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Periscope Data Vs. Looker: Four Questions to Help You Decide

Choosing a BI platform is a big decision. There are a lot of factors to consider as well as significant impact on every line of business and the way employees function across teams. To make it easier to determine between Periscope Data and Looker, we’ve boiled down the differences between the two BI platforms into a series of four big questions. If your team is evaluating a move to either Looker or Periscope Data, it’s important to make sure you’ve had conversations about these topics before you make a final decision.

1. Which analytics language(s) are already part of your workflow?

To use Looker, data teams need to use LookML, a proprietary language that serves as an additional layer between your data sources and the final data analysis. Since LookML is only valuable inside Looker, every analyst who uses Looker to prepare data has to learn the language in order to use the tool. As your team grows and adds more analysts, they’ll all require a period of training before they’re able to model BI data.

Periscope Data allows analysts to query data using SQL, a common language that they already know. This accelerates time to insight and makes the platform far more accessible to all users.

2. Are your business and underlying data structure constantly changing?

One of the biggest differences between Periscope Data and Looker is the amount of time that passes between asking a question and finding the answer. Looker’s BI platform allows data experts to build data models that answer predictable questions. It may take weeks or even months to build a model to answer a question, but once the model is built, that specific question will remain answered. However, if the question changes at all or a new source of data is added to the mix, Looker requires the model to be rebuilt.

If your plans include expansion of your data collection or your data capabilities, Periscope Data’s BI platform is extremely flexible. To manage new data sources, our network of more than 100 integrations and partners makes this easier than ever. With a lot of these solutions (Redshift, Snowflake, Salesforce, Oracle Etc.), connecting the data is as simple as a login and a few clicks.

Periscope Data’s BI platform is built to answer questions as fast as possible (usually in minutes), making it easier to adapt to change. The platform still incorporates reusable code (SQL Snippets and Views) so data teams aren’t starting from scratch every time they need to build a visualization. If your data needs (or your business questions) are frequently changing or you want to empower your data team to explore their own questions, Periscope Data is the best tool for you.

3. Do you have dedicated resources to maintain your data infrastructure?

In Looker, there’s a modeling layer (LookML) between the data that goes into analysis and the visualizations that come out. If there are significant changes to either in necessary inputs or desired outputs of that analysis process, the extra layer presents a problem. For every minor change, data resources are required to update the model.

Not only does this slow down the process overall by creating a bottleneck around LookML analysts, it also creates more opportunities for things to break. It also forces teams to create analysis that isn’t valid anywhere outside of Looker.

Periscope Data avoids these problems by using SQL instead of a proprietary language. Without a modeling layer, data passes directly from a source to a visualization using a simple coding language. Our approach doesn’t require specialists to maintain data models, making it the easiest way to make sure that your analytics infrastructure is capable of managing unexpected changes.

4. How important is supporting Python or R analytics in your choice of platforms?

This is an easy one. If you’re satisfied with querying data in just SQL (or LookML), Looker can get the job done. If you want to use SQL in conjunction with more advanced languages, like R and Python, to do predictive analysis or join predictive results with actual data for insights, you'll need to use a more powerful tool like Periscope Data.

The best way to answer the questions of which languages you want to use is to look at the types of analysis your organization needs. SQL is great at backward-looking grouping and counting. If the extent of your data analysis is going to be routine line-of-business reporting, you don’t need anything more than SQL. If your data analysis plan involves predictive analytics, natural language processing or preparing data for machine learning models, you’ll need a platform that can handle those more advanced operations.

If you don’t know the answers to any of these questions, it’s a good idea to discuss them with your team. In general, Looker is built for teams that need simple, predictable line-of-business reporting. Looker’s BI platform is built for teams with finite data needs who utilize a data team primarily as a preparer for business professional drag-and-drop analysis.

If your data plans involve more advanced analytics and the ability to tackle new questions instantly, you need a tool like Periscope Data. Our BI platform empowers every member of the organization to explore data and quickly find the insights they need, whether it's business reporting or predictive analysis.

To learn more about Periscope Data and how our BI platform differs from Looker’s, check out the Convince Your Boss Periscope Data is Best For Your Business guide.

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Trinity Nguyen
Trinity is the senior product marketing manager at Periscope Data. She is experienced in product positioning, messaging and sales enablement at both startups and Fortune 100 technology companies. When she's not working, she can be found planning her next international trip while listening to Big Gigantic or the latest audiobook at 2x speed.