First Looker and Tableau, Which Data Visualization Companies Could Be Acquired Next?

In a past life, as CEO of Mattermark, I spent a lot of time building lists like this with our customers — investors, M&A deal-makers, and other professionals looking to understand a space. On the heels of Google acquiring Looker last week and Salesforce announcing their acquisition of Tableau today, I’m looking through my competitive landscape with fresh eyes to contemplate potential deals on the horizon.

There are many reasons for M&A, but for the purpose of this post I’ll focus on situations where companies are not (at least visibly) in distress. The deals above combine the two things established companies want most 1) high quality (e.g. locked in, high $ per customer) revenue to fuel further growth and stock price appreciation 2) differentiating technology innovations that can be bought and leveraged faster than they can be build in house.

We’ve also included a long list of acquired companies in this space, which we believe has been quietly consolidating for year past year or two.

This is a collaborative effort, and feedback is welcome. If you’d like to contribute, please leave your comments here or tweet to us @meltanodata.

Press inquiries regarding this story can be directed to press@gitlab.com

Salesforce is Acquiring Tableau for $15.7B

It seems the consolidation train is chugging along nicely. This morning, it was announced that Salesforce* is acquiring business intelligence and data analytics company Tableau for $15.7B, a healthy premium on the company’s $10.8B market cap. While this is an impressive outcome for the 16 year old company, it will be interesting to see what it could mean for their customers and the broader market. Some open questions this morning:

Last week, we explored what Looker’s acquisition by Google could mean for the free open source data analytics movement and ultimately kicked off a new open source project with collaborators at Rakam to develop a spec defining an alternative to LookML.

Meltano is still in the early days, and seeing major transactions like these make us very bullish that this is a space where there is a great deal of untapped opportunity in terms of product offering, business mode, and for us — acquiring a unique customer base. Because we are able to offer a free open source alternative, much smaller companies can rely on Meltano for their business data dashboards without locking themselves into expensive contracts. As consolidation continues, it will be interesting to see how the “low end” disruptive part of the market we are serving evolves.

Interested in getting more involved with Meltano’s mission to bring data analytics tools to everyone? Feel free to leave a comment on this post, Tweet to us @meltanodata or jump into our public Slack channel. You can also reach the whole team anytime with an email to hello@meltano.com

*Disclosure: Meltano’s GM, Danielle Morrill, is a shareholder in Salesforce.

Rakam is Collaborating with Meltano to Define an Open Source Alternative to LookML

Following this morning’s announcement that Google is acquiring Looker, there has been quite a bit of discussion about the future of the open source data analytics space. Seth Rosen at Hashpath writes:

Meanwhile, in the open source data analytics space, there is a similar technological consolidation and integration happening. Specifically, the Meltano project out of GitLab is stitching together fragmented open-source data analytics projects into a single end-to-end platform. Meltano describes itself as “an open source convention-over-configuration product for the whole data lifecycle, all the way from loading data to analyzing it.” Based on the success that GitLab has had with other projects, we predict that Meltano could eventually give the big, proprietary platforms a run for their money.

Seth Rose, HashPath

LookML is a significant part of why Looker was acquired, and we believe there is a path forward to build an open source alternative that helps users define re-usable business logic without having to know how to write complex queries. While Looker is proprietary, the idea of having a portable way to describe the data needed to arrive at a particular insight or dashboard is a general problem. With Looker now part of GCP, this is the right time to work together on an open standard used by multiple companies.

Thank you to Burak and Ilker from Rakam for joining us on our open Zoom call to discuss a path forward today. We connected following the discussion of Looker’s acquisition of Google this morning, and invite anyone else who would like to participate to join us!

The new project can be found at https://gitlab.com/meltano/model-specs

What We Want to Do

Fundamentally, this project needs to deliver on three key steps:

  • Define a Model
  • Compile the Model
  • Generate SQL
YOLO MICAEL

Next Steps

In our open call today, we defined some next steps:

  • Define a new specification for representing data models
  • Define what data models encompass in this context
  • Think through how to describe core concepts like aggregates, dimensions, measurements, metrics, et al.

We invite those in the data modeling space to help, so that everyone can contribute on models rather than creating their own isolated solutions.

Join the project here: https://gitlab.com/meltano/model-specs


About Rakam

Rakam is a product analytics tool that lets companies analyze their customer event data coming from different sources such as Android, iOS and Web. We help companies to create their summary tables with DBT (the event data volume can be up to hundreds of billions!) and analyze their user behavior with features such as funnel, retention, and segmentation in a similar way to Looker.


