Why BigQuery is your answer to Data Studio performance problems

Why BigQuery is Your Answer to Looker Studio Performance Problems

Many agencies that are using connectors like Supermetrics or Funnel are experiencing performance issues when working with Looker Studio (formerly Data Studio) once datasets get bigger and the reason is that you are most likely skipping an important step.

What you can do to avoid performance issues is to first pull the data into BigQuery which is Google’s data warehouse and unlike Looker Studio it’s actually designed to query and process big datasets so you won’t experience any performance issues.

In a second step you then push out the data to Looker Studio, which is designed to visualise data, but ideally you want to be working with finished tables here.

Think of it this way: Google is giving you two highly performant tools that integrate seamlessly. BigQuery to prepare and process datasets and Looker Studio to visualise the tables. Two use cases, two tools.

BigQuery also makes it super easy to push your data out to other data visualisation platforms like Tableau, Looker, Microsoft Power BI and more if you want to switch things up.

But of course there are other data warehouse tools as well so let’s go over why we recommend BigQuery for digital marketing agencies.

Why are Looker Studio Reports Slow?

The size and complexity of your datasets are the main reasons behind the slow reports in Google Looker Studio (formerly Data Studio).

Imagine you have a client waiting for a website audit and it takes you hours to produce a single report. Or, delaying a keyword analysis, which then leads to missed deadlines and dissatisfied clients. Slow reports can impact all the processes in your agency.

First of all, the data queried by the report’s visualisation tools could be so complicated that the algorithms can’t answer quickly.

However, the nature of the queries you write in Looker Studio could also be the reason for slow performance, as complex queries take more time to execute.

The output of Looker Studio reports also depends on the performance of the respective data set, according to Google.

Last but not least, the number of people using Looker Studio at the same time can also cause problems. This can make it take longer for data reports to load. All of these factors combined could negatively impact other work processes in the meantime.

7 Common Looker Studio Issues 

The above factors are said to affect the speed of producing data reports. However, there are a number of other issues that could affect how you work with Google Looker Studio (formerly Data Studio). The most common issues include:

  1. Data can’t be queried within the expected timeframe because it’s too complex
  2. The underlying data set is causing poor performance
  3. Slow performance occurs when setting a frequent “Data freshness” update period
  4. Crashes occur when trying to fetch a huge amount of data directly from the original source
  5. Slow performance occurs due to inefficient connectors
  6. Slow performance occurs because unnecessary data is being queried
  7. Slow performance caused by network latency issues

When you’re producing reports with data from platforms like Google Analytics or Google Ads, you’re usually querying many detailed columns of data that are not necessary for your reports. This slows down the output process significantly. Depending on the project you’re working on, consider reducing the number of elements that need to be queried from your charts.

On the other hand, each time a page of your Looker Studio loads, a query on your Data Source is performed automatically to retrieve the latest data. The frequency of performing a new query to portray the latest data is determined by “Data freshness”. The more often this happens, the more likely it is that your Google Looker Studio performance will slow down.

Other factors that slow down your reports include network latency and the complexity of data in your tables. We spoke about this above as well, and it’s an issue that influences the Looker Studio performance directly.

Finally, other factors, such as the use of the Google Sheets connector can have an effect on performance too. Since Google Sheets wasn’t designed to keep large amounts of data like BigQuery, it can experience performance issues when running queries on its tables.

How to Improve Google Looker Studio Performance

Data Looker Studio (formerly Data Studio), part of GCP (Google Cloud Platform), remains an excellent tool for producing reports and dashboards. But, what can you do when Google Looker Studio is slow? There are a few strategies to optimise it for better performance. Let’s check them out:

1. Use Google’s Extract Data Connector

Google made a connector for Looker Studio (formerly Data Studio) that lets users explore subsets of their data. This helps reduce the time it takes to load and improve performance. The widget allows you to extract specific data from your chosen Data Sources thanks to its filters.

The connector comes with its own limitations, though. The data you’ll extract isn’t updated live, but it’s refreshed at either monthly, weekly, or daily intervals. Also, Google’s Data Extract connector stores a limited amount of data, not more than 100 MB. But it’s perfect for daily reports and gives you much faster and more flexible insights into your data. Plus, it’s free.

2. Change Data Freshness Updates

Data Freshness controls how frequently the data on your first page should be refreshed. If your data isn’t updated often, you might be slowing down Looker Studio (formerly Data Studio) for no reason by asking the platform often to check for new data.

Even though not all sources allow you to modify this setting to extend intervals, it’s reasonable to modify it for those that do. You can count on your browser’s cache to give you a copy of the most recent page for your Looker Studio and make it load faster.

3. Wipe Your Clipboard Clean

Using the copy-paste feature while building your Looker Studio (formerly Data Studio) dashboard is normal. But, what you might not have thought about is that while copy-pasting objects around your reports or pages, the clipboard gets overloaded. All these objects are stored in the local storage of the application, and this can lead to slow Looker Studio performance.

The easy solution is to clean your clipboard in 3 simple steps:

  1. Open your browser and open your Looker Studio report.
  2. Click on Developer Tools > Application > Local Storage
  3. Find the URL “https://datastudio.google.com” and delete the object with the key “Clipboard”.

4. Use BigQuery and BI Engine

Using BigQuery to store your data is another way to save time when making reports quickly in Looker Studio (formerly Data Studio). With the help of the BigQuery BI Engine, you can run queries in sub-seconds and create reports and dashboards without compromising on data freshness or performance. Integrating BigQuery into your data infrastructure will do wonders.

