- Visualization, easy manipulation.
- Business leaders do not need-- nor do they want-- to write SQL to get the data and then visualize it.
- Graphs and spaces that can be shared with other users.
- Little pop overs or tips that appear as you hover mouse over an object.
- Filters that help to perform a deeper analysis
- Detailed data analysis
- It saves time when presenting works
- You get fast results
- Sometimes it takes to load the information
- The calculation field is advantageous, but not intuitive
- They should be able to accept many more databases
- For some people, it is usually very cumbersome
- Some of its functions are somewhat limited
- Easy to use (I was able to pick it up without too much training.)
- The presentation of the data is easy to interpret
- Getting frequent reports is easy to setup
- I would not necessarily say it is a con but it is a VAST tool so there might be features you may overlook
- Powerful dashboards with preset information.
- Easy to use for novices using the GUI but with advanced options for power users.
- Excellent support.
- Report caching can sometimes lag behind fairly significantly.
- Real time dashboards
- Guided Navigation, meaning you can bring up a dashboard or report, click on a cell and drill into the foundational data.
- Central Metadata Management. LookML metadata repository and language is a game changer.
- Better visualizations. 3d graphs and charts. A little more sex and sizzle.
- Adding a new data source and/or tables should be easier.
- Self service analytics
- Realtime reports and dashboards
- Scheduled reports and dashboards
- Embedded reporting
Not well suited: Statistical reporting
- Build it once - The reason why we have so many Looker users in TransferWise is because it is easy and fast to use. If tables have imported and modeled then everyone can quickly pick the fields and run they query.
- Simple - average users don't need to know SQL or have technical skills to use Looker.
- Automated reporting - Looker allows you to schedule emails for daily/weekly/monthly reports or send alerts if there are anomalies in data.
- Missing some more advanced visualization options, for example Trellis Line Graph
Review: "Looker's great if you're looking for a customizable solution for making data available to your team"
- Customizing your build -- Fields and measures can represent whatever you want it to.
- Transparency -- Everything is translated to SQL in real-time so you know what's going on in the background.
- Innovation -- There's a monthly update where new features are regularly released.
- User Management and Sharing Data could be a little easier. Your entire model needs to be built with user permissions in mind.
- It's not quite as plug 'n play as the alternatives, but that's okay.
- Visualizations could be improved for large amounts of data.
- Date reporting could be improved. Date, week, hour, month, etc are separate fields...you can't quickly shift between them in reporting/visualizations.
Business Analytics and higher management heavy rely on looker for the trend of sales, expenses and many other use cases.
- Helps to dynamically create filters.
- Easy user interface.
- Can connect to multiple datasources with ease.
- Representation of data in different formats : graphs, stats.
- Can share the looks to different teams and assign appropriate permissions for individual look.
- Can include multiple looks within one single dashboard.
- Creates cache data in the internal looker DB which consumes much space. Would be great if it has some garbage collection technique.
- 2 Factor authentication to user login will add more value to its security.
- Would be great to download the looks and send through an email.
Less suited when OLAP datasources are connected which increases the data retrieval time and loading to looker is slow.
- Incredibly advanced analytics tool that is even more capable if you learn how to use LookML which is Looker's custom programming language.
- Quick access to the raw data that is being visualized allows you to spot check for data integrity.
- My usage with Looker is limited because of our integration but, having seen their updates over time, the integrations with Slack, Salesforce, and other tools appear to greatly improve organizations' workflows.
- The time it takes to load data has been INCREDIBLY frustrating to our clients. How much of this is the fault of our developers, I don't know. What I do know is that it's the slowest time to see a visualization of any BI tool I've used. By far.
- There is A LOT of exerting setup required for custom dashboards. When adding our custom integration into the mix it's been nearly impossible to get things done.
- The calculation field can be incredibly useful but, again, requires technical expertise which not all of our users have.
- The granular permissions sets allow a large amount of control over what users can see and do.
- Views, models, and (optionally) dashboards are version-controlled and stored in a git repo of your choosing. This is indispensable for having peace of mind when performing large refactors.
- Incredible customer support offered conveniently via live chat within the app. Feature requests are always taken seriously and you can check back anytime to see where it is in the queue.
- Option to implement custom D3 visualizations.
- There could be more stock visualizations.
- The delineation between user-defined dashboards and LookML-defined dashboards is confusing and disjointed.
Looker Review: "Definitely recommend it to companies willing to invest resources to learn the tool."
It solves the problem of having multiple data sources. It makes report sharing very easy and data visualization instantaneous.
Looker makes everyone able to join tables without any knowledge of SQL.
- It is very easy to use by business users.