LIVE: Join Us to Discuss Building an Open Source Alternative to LookML

This morning it was announced that Looker has been acquired by Google for $2.6B. This kicked off a discussion on Hacker News around open source alternatives. We are grateful to Burak Emre Kabakcı of Rakam.io for engaging with us to explore this more deeply in an open Zoom call, and we invite you to join us as we leave the channel open throughout the day to connect with other potential collaborators.

[CALL HAS NOW ENDED]

Check out the results of our conversation and plans for next steps in collaboration with the team at Rakam.

Looker Acquired by Google for $2.6B to Offer End-to-End Business Intelligence Solution

This morning we were impressed to see that Looker was acquired by Google for $2.6 Billion dollars, a massively successful outcome for a company that was probably on track to go public in the next year or two.

There are many tools available in the data visualization space, and Looker offers many benefits to users but what’s impressed us most are two things 1) usability 2) the LookML approach to describing business rules around data sets, so that non-technical people can explore information without needing to know how to write extremely complex queries.

While many Looker end users and the press will focus on Looker’s simple, powerful UI (and it is well deserved!) at Meltano we’ve been iterating on the guts of an open source alternative and have come to appreciate the power and challenges of becoming the glue for every step from data ingestion to dashboarding. Google’s data ingestion plus Looker’s visualization layer combined offer a 1+1=3 outcome, and we are also striving to provide something that is integrated end-to-end.

We’re exploring ideas for how to build an open source alternative to LookML (right now we have Meltano Model, but we would love to integrate a better 3rd party open source option), and would love to connect with potential collaborators.

There are many more open questions:

  • will Google limit Looker to BigQuery, or at least get the newest features first? (they say they won’t)
  • will Google limit which clouds Looker can be run on?
  • will Looker become more accessible to smaller companies?
  • will integration with GCP slow innovation (like what happened with Alooma)?
  • will it get shut down altogether?

Interested? Feel free to leave a comment on this post, Tweet to us @meltanodata or jump into our public Slack channel. You can also reach the whole team anytime with an email to hello@meltano.com

Meltano 0.26 Released

If this is your first time exploring Meltano for your company’s data pipeline management, you can follow our installation guide and quickstart guide to get going in minutes!

New

Changes

  • #657 Update Analyze page to have single purpose views

Fixes

  • #645 Fixed confusion around Loader Settings and Analytics DB Connector Settings
  • #580 Fixed project_compiler so the Analyze page can properly display custom topics
  • #658 Fixed the Analyze page when no models are present
  • #603 Fix an issue where meltano select would incorrectly report properties as excluded
  • #603 Fix an issue where meltano select incorrectly flatten nested properties
  • #553 Fix an issue where running meltano select --list for the first time would incorrectly report properties

Instructions for upgrading to the most current version of Meltano are available in our documentation.

To see the full history of improvements to Meltano, please review our CHANGELOG

Meltano 0.25 Released

We’re back! After a couple weeks off for our company summit GitLab Contribute and some vacations, the latest version of Meltano is now live.

If this is your first time exploring Meltano for your company’s data pipeline management, you can follow our installation guide and starter tutorial to get going in minutes!

New

  • #586 meltano ui now automatically start Airflow if installed; Airflow UI available at Orchestration.
  • #592 Added baseline UX feedback via toast for uncaught API response errors with a link to “Submit Bug”
  • #642 Improved UX during extractor plugin installation so settings can be configured during installation as opposed to waiting for the (typically lengthy) install to complete
  • !647 Added preloader for occasional lengthy extractor loading and added feedback for lengthy entities loading
  • #645 Added an Analyze landing page to facilitate future sub-UIs including the Analyze database settings; Added proper Loader Settings UI.

Fixes

  • #645 Fixed confusion around Loader Settings and Analyze database settings

Instructions for upgrading to the most current version of Meltano are available in our documentation.

To see the full history of improvements to Meltano, please review our CHANGELOG

Meltano Demo Day 2019-05-03

Each week, the Meltano team shares our most recent progress so you can see what’s coming next. You can read a brief text recap below.

In last week’s demo day:

  • Derek provides an update to the ELT setup process, walking through how to select data sources, and manage settings for API keys and entity selection (which data points you want to import).
  • Micael shares the latest Airflow UI integration directly inside of Meltano.
  • Ben shares improvements to the documentation, specifically for configuring your environment, working with role based access control (RBAC) – an experimental feature which is feature flagged off by default -, and deploying Meltano to Amazon Web Services on ECS with Docker.