Once you have data access to a dataset, you can further explore the dataset by adding it to a project. The Redivis project interface allows you to develop scalable, reproducible, and self-documenting data pipelines as you filter, transform, and merge data from across Redivis.
➊ To begin, select the Add to project button. From the drop-down, you can add the dataset to an existing project, or create a new project.
![screenshot of selecting Add to Project button, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Add_to_project.png)
![screenshot of adding a dataset to an existing or new project, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Select_project.png)
➋ This will bring the dataset into the Redivis project interface. Select the dataset icon to view the tables in the dataset. You can select a table to view its variables and summary statistics. In this case, we will select the articles_1977 table.
![screenshot of selecting a dataset in the visual query editor and viewing its tables, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Project_-_look_at_tables_new.png)
![screenshot of selecting a table in the visual query editor and viewing its variables, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Project_-_look_at_variables_in_table_new.png)
➌ To manipulate the data, click the Transform node underneath the table icon. This will open a panel on the right side of the page where you can 1) apply certain transformations, and 2) select variables to include in the output.
![screenshot of selecting the transform node, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Select_transform_new.png)
![screenshot of transform node panel, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Transform_panel.png)
➍ In this example, I want to filter the data to only include articles from the Business section. For my future reference, I rename the transform "Filter by Business section" and add a Filter step.
![screenshot of renaming the transform "Filter by Business section" and selecting a Filter step, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Transform_panel_-_add_filter_step.png)
➎ I specify the rules for my Filter step (section LIKE 'business'), and select four variables for inclusion in my output: section, title, authors and paragraphs. Then I click Run.
![screenshot of setting the transform rules, specifically 1) defining the Filter and 2) selecting variables to include in the output, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Transform_panel_-_filter_by_section__select_variables.png)
![screenshot of selecting Run button, as explained on this page](https://libapps.s3.amazonaws.com/accounts/276812/images/Run_transform.png)
➏ My output appears as a new table in the visual query editor. I can also see more information about my output on the right side of the page.
![screenshot of the transform output in the visual query editor, as explained on this page. The transform output is a new table.](https://libapps.s3.amazonaws.com/accounts/276812/images/Transform_output.png)