The sale of Looker for $2.6 billion to Google and Tableau for $15 billion to Salesforce early this year is a clear indication of the power of data visualization in Enterprises and the need of packaged Cloud Business Intelligence (BI) services.
It is a recognition that most people are often better able to process large amounts of data visually than in other ways, and that the insights from those visuals are worth serious money.
The competition in Enterprise Business Intelligence Tools just keeps evolving and that actually makes life difficult for Enterprise decision-makers in finalizing a tool.
Choosing the Most Optimum BI Tool for your Organization:
Having used Domo, Looker and Tableau – all three of which are quite popular and prevalent in the Enterprise BI space, I’m going to compare all of them and present a simple framework to decide which tool to go with for your business.
To decide upon a tool, we need to understand the business situation and all the factors/parameters associated with it
Here are some questions you need to ask yourself and list the answers down.
- What are all data sources that you have?
- What is the approximate size and level of data currently and how is it projected to grow?
- Who needs to make decisions and find insights based off your data? Your end-users?
- How large is your Data team currently and entire employee workforce?
- What is your timeline on creating dashboards/building insights etc?
- What’s your estimated budget for Data tools?
I’ve listed down in detail how to answer and define these questions for your organizations below and then provided a basic framework to make a decision based on it.
Data Sources & Data Connectors:
If they are not on the list, there is no connector supported from Tableau and Domo respectively. But there can always be workarounds created by developers, data analysts and our team also help in that. Eg: We’ve created multiple custom connectors for Domo and various workarounds by Databases, google sheets, airtable, scripting, etc
That was about Tableau vs Domo – But what about Looker?
They have no connectors and they are proud of it!
In a blog post, Looker’s chief data evangelist clearly explained why Looker has no connectors and why all other tools would eventually fail if the data is very large and there are no clearly defined formulae and wrong analytics leading to incorrect decisions, etc.
Daniel is quite correct and for big data projects and if the data applications have really big schemas like Salesforce, Infusionsoft – bringing them all together using data dumps and joining and creating formulae is a huge task with high probabilities of error. The LookML and model – view approach really solves that for big data enterprise customers.
Data Size/level & it’s Projected Growth:
All three tools are very good at handling all types of data sizes and levels here.
However, the way you bring data inside each tool is quite different as explained in the Data connectors section above.
Your data team that will be using the tool has to decide how they want to create the backend architecture and schemas (tables diagram) for the most effective manner with a long term perspective.
The best backend architecture design can be created by Looker with their LookML and View-Model architecture they have, whereas Tableau and Domo have a more connector based and dataflows based approach where you have to work on individual datasets initially and then create a backend based off it.
The experience of end-users for Domo vs Looker is quite similar as they are completely online and tools from the frontend, viewing and end-user perspective.
They both have cards and looks (individual visualizations) respectively that can be shared quickly with a link with anyone who has the rights and access. These cards/looks can be brought together to create an entire dashboard that can also be shared in the same manner.
The end-users and the data team both are creating and working on the same interface here
For Tableau, it’s slightly different as the creation happens on a Tableau desktop (in general) and then sharing can be done either using a Tableau reader (desktop – based software needed) or online by Tableau online / Tableau server. In general, the best practices are to share an entire dashboard here with all visualizations put together as it needs to be published and refreshed accordingly.
For a complete cloud and seamless experience in one single place on the web, Domo & Looker work much better with clean UI & UX.
Tableau is decent also with your online & server dashboards and views, but its main power is best suited in Desktop versions as it was built in the early days.
I’ve listed all the Dashboard and Business intelligence tools I’ve worked with in detail too from an Analyst and end-user perspective.
Your Data Team
This is important to understand so you can plan who will be doing all the work and what’s the added expense of time and money after you finalize the tool. You must account for the resource costs associated with setting up and maintaining these enterprise tools.
