- Louisa L.Data Analyst
- Data modeling capability in Looker is very powerful - Development mode and branch management is useful for testing codes without impacting production - Exploring from SQL runner result is very convenient for one-time ad hoc analysis - Custom fields - Using the shared link can show others what I am looking at with the exact filters and fields. This makes sharing very easy and doesn't require saving the view as a look. - Visualizations features are limited, and some features are not as flexible as other visualization tools such as Tableau - When I use derived query to create a view, the lookml doesn't automatically populate all fields from the query. I have to write them up one by one manually. - After I remove a table calculation if I want to add it back I have to rewrite the formula. I wish there's a way to hide and unhide the table calculation. - When there's a SQL error, the error message shows the error position but there is no way to find the position in the code. It takes long time to troubleshoot. - Sometimes referencing field names gets confusing. Looker is a great tool for analytics team that doesn't manage or have direct access to data warehouse. - When there are duplicated rows, using sum distinct in measure can avoid creating a false grand total. This is very convenient. - Being able to schedule and send csv directly to email is helpful for delivering data to internal users that don't have access to Looker or users that only want to look at data in Excel
- Jarrod S.Software QA Engineer
Looker is simply an extraordinary tool that allows us to work with our data comfortably, dynamically and strategically. One of the qualities I like most about this tool is its ability to integrate data from a wide range of sources, visualize them comfortably through attractive dashboards, and transform data activities, among others. It has performed impeccably in my organization; we use it in all our divisions. Data analysis and reporting are also strengths of this tool; it is an exceptional resource for daily use within my organization. One of the few disadvantages I have found with this tool is the lack of scalability when working with large amounts of data. On the other hand, it requires a large upfront expense; it comes with a high price tag. Looker has been an invaluable resource in our organization since its implementation. It has saved us a lot of time and effort by allowing us to manage and create dashboards to handle data from different sources in the same place. Moreover, it has excellent data analysis capabilities and has helped us to track activities from other divisions of our organization, manage our sales KPI and more. Today, it plays a significant role in Business Intelligence driven decision-making.
- Kian S.Full Stack Engineer
It has been quite influential, has had successful technical support, and has helped me focus significantly on its functions. So that you can present reports in the format you need, it offers pre-made templates. It's great to have access to such a high-quality tool, as all you have to do to put in a report is load the temple already developed template. Looker has been essential for evaluating business opportunities and job postings. It is fascinating, instructive and persuasive in equal parts. There have been no problems with the software, which is a great advantage given the importance and uniqueness of the product to the company. The company has well-received Looker; it is excellent software that allows for easy follow-up and quick, well-informed decisions. It facilitates communication and collaboration in developing a web-based business, a great application. Your company's marketing efforts will be helped, and consumers will widely accept it. You can use it to persuade potential customers to shell out a lot of money for your services, which is crucial.
- Verified User in Consumer GoodsMid-Market(51-1000 emp.)
Looker's visuals seem to be designed almost as if Google had a drag and drop product for your central reporting needs. The visuals are clean, and it is very easy to plop a number of visual representations on top of a query. Looker forces a company into two streams of thought: an analyst first culture and essentially married to Looker. Looker really thrives at young or small companies with no centralized reporting or analytics/data science teams. For the few people who know SQL, they can create these items called Dimensions and Measures which are essentially saved queries for qualitative and quantitative data. Instead of having someone write a query with many caveats in a where clause or in cast type conversions, these Dimensions and Measures are meant to save you the trouble of writing them and be ready to drag and drop into an editor for a quick dashboard. Unfortunately, this only useful for companies just getting out the gates with their data. If you have a column such as customerId, you cannot write SQL in looker to get an aggregate count of customer id's. You need to create a new dimension for it, and have it uploaded. If you have a count of customerIds restricted by some WHERE clause, then you will need to upload that new value as well. All the new measures and dimensions that you need have to be uploaded, which means that you will be responsible for learning Looker's LookML to upload new datapoints. As a company gets larger and as more departments are formed, your Looker repository will suffer from a lack of grooming. There will be a ton of dimensions and measures all over the place in different schemas and with different underlying queries that no one person will be able to explain. There will also be a massive amount of unused charts and visuals that were created ad-hoc and are relatively unused because they were spur-of-the-moment replacements for an Excel sheet. This also means that much of your business logic and data governance resides within the tool. If you were to divorce yourself from Looker, it would be a very messy process. Troubleshooting queries is already a challenge because you must look at the underlying code for a dimension or measure. Real trouble starts when Looker creates its own material views, which creates another layer of abstraction that you must then troubleshoot. This process of ad-hoc adding usable dimensions and measures in a tool through LookML and then troubleshooting the queries underneath the hood is not scaleable and no company with a centralized analytics function should allow it to happen. Invest in a tool which can intake an actual query through a database connection, and keep those queries thoroughly managed and groomed in a version control system. Create a dashboard environment in which a core group of people build an ecosystem of dashboards for specific requests and educate people on how to read and interpret them. Do not get into the business of enabling everyone in your company to have the ability to create their own ad-hoc visuals and set of dimensions and measures; you will truly regret the chaos that comes with it. Consider if you want a playground for people to create whatever dimensions, measures, and views that they want, or if you choose to proceed with more governance in your BI decision. Also note that you will have to learn LookML, which isn't difficult, but it's also like why? You are paying to have to learn a company's proprietary wrapper on SQL on top of hiring people proficient in SQL. If you do purchase Looker, I would highly consider centralizing the function of people who will create visuals and make things to address specific requests, and limit the views that Looker creates. Looker is used to provide visuals for YoY trends and to produce lists of customerIds that are passed from BI platforms to downstream tools such as CRM and advertising platforms in lieu of a query.
