My Thoughts on Google Cloud Next 2022
Last week, Google Cloud had a lot of different product announcements at Next 2022. The announcements spanned the gamut of product groups, and there’s an incredible amount of material to chew through. I’ve made a playlist of the sessions that I’ve been interested in, and they’re still worth watching, but I also did want to spend some time and talk a bit about some of the data related announcements that caught my attention.
BigExpansions (BigQuery Updates)
Unstructured Data
Recently, there have been feature additions that were trying to include more data that isn’t tabular. The introduction of the native JSON type back in January, and Google’s constant improvements to BigQuery GIS are examples of those. This time, Google has announced unstructured data support. Think about being able to leverage VertexAI and BigQuery to create object tables that let you query across things like images, audio files, and video files. Add in BigQuery ML into the mix, and the possibilities start to get really interesting. Google has published their customer demo around this, and I’m excited to see what other use cases come out.
Serverless Spark
This is a took that came out earlier in the year, and is pretty key in expanding Google Cloud’s Spark capabilities, which includes rolling out clusters on Compute Engine, and Dataproc. Dataproc Serverless allows you to submit workloads without having to manage your own cluster, which fits in line with the broader vision of empowering users to focus on the workload itself, by spending less time on managing the infrastructure. The really next thing that was announced is that this is now integrated with BigQuery, so you’re not having to work with multiple platforms for computing on the same piece of data. Go here for more information on Serverless Spark through BigQuery, and go here for more information about the new feature allowing you to create BigQuery Stored Procedures for Spark.
Looker Studio Premium
One of the announcements you may have seen is that Data Studio has been re-branded as Looker Studio. As part of an effort to standardize the portfolio, Data Studio has been brought under the Looker umbrella. As a huge fan of Data Studio, I’m pretty happy this happened because it starts to align the branding, helps customers understand it’s now part of a single platform for analytics, and most importantly, this introduces Looker Studio Pro. While there are technical integrations that are introduced and in the works, one of the key things that the Pro version brings is support. This is a key aspect that enterprise customers need in order to adopt a product, so having Looker Studio Pro be supported by Google Cloud Customer Care removes a key barrier.
Carbon Footprint
The one that I’ve personally been looking forward to the most is the general availability announcement of the Carbon Footprint tool.
This is a tool that I’ve been a longtime fan of, and it’s exciting to see this launch come to fruition. I’m definitely a little biased, so don’t just take my word for it, others also agree that it’s good. This is important as organizations continue to set carbon reduction goals, and sustainability topics gain greater mind-share, so having both this dashboard and the ability to analyze this data historically within BigQuery allows users to balance their engineering and platform needs with sustainability needs as well. Add this in with possible regulatory requirements in the United States and existing requirements in the European Union, and the importance of tools like this becomes greater.
Bonus Points, Earth Engine with BigQuery
While it’s not a product launch announcement, I did want to add one more thing. Google Earth Engine has always captured my attention, especially with regards to use cases in sustainability. Leveraging the vector data processing capabilities of BigQuery with it is something that’s always sought after, and Google engineers have published an example of using Cloud Functions to integrate the two. It’s really interesting, and worth a read if you work on this kind of data!
So Much More!
Again, there is a huge amount of products and features that dropped at Next 2022. For analytics I haven’t even touched upon all the cool things happening with BigLake, Dataplex, the VertexAI platform, and AlloyDB, there’s just so much that happened, but I did want to take a few minutes and add some of my thoughts around a few things that caught my eye. I’d love to hear what announcements you were interested in, and what cool use cases you’re looking to solve, I’m always looking to chat about new ways to use Google Cloud!