We as a team also help in all of the tools and would be happy to help
For Looker, ideally, you need a small but dedicated team that can help create the entire Model-View setup and really know LookML (their new SQL version)
For Domo, there are a good number of options and it’s an easy tool to learn for anyone who has had experience with basic BI tools. They will need connectors knowledge and best practices for storing all the data in Domo too as it acts as a data warehouse also along with Visualizations and Dashboarding features.
For Tableau, there are a lot of options as it’s one of the oldest and most widely used BI tools and thus has an entire ecosystem of users, so you can hire good talent surrounding it and get all the help you need.
To decide your timelines, we should look at two aspects: the Backend and Frontend of Data visualization and business intelligence (BI) tools. The backend aspect has to be designed and prepared first to actually do any frontend work.
For the frontend, all the tools are quite similar where it’s basic drag and drop of variables from the backend data. The only point to mention is that while Domo & Tableau will only give you the options to create a visualization from any single dataset or derived dataset, Looker will give you an entire “Explore” feature to pick out any variable from the same
(Explores can have multiple views and derived tables, which is where you can get a huge number of variables inter-connected for large schemas by writing LookML in your data models)
In Domo vs Tableau, both are really good at just plug and play dashboards from your data anywhere using their quick connectors. Looker, on the other hand, needs backend and LookML work initially and explores written out and only then can be used.
However, for complex formulae and dashboards built out of product data that have large schemas i.e. many data tables (eg: salesforce, infusionsoft) – it will take time to bring all the data centralized and then convert them to something meaningful in both the tools above.
For Domo, you will have to use in-built Magic ETL or SQL dataflows to create the dataflows and ETL aspects such that you have the right backend.
Your Total Cost of Ownership of Modern BI Tools:
Whenever looking at these modern BI Tools, you need to look at your total cost of running, maintaining, building, deploying and sharing all the aspects of these tools and not just the “pricing” shown on a product pricing page.
Here are some parts of total pricing and time you should keep in mind:
- Exploration & Creation – Setting up, Using the BI tool and building visualizations and dashboards – your data & IT team that does this and the cost involved here is important to consider
- Viewing & Consumption – Deployment and sharing of the above with business stakeholders
- Adoption & Impact – Cost & Time for organization-wide training & adoption – A BI platform is only impactful if employees and leaders use it regularly
Tableau apparently is the only option that provides the pricing publicly and most clearly due to it’s the longest existence and also confusion among various types of solutions it offers.
They have moved completely to subscription-based pricing just like your Netflix or gym memberships and it’s now very easy to add 1 new tableau desktop license for a team member or 150 new server licenses for your global level teams both.
Looking at the subscription pricing, It ranges from 12$ for the viewer (min 100 viewers) to 70$ for creators per user per year with some more caveats for a Team/organization that becomes 840$ + taxes per creator for the entire year that has to be paid at the start.
Domo can be tried out free with some data source and connector restrictions at any time, which is great and highly recommended.
As per a third party report and based on their last updated on Sep 2018, they have four plans named Free, Standard, Professional & Enterprise plans with separate pricing for all of them.
Free plan just allows 5 users and up to 5 mil rows of data with a limit on the type of data sources that can be used so that you can test the entire platform quickly with some parts of your tech stack.
For others, the price ranges from ~990$ per user per year for standard to ~2,000$ in professional & ~3,000$ in the Enterprise plans respectively.
According to another third party site, Looker offers subscription pricing that ranges from $3,000 – $5,000 per month for 10 users, and $50 per month for each additional user with a free trial also available
For exact pricing for Domo vs Looker, you can get a customized quote from their sales teams.
An Enterprise Framework to decide a Business Intelligence Tool
Based on all the questions, answers and discussions, here’s a final diagram you can use quickly for taking a final call on the best BI tool for your business and your specific requirements (not on someone else’s agenda)
Your final decision can be weighed on the following factors:
The Enterprise BI space is an ongoing evolving one where there are always new tools, new ideas, and new developments – so make sure you are updated with what’s going on in the field at the actual scenario of choosing.
If you have any further questions, feel free to contact us or comment below and our team would be happy to help you out in choosing your BI Tool and any associated help needed.