Bringing self-service analytics to your organization can be a long but rewarding journey, and it certainly doesn’t stop after the launch of your first instance. Succeeding with your data through Looker is an ongoing process of education, enablement, and discovery.
Whether you are a seasoned Looker customer, or rolling out your instance for the very first time, we’d like to share some tips that have helped our customers maintain healthy instances and teams of happy, effective users.
First, and most importantly, make sure your team is aware of the Looker training resources. Sharing these courses early and often with every Looker-user in your organization will help enable confident self-servers.
The more intuitive your explores and dashboards are, the better users will be able to self-serve. An easy way to get started is to check out our eLearning course on “Building Explores Users Will Love”. Additionally, deleting old content and holding regular data-governance meetings will go a long way in helping to keep things clean for your teams. Lastly, leverage the iLooker feature to make data-driven decisions about what to delete.
Identifying Looker “ambassadors” across your organizations is a great way to build a support network for users. Ambassadors are often stakeholders who represent their end-user groups. They’re able to help answer questions and drive adoption within their respective teams. If you’re looking for ways to identify potential ambassadors at your organization, use iLooker to take a look at those who have the highest Looker usage data.
Once you have ambassadors in place, encourage them to consider owning one or more of the following, based on their strengths:
Creating a data dictionary of all the fields in an explore will help keep track of the logic developers are putting in the modeling layer. If you have thousands of fields, you can search for the fields you need and quickly figure out what they are called.
Important Note: To create a data dictionary, you will need an internal site to host the values, or you can use a Wiki page.
Looker is a very powerful tool, which means people can certainly find ways to create a confusing environment for end-users. Below are a few common pitfalls that can get in the way of self-service and success.
If all users are able to see all the explores in your instance, they can easily become confused. It is important to give users access only to what they need to do their jobs. If you have niche explores, consider hiding them from users who don’t need them.
Having one giant explore with everything can cause content-overload and confusion. It is important to name your dimensions and measures things that actually make sense. The more clear and specific you are with naming, the better. Additionally, be sure to use ‘group’ and ‘view’ labels in order to better organize the field picker for your end users
If your instance is the wild-west of users saving content anywhere they please, content redundancy, difficult clean-up, and prolonged confusion are likely to ensue. Set guidelines for how and where you’d like users to save their content to help keep everyone on the same page.
If you want to learn more, check out how Diana and the team at AdoreMe cracked the code on best practices and adoption.