- They have an insanely good customer service. They reply within the minute to any question and sometimes spend hours debugging your crytpic SQL query even if it is not really their job to do so.
- The possibility of doing spreadsheet like operations within their UI on top of the result of a SQL query is very convenient from an analyst point of view.
- It misses something to properly manage dependencies in the data pipeline such as Luigi or Digdag.
- It can be very frustrating to use is your internet connection is so so.
- The visualisation could be improved.
- Their customer service is very good at helping to solve local problem. It took me a while to understand the big picture of the problem that this tool solves and I think they share half of the responsibility.
It is good if your data pipeline is not too complex. You can manage it from the LookML but as soon as it becomes too involve you need an alternative tool.
- Automation of reports.
- Easy drag and drop interface for most functionalities.
- Great variety of reporting options.
- Works well with large data in terms of performance.
- Setting up looker is quite tedious.
- It takes a considerable amount of time to get handy with the features on Looker .
- Need to configure database separately every time you want to connect a new database.
On the other hand, if you are looking for out-of-the-box trends or data patterns, Looker is not the right tool for you.
We have Looker connected to multiple product databases (PostgreSQL, MySQL) and to a data warehouse (Redshift).
Currently have over 50 internal active users of Looker.
- I believe that among BI tools, Looker provides the best balance between flexibility and configurability for the data team, ease of deployment and support for dev ops and great user experience for the end users – consumers of data.
- The data modeling layer, LookML proved to be extremely helpful for the Data team to define data models and abstract end users – data consumers – away from the complexity of underlying data sets.
- Documentation is clear, comprehensive and easy to find.
- Live chart support within the Looker interface is very helpful.
- Powerful permission management system allows to provide access to multiple data sets to a big number of users without the risk of compromising security.
- Very easy to deploy: is shipped as a standalone server Java application. Or even better: can be hosted by Looker company.
- Add the ability to perform joins across physically distributed databases
Greatly reduces the burden on engineers by allowing business users to perform analysis, build visualizations and put together dashboards themselves.
Currently cannot handle other data interfaces, such as Splunk.
- Interesting approach to data modelling (LookML), that highly increases re-usability, is version controlled and much easier to understand for people that are not fluent in SQL.
- Makes data discovery fun and easy.
- Collaboration features
- Visualisation capabilities clearly lack behind Tableau and some others.
- Allow for custom branding and CSS changes to fit a given corporate identity / design.
- Ability to blend data between different sources (i.e. two different connections / databases).
After all, the Looker UI is very simple to use, simpler than Excel, Tableau, Qlik etc.
For the most fancy visualisations or complex reports I'd rather choose other software as of now. However, becoming data-driven and using data to generate the best insights possible is key here - this is definitely not mainly achieved by visualisations (partly also because it requires more time / resources to do it right than most companies have available).
It's not entirely well suited for very small companies due to its pricing structure, but that applies to many others in the field as well, that also target mid sized to large companies.
Review: "Looker is an ideal data exploration tool with room to improve as an enterprise-level BI solution"
- Enables simple sharing of reports and data views throughout the ogranization.
- Allows for immediate on-demand querying of the data warehouse without direct access to the data warehouse of knowledge of SQL.
- Provides the ability to embed data modeling rules into the platform to make sure that "Revenue" (as an example) means the same thing to every person and is calculated with consistent logic every time.
- New user on-boarding requires some dedicated training. It's not an easy tool to pick up and use immediately.
- Visualization customizations are still a bit cryptic. Most end users can't figure out how to change a data series' color, for example. It's not intuitive.
- The ease of development actually makes for a potential nightmare down the road if too many people have developer privileges. There are a lot of potential issues over the longer term if you don't introduce adequate safeguards right at initial implementation.
Looker Review: "Robust and speedy BI tool for companies with internal data science and ETL resources to bring out its full potential."
- Blazingly fast for most queries as it sits on top of our Redshift instance.
- The ability to create user-defined filter presets through "Listeners" on dashboards that can be adjusted by the end user is really nice for making the product more accessible to non-technical business users.
- The interface is very fast, limited only by the complexity of the data/dimensions we're trying to work with.
- Support is AMAZING. Our live chat support team are always super friendly and go above and beyond to help us. I even had their CTO Lloyd respond to me once.
- Looker has come a long way in the brief time I've used it. However it is still challenging for non-technical business users to pick up and use, even with training. Dashboards are much more accessible once configured by a knowledgeable user, but the root of the issue is that our underlying data is complex and nuanced, and requires an internal technical resource who can own the data to properly inform and guide on the appropriate dimensions to use.
