, and then you can deselect items in the visualization’s choice list.

  • Cross-visualization marking doesn't correctly mark items in the List visualization. This issue has no workaround.

Data Blending Auto Option Behavior Change

In previous releases of Data Visualization, when using columns from multiple sources, the default blending (Auto) often resulted in an “All Rows – All Rows” blending, whereas the more appropriate option was only one data source set to “All Rows” and the others set to “Matching Rows.”

In the current release of Data Visualization, when a visualization includes columns from multiple data sources and none of the columns are match columns, the data blending option of “Auto” results in only a single data source being set to “All Rows.”

Date Formats in CSV Files

If you add a CSV file as a data source and the CSV file contains dates, then they must be in the YYYY/MM/DD or YYYY-MM-DD format. If you use any other date format, then Data Visualization imports those date formats as a text column. If you try to change the data type to Date when importing the CSV, then you get an error.

Perform the following procedure to work around this problem.
  1. In Data Visualization, delete the incorrectly imported data set.
  2. Import the CSV, but leave the data type as Text.
  3. Create a project and add the data source.
  4. In the Project Editor, go to the Prepare canvas.
  5. Duplicate the column.
  6. Change the formula of the copied column to something like:
    CAST(SUBSTRING(Date,7,4) || '/' || SUBSTRING(Date,,4,2) || '/' || SUBSTRING(Date,,1,2) AS DATE)

    This example assumes the original format was DD/MM/YYYY.

Null Values in XLSX File Set to String

If you're adding an XLSX file as a data source and if the spreadsheet’s null values are expressed as hyphens, then Data Visualization treats the null values as string irrespective of the other values in the column.

To work around this issue, remove the hyphens from the column and try to import the XLSX file again.
Error Importing XLSX Files Generated from Microsoft Access

Importing an XLSX file generated from Microsoft Access can sometimes fail. Data Visualization can interpret such XLSX files as header-less or even empty.

Perform the following procedure to work around this issue.
  1. Open the Access-outputted XLSX file in Microsoft Excel.
  2. Select a cell.
  3. Make and reverse a change. For example, select the top left cell, type an X, and then remove the X.
  4. Save the file.
You can now import this modified file successfully into Data Visualization.

Data Visualization Database Support Limitations

Data Visualization doesn’t fully support all of the databases listed in the Create Connection dialog. In some cases, Data Visualization doesn’t support all versions of a specific database.

Data Visualization provides limited support for databases marked with the Beta label.

In the Create New Connection dialog, some of the databases might be marked Beta. The Beta label indicates that the database has been tested, but isn’t fully supported. Data sources created from databases marked as Beta might contain undocumented limitations and you should use them as is.

Data Visualization Supported and Unsupported Data Types

This section contains information about the data types that Data Visualization supports and doesn’t support.

Unsupported Data Types

Some data types aren’t supported.

You'll get an error if your database data source contains data types not supported by Data Visualization.

Supported Base Data Types

When reading from a data source, Data Visualization attempts to map incoming data types to the supported data types.

For example, a database column that contains only date values is formatted as a DATE, a spreadsheet column that contains a mix of numerical and string values is formatted as a VARCHAR, and a data column that contains numerical data with fractional values uses DOUBLE or FLOAT.

In some cases Data Visualization can’t convert a source data type. To work around this data type issue, you can manually convert a data column to a supported type by entering SQL commands. In other cases, Data Visualization can't represent binary and complex data types such as BLOB, JSON, and XML.

Data Visualization supports the following base data types:

  • Number Types — SMALLINT, SMALLUNIT, TINYINT, TINYUINT, UINT, BIT, FLOAT, INT, NUMERIC, DOUBLE

  • Date Types — DATE, DATETIME, TIMESTAMP, TIME

  • String Types — LONGVARCHAR, CHAR, VARCHAR

Supported Data Types by Database

Data Visualization supports the following data types.

Supported Oracle Data Types

  • BINARY DOUBLE

  • BINARY FLOAT

  • CHAR

  • CLOB

  • DATE

  • DEC (p,s)

  • DECIMAL (p,s)

  • DOUBLE PRECISION

  • FLOAT

  • INTEGER

  • INT

  • NCHAR

  • NUMBER

  • NUMBER (p,s)

  • NUMERIC (p,s)

  • NVARCHAR

  • NVARCHAR2

  • REAL

  • ROWID

  • UROWID (size)

  • SMALLINT

  • TIMESTAMP

  • TIMESTAMP WITH LOCAL TIMEZONE

  • TIMESTAMP WITH TIMEZONE

  • VARCHAR2

Issues with Predefined Application Roles

Oracle Data Visualization Cloud Service supports three application roles: Administrator, User, and Viewer.

Additional predefined application roles display in the Console but they are not currently used. Specifically, those named Data Loader, and NA.


Oracle Cloud Known Issues for Oracle Data Visualization Cloud Service

E66330-08

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Documentation for Oracle Data Visualization Cloud Service users that describes known software issues and their workarounds for this release of Oracle Data Visualization Cloud Service.

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