What is BigQuery? BigQuery is a data warehouse that allows users to store data and query it with ease. With the BigQuery BI Engine, it takes agencies much less time to get data from Looker Studio.

What is GCP: Google Cloud Platform Explained

Google Cloud Platform is a compilation of cloud computing services offered by Google to the public. These services include computing, networking, big data processing, artificial intelligence and machine learning. Basically, you’re paying to access a virtual space on Google’s servers instead of setting up the infrastructure by yourself.

All of these services are said to run on the same cloud infrastructure as the majority of products offered by Google, such as YouTube, Gmail and Google Search. IT professionals, software developers and agencies can benefit from these services to manage their clients’ data, produce reports that analyse customer behaviour and outline solutions.

Certain features make Google Cloud Platform the best option for your services, such as:

  • High Security. Protecting your resources and assets through multi-level security options makes working on the platform safe.
  • Professional Support. Google is known for its staff of top-notch engineers. They help you maintain, install and run each service with ease.
  • High Bandwidth. The provided bandwidth allows users to handle and process high amounts of data.
  • Easy Access. Google offers access to GCP from anywhere users have a stable connection and makes scaling easier.

Google Cloud Platform can serve agencies of any size to work with their data. Thanks to BigQuery, its own data warehouse, it helps you securely load data into the platform and access it from anywhere.

What makes BigQuery the best data warehouse for agencies?

Full disclosure, we do not get paid by Google to recommend BigQuery, our data engineers and developers simply think this is the best tool in the market right now.

Performance: How’s this for speed, you can process 35 billion rows of data in 10 seconds. In other words, plenty! Good-bye performance issues with Looker Studio (formerly Data Studio) or other data visualisation platforms, your broadband speed will be the limiting factor when loading Looker Studio reports that draw on tables in BigQuery.

Integrations with your existing stack: Obviously agencies typically already work with the Google suite of tools like Looker Studio and Sheets and the integrations are seamless for all major data visualisation tools like Tableau, Looker, PowerBI. But there’s more, BigQuery also integrates with leading data pipeline tools like Funnel and even with purpose built two-way data pipelines like Shape ADI that allow you to push optimisation changes back to the popular ad networks (here’s a PPC Hero blog post with more on that).

Reliable: BigQuery runs on the Google Cloud Platform and it has an industry leading uptime SLA of 99.99% meaning your data is always safe, replicated and accessible 24/7. Again, if there is an issue your broadband speed is the most likely culprit. As the performance levels above indicate this is an enterprise level product and most agencies will be barely scratching the surface of what BigQuery is built for.

Price: Can be summed up as “bang for buck”. The performance you get out of BigQuery is unparalleled, but it’s surprisingly cheap. We offer a managed data warehouse service for agencies and process terabytes of data daily, yet the BigQuery costs are not a big cost factor. That being said, you are being charged for processing so very inefficient SQL queries that run a lot can cost you so it’s worth setting it up with an expert.

3 key elements for success with BigQuery

1. Technical expertise

Reality check, as with all advanced technologies it’s important not to underestimate the human factor. You’ll need data engineers with a good command of SQL and experience working with APIs and data pipelines to add more data sources and set up automated data flows.

The reality is that larger agencies can afford to have data engineers on payroll and find it easier to attract top talent. That’s why we founded Acuto to give agencies an edge that are on the smaller side but have clients that are no less ambitious and demanding!

To address this problem we offer a managed data warehouse service. We set up your BigQuery data warehouse and manage the data and the data flows for you and help you visualise the data, but you own everything.

2. Minimize maintenance and manual steps

You can connect any number of data sources so they are continuously pulling data using APIs and data pipelines and data integrity is key so you can trust your analysis and automations.

If you want to find out more about the trade-off between building your own API connections or using an out-of-the-box data pipeline you can find out more in this blog post comparing the cost of each option with a real-world scoping example.

Suffice it to say that updating and managing API connections and data pipelines takes a bit of maintenance and that’s included in our managed service so you can focus on working with your clients and trust in your data.

3. Enable your staff to work with the data

Finally, it’s key to prevent a scenario where your agency is overly reliant on a single member of staff so you’ll want to upskill a couple of team members and enable them to use BigQuery in combination with Looker Studio (formerly Data Studio).

SQL and Looker Studio training for account managers as part of our managed service to upskill key members of your team. It’s not rocket science and a great career development initiative for your staff as well!

Get Started with BigQuery with the Help of Acuto

As your agency scales up, you’ll notice that keeping up with the analysis of your Google Ads, Analytics, social media and other data sources is challenging and time-consuming.

If your Google Looker Studio (formerly Data Studio) isn’t running as smoothly as you expected, hand your processes over to us. At Acuto, we save you the trouble of having to wait for GDS reports to load slowly by consolidating all of your data into a BigQuery warehouse and letting you use customised dashboards to look through it. You can find out more in our eBook on Data Warehousing for Digital Marketing.

Acuto can help you bring all your data from different sources into a single source of truth like BigQuery. If you’re not sure what a data warehouse is, we’ll put it simply like this: it’s a digital space to store information with the intention of analysing it and turning it into useful insights.

Before getting on a call with our team, you can check out some of the case studies that attest to the results we’ve achieved for our clients. We can help you overcome your GDS performance issues once and for all, so let’s talk!

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