Google to Acquire Looker(cloud.google.com) |
Google to Acquire Looker(cloud.google.com) |
Unless they say put out a statement to commit their efforts into keeping it the way it is.
If that statement comes out, then shorten it to 1 year.
1. When Google acquired Alooma, they slowed down the development and dropped the support for other destinations such as Redshift and Hive. Even though Alooma is a data pipeline tool which makes it similar to Looker's case, the deal was $150M (compared to $2.6B) so I'm not sure the comparison makes sense.
2. Looker's sale team is so aggressive and their support team is great. In fact, that's why Looker became so big in the last few years. Google is not famous in terms of support.
3. Google is serious on BigQuery and I'm almost sure it will make Looker part of the Google Cloud. Since most of Looker customers are enterprise companies, Google will probably chase them to switch to BigQuery. On the other hand, Google has tons of BI tools (Data Studio, BigQuery BI Engine, etc.) so I'm not sure if Google makes Looker part of their analytics stack.
P.S: We're big fans of the LookML and we have developed a LookML alternative based on Jsonnet (https://jsonnet.org/) and the great data pipeline tool DBT. (https://github.com/fishtown-analytics/dbt). Here is how it looks like: https://github.com/rakam-io/segment-recipe/blob/master/event...
I work very closely with the Google Cloud team as a technology partner. With the recent hire of Thomas Kurian he has to make a big splash at Google while good will is forthcoming and I expect he will continue to authorize significant acquisitions to help build out their cloud to compete with Azure/AWS. The next piece of the puzzle will be an integration platform to help bring it all together.
When users connect to their Segment warehouse, we automatically install this recipe, they can fork our Segment recipe to build their models on top of our base recipe. Thanks to DBT, we support some advanced features such as incremental materialization and since our focus is on product data, we have embedded features such as funnel & retention & segmentation.
Our product is not feature-complete compared to Looker but we're implementing features & working on stability for the last few months. One of our team members is working on automatic LookML converter to Rakam Recipe so that we can have more coverage of LookML. We will definitely focus more on Looker use-cases after this acquisition. :) Would love to talk if anyone is interested! (email is in my bio)
I've found something like a LookML syntax backed by SQLAlchemy Core has allowed me to implement something like Looker (but tied to my own visualization stack)
That's probably the major reason of the acquisition.
1. “When will Google deprecate this feature/product/service?”
2. “None of Google’s acquisitions have done well”.
- It connects directly to your existing data warehouse. Most BI tools suck in your data into their datastore; Looker queries your database directly. If you wanted Looker to cache results for performance reasons, you could set up a dedicated schema in Redshift for example and only give write privileges to that one schema. But even the cached dataset was stored directly in your data warehouse.
- It is platform agnostic.
- LookML is backed by Git. By default, changes to your LookML definitions are pushed to a Looker-owned Github repo, but you can change this so that the repo is under your control as well.
- The support is pretty phenomenal.
There's that unsettled part in me that's wondering the over/under on two years before we get the next announcement: to give you better performance, it's tightly integrated with BigQuery; LookML is getting long in the tooth so we've gone ahead and created the views you'll need which are now accessible via the Google Analytics interface; you can go ahead and forward your concerns to /dev/null.
Google Cloud has an actually great track record of acquiring data-centric companies and democratizing them. While Data Studio is pretty amazing for a free tool, it has many shortcomings for serious use, and Looker fills all those holes nicely, while also providing the ability to formalize processes around data. Instead of mousing around Data Studio, Looker allows for all of its resources to be defined in its YAMLish syntax and maintained in source control.
For instance, this is the mantra about Borg, Omega, Kubernetes and GKE, or Blaze and Bazel, or etc.: well, we have an amazing thing, we copied a bit of it for you because you’re not us, but isn’t it great? Please send any feedback to our noreply@google.com autoresponder so we never have to leave the hive.
TBC, the world is better for the stuff Google externalized! CNCF wouldn’t be what it is otherwise. But the default attitude about it is the exact opposite of how enterprises get comfort in buying.
That describes most enterprise software, so it's not a unique challenge.
They don’t have a price on their website. Can anyone here provide what price points a medium-large company is looking(no pun intended) at?
I can talk a lot about it if anyone is interested.
We already have a few small business using Kato. They seem to enjoy that.
I'm also wondering how this affects pricing over the long-term and whether this becomes a replacement for Data Studio / commoditized analytics platform to make GCP more compelling?
