In this blog we will talk about a new feature in the latest version of Oracle Analytics Cloud called Replace Dataset. This feature allows users to intelligently apply (or map) data visualization analyses created using one dataset on to another dataset with few clicks and intuitive column mapping.
Oracle DV allows users to create in-depth and insightful analyses, add sophisticated calculations, create nice looking infographics and more. Sometimes after spending quite some time and energy on a project, they realize they want to do "similar" analysis on different dataset or substitute certain columns within those analyses. Replace Dataset feature lets users to capitalize on the efforts they have already put in creating a project by offering a intelligent tool to swap the dataset/columns with its corresponding new dataset/columns. This feature come handy also in situations where you do analysis on one batch of data and later you want to perform the same analyses on a different batch of the same data set (perhaps for a different date range or region or product).
For demonstration purpose in this blog we will use a sample project which analyses Quarter Value growth, Quarter indexed growth, and Quarter Ago growth for a sample sales data. Here are quick snapshots to give you a quick overview of this project:
This analysis looks good and as a end business user I would like to do exact same analysis but for a different data that I have: Expenses data. To achieve this goal I will use Replace Data Set feature and in this process I will walk you through this feature in detail.
Replace dataset feature is quite easy and intuitive to use. To replace dataset in an existing project with another dataset, user has to simply right click on the dataset and select "Replace Data Set" option. Please note Replace Data Set option is available only for non-joined datasets. Here is a quick snapshot that shows how to invoke this option:
This will open a prompt window which lets users select or map the columns of existing dataset to the columns from new dataset. Oracle Analytics identifies columns which are used in the project (visualizations and custom calculations) and prompts user to map only the used columns to relevant columns in the new dataset. Here is a quick snapshot that shows how the prompt window looks like:
Once user clicks Replace button, all the existing visualizations will be updated with metric and dimension columns from the new dataset without any manual intervention. In this case we are replacing the Sample Order Lines dataset with Expenses dataset. This is how the canvases look like with Expenses dataset (with a filter that removes data for 2016, as we do not have data for entire 2016):
Another important functionality of this feature is, if the user would like to replace a column in this dataset with another column in the same dataset, he/she can use Replace Data Set option -> select the same dataset and then map the column to be replaced with a new column in the dataset. In this example if user would like to replace Business unit with Expense type, he/she has to map Business Unit column to Expense Type column.
To summarize, Replace Data Set feature lets users choose a project as a template and use the same analysis for other datasets with few clicks and without having to manually re-create the entire project which is tedious and time taking.
Here is quick video tutorial that demonstrates Replace Data Set feature:
Oracle DV allows users to create in-depth and insightful analyses, add sophisticated calculations, create nice looking infographics and more. Sometimes after spending quite some time and energy on a project, they realize they want to do "similar" analysis on different dataset or substitute certain columns within those analyses. Replace Dataset feature lets users to capitalize on the efforts they have already put in creating a project by offering a intelligent tool to swap the dataset/columns with its corresponding new dataset/columns. This feature come handy also in situations where you do analysis on one batch of data and later you want to perform the same analyses on a different batch of the same data set (perhaps for a different date range or region or product).
For demonstration purpose in this blog we will use a sample project which analyses Quarter Value growth, Quarter indexed growth, and Quarter Ago growth for a sample sales data. Here are quick snapshots to give you a quick overview of this project:
This analysis looks good and as a end business user I would like to do exact same analysis but for a different data that I have: Expenses data. To achieve this goal I will use Replace Data Set feature and in this process I will walk you through this feature in detail.
Replace dataset feature is quite easy and intuitive to use. To replace dataset in an existing project with another dataset, user has to simply right click on the dataset and select "Replace Data Set" option. Please note Replace Data Set option is available only for non-joined datasets. Here is a quick snapshot that shows how to invoke this option:
This will open a prompt window which lets users select or map the columns of existing dataset to the columns from new dataset. Oracle Analytics identifies columns which are used in the project (visualizations and custom calculations) and prompts user to map only the used columns to relevant columns in the new dataset. Here is a quick snapshot that shows how the prompt window looks like:
Once user clicks Replace button, all the existing visualizations will be updated with metric and dimension columns from the new dataset without any manual intervention. In this case we are replacing the Sample Order Lines dataset with Expenses dataset. This is how the canvases look like with Expenses dataset (with a filter that removes data for 2016, as we do not have data for entire 2016):
Another important functionality of this feature is, if the user would like to replace a column in this dataset with another column in the same dataset, he/she can use Replace Data Set option -> select the same dataset and then map the column to be replaced with a new column in the dataset. In this example if user would like to replace Business unit with Expense type, he/she has to map Business Unit column to Expense Type column.
To summarize, Replace Data Set feature lets users choose a project as a template and use the same analysis for other datasets with few clicks and without having to manually re-create the entire project which is tedious and time taking.
Here is quick video tutorial that demonstrates Replace Data Set feature:
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2 comments:
Thanks for sharing beautiful information about Replace Dataset Feature
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