The Beginner’s Guide to
In our world that is consumed by the acquisition of data for everything from commerce to education, importance is placed on data activation, which is the way of changing information into actions.
Data activation is normally achieved by pulling clean, transformed data out of its data warehouse and placing it into the operational systems that are relied on by teams in an organization, such as marketing and sales.
This is where the purpose for Looker actions comes into play. Looker Actions is a tool for data activation that is offered by the Looker data platform.
But before you move any further, indulge in this beginner’s guide to Looker Actions to be privy to what users can expect from it.
Introduction to Looker
The Looker data platform, which was bought by Google in 2020 for $2.6 billion, is a business intelligence (BI) solution that is generally for dashboarding needs to create visualizations on the data a user chooses to work with.
Looker is a browser-based way of collecting, visualizing, and analyzing data to make and share dashboards that are interactive, leverage embedded analytics and automated alerts.
Using Looker can happen in the cloud or on a company’s premises. But be aware that when you first start using Looker, it will require quite a bit of effort because all the data will need to be formatted and modeled using the Looker coding language called LookML.
Looker Actions Explained
Looker Actions is a data activation tool that makes it possible for users to analyze and act on data in real-time so business teams can perform tasks such as automating emails, updating application values, signaling team members, and sending email lists to marketing platforms.
The aim of Looker Actions is to push data into the native tools of its users so they can have the capability to leverage data and make beneficial decisions based upon it.
There is also the Looker Action Hub feature to send content to third-party services that are directly integrated with Looker directly through an action hub server.
Data Modeling Limitations
Even with the advantages that Looker Actions presents, it also comes with a few disadvantages that should be considered.
Remember that Looker is based on its own LookML coding language, which puts limits on data modeling and matching possibilities.
Simply put, to use Looker Actions effectively, organizations must model all their data in LookML. The drawback to being forced into this corner is that companies cannot use their own data models or tools from their tech stack whenever they wish to transform their data.
The reality of this situation is that if a company isn’t already situated in Looker, there will be a cost of money and time to convert everything over and get the staff up to speed.
Also, being that most organizations tend to leverage SQL (Structured Query Language) to transform their data, users will have to learn LookML because it is not completely built on SQL.
Large Data Issues
Unfortunately for users of Looker Actions, they will find out that the service has difficulty dealing with large data volumes because Looker Actions does not do any data differencing (diffing) to check what data has been altered prior to sending off to another application.
In other words, each time that data is requested, Looker Actions sends all records of it, including the duplicates.
To make large data issues even worse, Looker Actions doesn’t have batching abilities for many destinations, so if a large data set must be moved, there is a very high chance that this will fail because of a rate limit problem.
Looker Actions has few destinations with only 20 integrations at the moment. Therefore, it won’t be able to connect with each and every business/SaaS tool stack.
It also doesn’t offer users the chance to map data using any specific field, so in order to leverage Looker Actions, users have to keep changing their underlying LookML data models to connect with the limited number of destinations that are available.
In summary, Looker is a business intelligence tool that comes with data integration limitations, such as Looker Actions being rendered unusable if the data isn’t modeled through LookML first. This may force business teams to have to manage their data all the way in the Looker system and abandon other tools that they may be more familiar with.
Hightouch is a more flexible option due to its ability to send data in batches, unlike Looker Actions, which let users update any field, whereas Looker Actions limits fields, and along with data warehouses, Hightouch integrates directly with Looker and LookML, allowing companies to connect directly to Looker and select their reports.