Why this happens?

In some cases, when the amount of data coming from the API is too large, Data Studio does longer to load your charts. This challenge is pronounced when:

  • iOS apps: Apple sends one file per day worth of data, making the API heavy and hard to process. If you're looking at 90 days of data, that's 90 different data files you're pulling at the same time;

  • We're processing large apps, with millions of data points (mostly from app units, sales and revenue)

The key point here is that sometimes there are just too many lines on a given dataset so Data Studio struggles to process it.

Here's a couple things we learned from our clients when dealing with loading speed issues:

1) Use Google's Extract Data connector

You can find it on this link.

It adds up to 100MB worth of data on your cache, which can help a lot or a little (depending on how much data we're talking about).

Our recommendation: pick only the dimensions you really use to avoid importing data you won't need. You can also filter your data. In the example below I'm filtering for app installs, for example. You can then create multiple extractions to get only the data you need.

👇 This video provides more detail on how to use this data extractor

2) Calling your inner Data Studio ninja

There's also ways to avoid this problem by adopting a few best practices:

  1. Use multiple pages to organize your charts. Don't build one massive page with everything you need at once (that will constantly break your dash)

  2. Always filter your data

  3. Reduce the data freshness of your connector

  4. Expand your date range as your data is cached, avoid downloading multiple months worth of data before downloading one

Most of all: we ask you to be patient. In the end, if it takes a lot of time it's because there's lots of data coming in. From our end, we're working on ways to overcome this.

And what about a more permanent solution, you may ask?

A new data destination

We already know that the main obstacle is Data Studio's capacity to handle data coming from 3rd-party connectors like ours. So added Google BigQuery as a data destination on our roadmap. We're aiming to launch it on Q2 or Q3 2022.

Data processing

We're also exploring ways to treat your data so it can be condensed before sending to Data Studio. That'd work as a pre-filter so you can send less data to your dashboard, which helps with the loading speeds.

Meanwhile, please reach out so we can think on alternatives together. We're also always happy to receive suggestions from you so feel free to do so.

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