- Integrating Snowplow Analytics (Looker's recommended web analytics solution) has been a headache, despite how powerful the data is once it is working. But don't expect it to be a replacement for off-the-shelf web analytics tools like Google Analytics as Looker doesn't really have any of those reports "out of the box" since you need to model it all out yourself. It is nowhere near as intuitive to explore web data with Looker as it is with Google Analytics.
- The biggest challenge Looker highlighted for us was the issues with our own data and ETL. Not so much their fault, but at the end of the day, the data issues have made leveraging Looker to its full potential difficult. Having a dedicated Data Science and ETL engineer is pretty much necessary if your data has even minor complexity.
- Seamless integration with Amazon's Redshift.
- Visualization without additional software development.
- Painless user management and information segmentation.
- Separation of development and production data and source code. However, great strides have been made here.
Looker Review: "Great product and support but you need an internal owner with strong SQL and data model knowledge"
In addition, we may expose some data through the iFrame to Merchants to see their data and see how they may rank compared others in their area.
The business problems it addresses is that not everyone is competent in SQL and we have a lot of reporting needs so it helps to not rely on someone in Tech to do reports on demand.
- The fact that you create it once and can allow everyone else to use the same Looks. It allows for consistency in how data is reported and provides a layer of abstraction over the straight db tables
- Their client support has been very helpful, both the implementation specialists and the online chat
- Not necessarily a criticism of Looker but in the end, you really need one internal owner and someone who really understands the data model in order to build it properly in Looker. Here I tried initially to leverage Tech, but within tech we had knowledge of data model spreadout and it was also hard to take the devs away from bugs/features to help work on Looker. In the end it required me to hire someone on my own team with advanced knowledge of SQL to own Looker.
- As a company that is focused on local on demand delivery, the out of the box geo-mapping is very weak. We use carto-db now for mapping but it would have been nice to get this out of Looker. Ability to draw polygons and not just fixed points.
For more fancy graphing and reporting, Looker's options are pretty basic and not as pretty as some competitors.
Looker is strong when trying to do more advanced reporting with cohort analysis and the use of measures where you can input your own case/sql statements is very powerful.
Non-technical users can simply view saved queries (“Looks”), consume dashboards (collections of “Looks”), or go deeper and explore data on their own.
Technical users can use Looker’s modeling language, LookML, to set up data for exploration. Once a data model is set up in Looker, we don’t have to waste time manually writing SQL queries. “Looks” can be saved which store common queries and therefore reduce the chance of a person accidentally issuing an incorrect query at a later date.
- Allowing an analyst or organizational stake holder to explore data
- Generating canned reports or dashboards
- Emailing out reports on a regular basis
- LookML can be difficult to comprehend and I've gotten stuck at times when trying to issue queries that would be manageable to write with raw SQL
- Dashboards could allow more customization
- Pricing is high for small businesses
Who should have access to your data? If it's only a few analysts, a cheaper option may be a better bet. If you want to make data available across your organization, Looker is a great bet.
- Flexibility to control the data we expose to our internal team for reporting purposes
- Looker's data intake model doesn't require data storage on their servers
- Ease of building out the capabilities of the platform over time (vs. intensive upfront setup)
- Ability to send daily reports to any email address
- Ability quickly build adhoc queries
- Ability for users to create visualizations on the fly
- Ability to change the data that is made available to end-users
- Error checking could be better; would be nice to know that your code changes will break existing reports before you commit them
- Documentation tools could use some improvement
- The LookML language for creating data models is extremely intuitive. It blurs the line between the data integration aspect of BI and the visualization or self-service BI component.
- The dashboarding interface, from both a developer and end-user (UI) perspective, is beautifully modern.
- The data table can use some basic features, like the ability to subtotal and renaming and grouping of column headers. However, as Looker is primarily a visualization tool, one might consider some features superfluous.
- Looker connects directly to our databases in MySQL and hence there is no wait time for the data to be updated into another data warehouse.
- LookML is extremely powerful and easy to learn.
- Derived tables in Looker help in speeding up the reports.
- Chat support is extremely efficient as the support personnel are quite knowledgeable.
- The ability to connect to different data sources like Facebook and Mixpanel.
- Visualization can be made better.
- The Looker team is always keen to take feedback on the product and improve the user experience.
- Looker is customizable and integrates well with other platforms.
- Looker has tons of features that many don't know about it: they should figure out how to quickly introduce these to users that might find them useful.
Looker Scorecard Summary
Feature Scorecard Summary
Looker Support Options
|Free Version||Paid Version|
|Video Tutorials / Webinar|
Looker Technical Details
|Deployment Types:||On-premise, SaaS|
|Operating Systems:||Windows, Linux, Mac|
|Supported Countries:||United States, Canada, United Kingdom, Mexico, Germany, France, Australia, New Zealand, South Africa, Brazil|