There are a several areas in TapClicks where you will be asked to select a Data View. The most common is when creating widgets on a dashboard. After selecting a Data Source (referred to as a "data category" in the widget creation interface), you must choose from a dropdown list of Data Views.
You might ask yourself: What is a Data View? This article answers that question.
What is a Data View?
Data Views organize data into structured groups to help you analyze and make business decisions.
A simplified way to understand Data Views is through a playing card analogy:
Let's pretend you want to connect your Facebook Ads account to TapClicks. Imagine all the data available from the Facebook API is represented by a deck of playing cards. Each specific card in the deck represents a field from that data source, which could be a metric (e.g., CPM, impressions, clicks), a dimension (e.g., Campaign, Ad), or an attribute (e.g., Start Date).
For example, You can group these cards by color, placing the red cards together. You can also group them based on their face value. Each of these is a way of organizing the cards based on a common trait.
Data Views categorize data fields in a meaningful way, making analysis and interpretation easier. Like playing cards, each field contains multiple pieces of information. Some of this information is numerical. It might be the count of clicks on a particular ad. This is called a Metric. Continuing with the card analogy, another piece of information might indicate whether a card is an Ace or a face card (King, Queen, or Jack). Those have some additional value beyond just the number. These are referred to as dimensions or attributes. Common dimensions you'll see include Campaign, Ad, Site, and Pixel. Dimensions add context to the data beyond just numerical values. For example, you might group data by Campaign.
TapClicks organizes data from Data Sources into Data Views for several reasons:
- enable users derive insights from the data
- group fields that work well together in reports and analysis
- accommodate limitations in how data is served from the source
What Data Sets are Used to Create Data Views?
Metrics
- Numerical fields that serve as performance indicators
- Examples: Impressions, Cost, and Click-Thru-Rate (CTR)
Dimensions
- Fields that add granularity and typically increase the number of rows in a dataset (one per dimension type).
- Examples: Campaign, Ad, Site, Pixel, and Action
Attributes
- Descriptive fields that provide additional context to dimensions without increasing granularity.
- Examples: Campaign Start Date, Ad Size, and Target Audience