- April
Posted By : Caitlin Daugherty
Four Steps to Start Your First Project in Knarr

Knarr is filled with quick and easy tools for complex operations that will enable you to find the insights hidden in your data faster than ever. BUT with any new software tool, it may be difficult to know where to start. Beginning any new project in Knarr starts with four basic steps: loading data, exploring, capturing analysis, and collaborating with your team. 

So without further ado, click here to log in to your account, and let’s get started…

Step 1: Load Data

Before you begin, you will need to know which data source you will be loading from and if applicable, your account login information and the file path or URL to your data set. So be sure to have them handy. 

To follow the detailed guide on connecting to your specific data source click here ›

Once you add your data source, depending on which one you choose, you’ll be prompted to either enter a URL or choose a schema and/or database. 

Your schema will be generated and displayed in the left panel as a list of tables you can choose from. Click any of the tables to view the columns within them. To insert any table, click the SQL -> button to the right of the table. After previewing the data add “Apply Changes” to load. 

Knarr allows you to combine and analyze data from multiple sources. To do so, you will load one table at a time. To add another table click “Add Data” and follow the same steps to add a different source or simply select another table from a source previously added. 

Note, since you can only load one table at a time, clicking the SQL -> button will overwrite your current SQL code. If this happens, you can click into the SQL box and press Ctrl + Z on your keyboard to reverse the changes.

For a detailed guide on working with your data model click here ›

Step 2: Explore

Below are the basics to get you started slicing, dicing, and visualizing your data quickly and easily with Knarr. We’ve included links to our detailed guides on the support portal for you to become a master in no time. 

Adding Charts: 

Create charts by either clicking the icons in the top toolbar or by right-clicking the canvas, selecting “Add object” and choosing your type of chart.

For a detailed guide on visualizing data with charts click here ›

Adding Tables: 

Create a table by either clicking the icon in the top toolbar or by right-clicking the canvas, selecting “Add object” and choosing “Table,” as seen below.  

Once you create a table, add a dimension or a measure to it by clicking the “+” button in the properties panel. 

For a detailed guide on working with tables click here ›

Using the Filter Panel: 

The filter panel allows users to rapidly search and filter multiple fields to see how the data changes, or use lenses to find associations in the data right from here.

The filter panel can be accessed in the top right corner of the canvas with the funnel icon. This will open a panel containing all of the available fields in the pad’s data model, along with a histogram in each field depicting the frequency of each value.

For a detailed guide and more tips on using the filter panel click here ›

Advanced Filtering with Lenses: 

Lenses are designed to allow you to filter data in complex ways so you can quickly and easily see relationships and associations without writing any code.

Lenses can be accessed either from the left-side filter pane, or from the full-screen filter panel. To lens a field, click the camera lens icon on the top right of the field box:

For a detailed guide on associations and lenses click here ›

Global Search: 

In explore mode your “Context” section of the dataset panel contains information about the fields available in the data model, as well as a global search.

Global Search will search all values in the current dataset. Clicking any of these values will filter to those values in your context filters.

For a detailed guide on context and global search click here ›

Step 3: Capture Analysis

Notes are a great way to record your thoughts while you’re building an analysis, allowing you to type rich text and save Snapshots inline with your text. 

To add a note click the “New Note” button in the top right of the notes panel.

To delete a note right-click and select “Delete” to remove the note. Remember that only the creator can delete a note and doing so will delete the note for all users, so be careful! It’s often better to leave the note or rename it in case you want to reference it later. 

Snapshots are visual bookmarks that capture and save all items on your canvas workspace at a point in time allowing you to reference back to any analysis at any point in time with all the context present. Use keyboard shortcut “CMD + K” or “CTRL + K”  to save a snapshot while you’re typing in a note.

For a detailed guide on capturing your analysis with notes click here ›

Step 4: Collaborate

Share a project with your teammates in Knarr by clicking the “Share” button in the top right corner of the screen next to your account avatar. You’ll be prompted to add the email address associated with their Knarr account in a dialogue box. Once you have shared your project with a teammate, by default you share the same data model, but are placed in different sessions so your selections and canvas layout are separate.

To share the same session, click on the “My Workspace” drop down and select a teammate’s workspace to jump into their session. This will allow you to both make selections and create objects in a shared multiplayer workspace.

When you’re finished, click on the drop-down and select “My Workspace” to jump back into a solo session.

For a detailed guide and tips on collaborating in shared workspaces click here ›

Now that you have the basics covered, click here to log in to your account and start exploring today. 

Caitlin (Katie) is the Head of Communications and Operations for Knarr Analytics. With a background in policy analysis, project management, and communications for various organizations, she is excited to empower analysts and businesses with a better way to explore their data.

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