Would it be in Google's interest to offer this for free (or at least with very little up front cost) in the interest of competing with AWS?
As a sidenote, Looker is a great platform. I evaluated 8 BI platforms late last year, and it really stood out (LookML, Git integration, awesome charting widgets, customization, etc).
Before you downvote me, these are not mine words but actually from a Looker engineer I asked to summarize the product. I don't know how accurate the quote is, but it stuck with me.
Also, congrats to the team I guess. Is an acquisition an accomplishment or just a decision?
I was once part of a project where we had certain users and payments we would flag as invalid (for fraud or other reasons). We wanted those records in our data warehouse for very specific reports, but never wanted anyone who was consuming reports to be able to include them in final counts. A global constraint in the LookML definition was a perfect answer. I could still run specific reports directly against Redshift, but there was no concern that a less technical manager would get confused.
I'm not associated with Looker in any way, but have really enjoyed working with their product. I was really hoping they'd stay on the path of independence and IPO, but I can't fault them for taking billions of dollars and calling it a day...
- https://training.looker.com/
- https://discourse.looker.com/- Its use of LookML provides a steep learning curve, yet provides a maintainable and reusable data modeling
- Looker's drill-down ability is decently powerful and easy to use once you are familiar with LookML.
- Looker does not have its own storage layer but instead relies on customer's data warehouses
- Looker, in essence, is a SQL query builder engine that converts business users' drag-and-drop inputs into SQL queries.
- Looker provides highly flexible and sophisticated access control and permission management, sacrificing simplicity for power.
- Looker has limited data preparation capabilities compared to other tools, delegating this task to its partners to provide these capabilities.
Unfortunate news for non-Looker users: Supposedly Alooma stopped supporting Redshift and Snowflake integrations following the acquisition, since those compete with BigQuery. If you're using Looker with Redshift or Snowflake you should be concerned.
Edit: By “stopped supporting” I meant they deprioritized it from the roadmap. I do not mean that they disabled the integration.
https://cloud.google.com/blog/products/data-analytics/announ...
Maybe you're personally noticing a difference in the amount of support before and after the acquisition?
http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=H...
If I sat in the governator’s office, I’d push for a commuter line from the South Bay to St Cruz. That would be so much more beneficial than the HSR to no-where we wasted 70 billion on.
After this acquisition: Superset (now preset.io) > Looker > Tableau > QlikView
Now that Looker is owned by a corporation, the innovation is going to diminish. The creative forces will cash out and move on. I think Superset is going to fill the void that these BI corporations leave behind.
Looker is one of the best upcoming BI platforms in the market. I like Looker. I even took Looker Certificate exam 3 years ago because I think Looker consultant will be valuable in the future. I would’ve already joined Looker to get their shares if they have office in Vancouver. :slightly_smiling_face:
LookML is a killer feature that solves a critical pain point in Enterprise BI and set Looker apart from the competitors, like Tableau and Periscope. This feature is no value to small startups and small company, but great feature for mid-size company, and critical to Large enterprise BI. Looker has a great potential to become the next leading Large Enterprise BI that successes Oracle OBIEE, MS PowerBI and SAP Business Object.
I think if Google is to take Looker and make it the next Enterprise BI and use it to get in the door of large Enterprise Customers, They are making a right strategy move. Google will bring a superior BI solution to its top-tier enterprise customers than IBM, Oracle, SAP. It plays well with Google’s strength in data offering, and BI the easier segment for Google to break through comparing to ERP, CRM and other enterprise solution segments.
If Google just wants part of Looker and absorb into the Google Machine, they are paying too high a price tag for it. (I don’t think that’s what Google are doing). I don’t think Google is buying it to eliminate competitor either, Google doesn’t have any products that offer similar features or target same market as Looker
> For customers and partners, it’s important to know that today’s announcement solidifies ours as well as Google Cloud’s commitment to multi-cloud. Looker customers can expect continuing support of all cloud databases like Amazon Redshift, Azure SQL, Snowflake, Oracle, Microsoft SQL Server, Teradata and more.
Time will tell - but I suspect we’ll see new features will be “bigquery first”
That said Azure has embedded PowerBI[1], AWS has embedded Quicksight[2], and Tableau even offers an embedded analytics service[3]. So you're far more likely to see it being rolled into GCP than being killed off outright. And all of their competitors offer the same flavor of "deeply integrated with our ecosystem but also connects to just about data store". So they'd actually lose feature parity with all of their main competitors if they butchered the embedded version.
