Getting started is easy and you can be up and running in less than 30 minutes by just following these three steps.
Connect your data and define all your datasets - already have the data, connect your data warehouse. Need help getting the data, integrate with one of our data pipeline partners. Once you're connected, Data Preparation and Data Definition has never been easier to manage.
Let our unified data transformation layer inspect all of the data you connect and build useful models to speed up your analysis.
Have something totally custom, dive in deep and configure your own custom models
Invite teams into Personalized Workspaces and let them start safely customizing their metrics, setting up monitoring and letting the system push insights to them, freeing up more time to focus on the business.
When getting started using a new platform, it can often take time to “learn the ropes.” At Pano, we want to minimize that time so you get immediate value out of the platform. The below definitions explain how the platform is organized in an effort to help you quickly get up and running.
BOARD - A Board can be thought of as your “visual organizer.” A Board can consist of one or more charts. There are two types of Boards: Featured Boards and Custom Boards.
Featured Boards - Part of the enterprise offering, Featured boards provide out-of-the-box report templates that appear soon after connecting your data to Pano. A Featured Board typically contains 5+ charts to provide you inspiration into how to analyze and visualize your marketing performance based on the data source you've connected (i.e. Facebook Ads, Google Search, etc.)
Custom Boards - A Custom Board is a collection of charts that you, your team, or Pano’s Analytics Consultants have created which are tailored to your specific reporting needs
DATAFRAME - Within each board lives one or more Dataframes. A Dataframe in Pano is considered any view of your underlying data, either in the same format as it exists in the data warehouse or transformed to match your reporting needs. These Dataframes can either be presented as tables or using any of the available chart types. As you assemble your transformed data, its common to think of boards similar to schemas in a database and Dataframes as the tables within the schema.
FIELDS - Each Dataframe is made up of one or more fields. Fields split up into two types, dimensions or metrics. At its most basic level, metrics are fields that can be aggregated for reporting purposes and dimensions are the fields that are used to group metrics into buckets. Fields are used to populate tables and charts according to your specific needs. Most organizations have a set of key performance indicators, or KPIs, which can be used to determine the right metrics and dimensions to include in your Dataframes.
Metrics - Measurable values that can be aggregated for reporting. Metrics are restricted to certain data types where algebraic or logical functions can be applied. Common examples include Cost Per Thousand Impressions (CPM), Video View Rate, Return on Ad Spend (ROAS), Click Through Rate (CTR).
Dimensions - Technically defined as anything that is not a metric, these can include entities, attributes of entities or any other non-metric breakdowns available in the data. Common examples include the ID of a customer, where they are located (Region, Country) or what type of audience they fell under (Males, Ages 20-30, etc.)
DATASET - The foundation of any Dataframe is the one or more Datasets that feed into it. These Datasets represent the raw data that is piped from an external API, such as Facebook Ads or The Trade Desk into your connected data warehouse. During the data modeling phase each group of tables from a single source should be defined as a Dataset. These Datasets can then be pulled into a Dataframe and blended to meet your reporting needs.
If you are an Admin, you will see the Main Menu, which displays three primary tabs: WORKSPACES, INBOX, and COMPANIES.
WORKSPACES - Secure areas for teams to collaborate around their data, while allowing Admins to customize permissions (e.g. giving access to one agency for certain campaigns, sectioning off access per teams for different product lines, etc.). Within one Company, there can be multiple Workspaces. Common examples of using more than one Workspace include separating data by marketing channel, product lines, store locations, or movie titles. All users within a Workspace will see the exact same content, from Boards to Dataframes to comments, Pano is designed this way to make sure everyone on the team is seeing the same information and can collaborate easily.
INBOX - Destination for all your message types (Public, Private, Team-specific) across all of your Workspaces. Inbox is especially useful if your Company uses multiple Workspaces. The Inbox is tailored for each user to include all of the messages that are most relevant to them.
COMPANIES - Independent entities that define a Pano billing relationship. Companies are the highest level abstraction for data in the Pano platform. No data, fields, models or any other Pano objects can ever be shared across companies. Companies can set permissions for all Workspaces such as which fields to expose from the Data Glossary or which users should have access.
After creating and selecting a Workspace, you will see the Workspace Menu, which displays five primary tabs:
FEED, FEATURED BOARDS, CUSTOM BOARDS, GLOSSARY, and SETTINGS.
FEED - Destination for all your message types (Public, Private, Team-specific) within a given Workspace.
FEATURED BOARDS - [Enterprise Tier only] - These are out-of-the-box Boards that come with pre-set charts to help you quickly visualize your marketing performance without the need for any customization or ramp-up time.
CUSTOM BOARDS - These are any Boards that have been built and customized by collaborators in the Workspace. Each custom board can have the name, description, date range selector and default comparison defined by the board creators.
GLOSSARY - Any fields that have been defined in your data modeling or created in the platform will appear here. You can customize these fields by adding a clear definition, abbreviations, formatting and other helpful attributes.
SETTINGS - Here you will be able to customize the general details of your Workspace, including adding Collaborators, connecting your Datasets, re-naming your Workspace, and add an image icon to your Workspace.
Just below the Workspaces tab within the Main Menu Navigation is Your Inbox. Inbox allows you to work across multiple Workspaces, combining private, public and team-specific messages in one place. After selecting Inbox, you will see the following options on the left menu:
All - Displays all Read and Unread Messages
Unread - Displays ONLY Unread Messages
Active - Displays ONLY Messages that have not yet been Resolved
Resolved - Displays ONLY Messages that have been Resolved
All - Displays All types of Messages (Public, Private, I'm Following, @Mentions)
Public - Displays ONLY Public messages (messages that appear in your Workspace)
Private - Displays ONLY Private messages (sent directly to you from 1+ people within your Workspace)
I'm Following - Displays ONLY messages that you are Following
@ Mentions - Displays ANY messages that you are directly mentioned via the @mention. These can include both private and public messages.
After creating a Company within Pano, you will see the Company Settings Menu, which displays the following tabs:
COMPANY, SHARING, WORKSPACES, USERS, TEAMS, DATA CONNECTIONS, DATASETS, GLOSSARY.
COMPANY - Here you can edit basic settings like changing the name of your Company should you need to.
SHARING - [Enterprise Tier Only] View or share access to any other companies working with your marketing data, such as consultants or agencies.
WORKSPACES - Display any Workspace(s) that have been created under your Company.
USERS - Display active and inactive users within your Company. You can also invite new users or remove individual access here
TEAMS - Create teams for groups of users to easily communicate with one another.
DATA CONNECTIONS - List of data warehouses that have been connected to the Pano platform. Each data connection will be scanned and the visible tables within the connection will become available for data modeling.
DATASETS - Datasets are common groupings of data based on the data's original source or meaning. It's important to define datasets to create meaningful groups of data for easier and more useful analysis. Two examples of common datasets could be a set of Facebook Marketing tables pulled in by Fivetran or mobile app activity tables uploaded by Appsflyer.
GLOSSARY - Displays all mapped fields across all Workspaces within that company, this is beneficial for company admins to track and audit all the metrics that are being used.