Concepts of neebo
The following topics should help you understand how Neebo interacts with other systems and how it organizes your work.
In Neebo, asset is a general term covering Workspaces, datasets, documents, and other resources you might use for making analytic decisions. Almost everything you interact with in Neebo is an asset. Each different asset type has unique features to help you get your work done in Neebo. All assets also share common features to make them easier to discover and monitor.
Common asset features
Common asset features#
An asset name can be up to 100 characters long. Names cannot start with a space or underscore (_), and cannot contain the backtick character (`). Note that an asset name does not need to be unique.
The description can be up to 400 characters long.
Tags help quickly identify, search, and categorize assets in Neebo. A tag can be up to 80 characters (spaces are not allowed). Clicking on a tag launches a search for all assets with that tag in Neebo.
The owner is generally the person who added an asset to Neebo. The owner has the ability to change basic information about the asset like its name and description, to delete an asset (Workspace only), and to transfer ownership (Workspace and Document only).
Neebo Administrators have owner-level permissions to all assets. This includes the ability to transfer ownership.
Follow an asset to have any changes to it included in you Activities panel. Assets you are following will display a button on their detail pages and search results. Assets you are not following will show a button instead. Click on either button to toggle between following and not following the asset.
Datasets are the data assets in Neebo. They enable you to preview your data, cache it inside Neebo, discuss it with colleagues, and they can be opened in external tools for further analysis. Datasets can be added to Neebo or created inside a Workspace's Workbench.
You edit or transform data in Neebo by creating a Workspace, adding a reference to your data in the Workspace, and then using the Workbench to create a new dataset from that reference. See "What is a reference?" for more on the difference between a reference and a dataset.
Workspaces are Neebo's collaborative project areas. Add references to datasets and documents that you need for your project. Use the attached Workbench to combine, filter, and otherwise transform your referenced data into new datasets.
Use the Flow area to trace the lineage of your datasets and quickly show details about the referenced assets that provide data to them. Document with comments, tags, and the description field so that your work is more discoverable and you can easily distinguish between related projects.
The Workbench lets you view data from the references and datasets in your Workspace, then use that data to create new datasets. New datasets can be edited with operations, used elsewhere in Neebo, or opened in external tools like Tableau, or Jupyter for further analysis.
Three datasets pull data from a single reference in the Flow area of this Workbench.
The home page is your discovery and navigation center as well as where you add assets to Neebo. You can return to it from anywhere in Neebo by clicking the Neebo logo in the top corner of the screen. See Browse Neebo for a tour of the home page.
To help you locate your data wherever it lives, Neebo indexes basic metadata from all your organization's connected data source systems. We call this process "Introspection" and it collects all table and column names that Neebo can access. Neebo keeps this inventory of metadata updated as resources change and new systems are connected.
If you are the first user at your organization to connect a source system to Neebo, you will also be notified as new tables and columns from that system are indexed.
When you connect databases and data warehouses to Neebo, Neebo creates a virtual representation of the data assets they contain. Neebo acts as a live connection to these data assets and does not move or copy the data itself. You can discover, combine, and enrich these virtual assets inside the unified Neebo interface, then connect to them through you BI tools of choice to perform analysis.
Virtualization has several key advantages.
- BI queries against a virtual dataset inherit any Neebo data prep done on it, making queries more specific and minimizing data traffic out of your systems.
- Compute is pushed down to your data systems where possible, enabling better optimization and load management.
- Your data systems authenticate users with each Neebo query, so your existing access control mechanisms retain control over your data.