[1] https://powerbi.microsoft.com/en-us/power-bi-embedded/
Google kills plenty of its consumer products if they don’t catch on in a big way (Reader, Google+); and it certainly “transitions” developer-targeted product/service startups into plain features (Firebase, WordLens, etc.) But this is neither—it’s BI software, for enterprise customers who build it deeply into their decision-making in the same way they build Google Analytics itself into their decision-making. These are not the people even Google wants to make mad. They’re precisely the people writing the checks which make up the majority of Google’s ad revenue!
Seriously, it seems like Looker is filling a specific hole in the Google Cloud offering.
And Android, Youtube, Doubleclick, etc.
Having architected and implemented BI infrastructures using all three, their pricing models all tend to converge to the same ballpark once you get to a standard, fully loaded and integrated installation. But they all have different levers for their pricing sheets, so unique usage models can sometimes take advantage of that to get a substantially better deal. Licensing models that are amenable to minimal/opportunistic usage exist for Tableau and PowerBI, but Looker very deliberately prices out that usage model.
Would love to collaborate, do you want to join our Zoom call https://gitlab.zoom.us/j/542273985? (Anyone else who wants to join in is welcome, the link is open)
We have launched a new open source project to work on the spec and collaborators are welcome
They recently killed "Works with Nest" in favour of an Assistant-backed API that doesn't currently implement what Google acknowledges to be the most popular features of "Works with Nest".
Google are more than willing to kill developer-oriented as consumer-oriented.
https://arstechnica.com/information-technology/2019/06/googl...
You mean Mode/Periscope/Superset/Metabase. I don't see anything that put's Kato near Tableau's offerings like Server, Prep etc.
I couldn't find anything about these features on my first pass, though I do now see the "Cleanup" bit on the "Data Visualization" page. I would have really liked to see more about features/tools/strengths and less nebulous marketing promises.
In Kato filters can be replaced anywhere. Plus we offer a ton of integration and data manipulation features. One of the biggest things that the client really liked over Superset is the ability to set up drilldowns where when you click on a bar chart on any graph you can see further details about that bar chart in a table, or any other graph. And this drilldown can go however many levels deep. We can link different reports from entirely different datasources with drilldown. I don't think that's available in any of those mentioned above and it completely changes the user experience.
https://www.forbes.com/sites/gordonkelly/2019/01/29/apple-io...
There is even an abandoned tunnel under the mountain that did this in the early 1900s!
Commuters would rejoice, SCZ would enjoy revitalization and integration into the Bay Area economy and holidaymakers would enjoy a nice leisurely trip to the beach by train --what a treat that would be!
[1]https://www.mercurynews.com/2018/01/05/abandoned-railroad-tu...
In any event, it would make way more sense than the Central Valley HSR which serves very little purpose. HWY 17 is not going to get wider, but there is pressure for more cars. I think this would serve the Coast very well. It would bring a lot more commerce there in the Summer months as well.
Financial Challenges - please. We have so much money in this state and it is just squandered on so many unneeded things (like the high speed rail line in the central valley).
I know Looker to really incentivize keeping their workforce local.
Except for the super distracting Ads that cover half the screen while you're using it every time your car comes to a stop, the sponsored landmark-Ads that put a huge marker over every Dunkin Donuts location while driving, etc.
(in my country, waze is the go to app for navigation for everyone)
We are a Looker customer and are concerned. It seems Google is one of the only companies that can buy a SAAS enterprise product that people are paying a lot of money for, and eventually drop enterprise customers for the free* model. Hundreds of millions or even low billions of revenue isn't interesting to them it seems.
When a Cloud company acquired a product/service for integration into their platform, I would hope that that includes transitioning to a Cloud friendly consumption based model. If that means including a free tier, or paying peanuts for low usage, that’s a good thing!
Finally, Google’s (GCP’s really) enterprise SaaS (mostly) acquisitions that I can think of are - StackDriver, Firebase, Apigee, Velostrata, Alooma and Cask. The venerable ones like StackDriver and Firebase are IMHO well integrated into the platform. The others are too relatively new? Curious which ones you had in mind that dropped enterprise customers?
And despite Google’s other product demises in the consumer space, GCP has had a decent track record thus far.
Market that stuff! Blog posts, list of features, service comparison - anything. For example, I know that Tableau offers in-memory storage that can help improve performance by bring data in locally and not hitting the original source. Kato mentions something about "10x performance improvement", but there's zero explanation how this is accomplished.
I think I'll start writing out the feature comparisons.