- Verified User in Information Technology and ServicesEnterprise(> 1000 emp.)
The thing I love about Looker is its functionality for storing data models. I often need to manipulate raw data before reporting on it or visualizing it in a dashboard, and Looker allows me to easily manipulate raw data directly from its source and store the data model so that it can be used again in the future. I have some trouble making visualizations exactly to my liking in Looker. It can handle basic charts such as line and bar graphs well, but when I want to create a complex visualization I often find myself longing for more customization. I would request a demo of Looker. If you contact them through their website they will let you set up a "POC" using your own data I turn raw data into insight using Looker. I create data models that can be shared with my team and create dashboards/visualizations from this data. Looker has allowed me to easily share this work across my team so that duplicated efforts are avoided.
- Verified User in E-LearningSmall-Business(50 or fewer emp.)
Looker is a very powerful tool. They have a clean UI and tons of functionality. I really like the reports and dashboards that you can set up with looker. We use looker to run reports for everything, sales, account management, users, engineering, etc so it can be used in all areas of the business. This may be just because of training or because I don't use the system enough but there is so much in there it can be difficult to get the exact report you are looking to pull. It's like a huge spreadhseet on steroids so if you're not using it daily it can take some time to get the data you need exact. seems to have all of the functionalities needed. Dashboards Tracking Reporting Insights Sales Dashboards Customer Success Dashboards Customer Reports Marketing
- Brice T.Banking
- James P.Marketing and Advertising
Overall Looker has been a powerful tool for our company to draw data insights from.
- Ernesto C.Financial Services
- Jo R.Financial Services
Displeased and frustrated.
- Anonymous ReviewerRetail
Terrible. I paid a high price point to have no support or any assistance whatsoever.
- Anonymous ReviewerComputer Software
- Verified User
Looker is much better at allowing users to interact with the data and "explore" to answer their "ad-hoc" questions. Tableau is better at pixel perfect visualizations. On balance, the interactivity is more important for our uses rather than "polished" visualizations.
Looker works very well against Amazon's Redshift. Some of the questions I asked during a reference check with another customer: * How much data are you storing in Redshift and querying with Looker?* How large is your Redshift cluster?* How is the performance of Looker against that cluster?* How "real time" is the data? Do you add data on an ongoing basis or have more of a "traditional" ETL model where you update your data warehouse once a day?* How large a team do you have working with Looker? How many people are authoring LookML versus just exploring the data?* What if anything were you using before Looker?* What's the one thing about Looker you know now that you wish you knew before making the decision?
Looker is very good at answering "ad-hoc" questions once the data model is defined. A simple example for instance is when we show the number of users added to the system, we start with just the basic number, Looker makes it easy to explore from that starting point and ask other questions like "how many of those users were added in the last X days", or "how many of those users are on android versus ios." Looker has a feature called "Persistent Derived Tables" (PDTs) which allows for highly analytical queries which may take a long time to execute against the raw data to be pre-computed and the results quickly available to end users. Looker provides a lot of flexibility in how the data model is defined, you can start simply with individual tables from your data warehouse, but you can also define parts of the model based on SQL queries. Beyond the technical aspects of the product, the Looker team has been very responsive to questions from my team, as well as to requests for new features (and the occasional discovered bug). The evaluation process was very straightforward, we were able to use Looker against our own data and even begin the development of the data model during the evaluation, it gave us a real sense of how we could use for real use cases. Looker has had multiple product updates in the few months we've been using the product, they seem to have a good steady cadence of adding new features, improving existing features and addressing existing shortcomings in each new release.
Looker needs some improvement in the visualization aspects of the product, they are very good at getting the data, but the choices for visualizing that data are somewhat limited, there are workarounds for some of the weaknesses but they tend to be labor intensive and fragile. For example, there is no way to define a custom color palette for use in our charts, we could define a set of colors on an individual graph and tie those colors to individual values, but it's more trouble than it's worth. Looker dashboards are an area where the needs often exceed the capabilities of the product. The dashboard layouts are done with a drag-and-drop interface which is not very responsive, and we often wind up with a dashboard that is "good enough" rather than what we were aiming for. This isn't a show stopper for us as the data is all present, but it can be frustrating. Looker does not provide a lot of feedback to users when it is processing data or even when there is a problem getting the data (possibly because of user/modeler error), you have to know to look for little spinning circles to see that it is still "thinking", or know that if a dashboard shows "No Data Available" that you have to dig deeper to find out what the actual problem is. Looker allows you to explore a large amount of data, this is both good and bad, it's great because you can probably find whatever you're looking for, but on the flip side, it's easy for users to get lost or overwhelmed with the number of choices they are being given.
- Michael ShostackHead of Online Advertising
I considered Looker along with RJ Metrics and Domo. The other platforms seemed to be offering much more of a service-focused offering, with fees that would likely scale quite high without certainty. Looker is focused on more of a product-driven approach and would be a good fit for companies with the data/analytics resources in-house to handle the ETL, integration, and ongoing management. If you don't really have those resources in-house, a solution like RJ Metrics, which provides a team of analysts to help manage your data and build out the actual models for you might be a better solution. At the other end of the spectrum of tools are things like Mixpanel and Kissmetrics. Both charge based on events, and frankly weren't robust enough for our needs with Looker in terms of how we wanted to leverage our data. Those solutions might be a better fit for companies without other web analytics solutions and who need something a bit better tooled out of the box for answering standard business questions.
Make sure you understand the data work required to make Looker shine. It is incredibly powerful, but ultimately only as useful as your data. Be prepared for an integration that likely will be ongoing forever as you add new tables, new dimensions, etc. This added perpetual resource cost is important to consider when looking at pricing as it has a decent chance of being more expensive than Looker itself. That said, Looker is a tool that enables teams to leverage their data, and we've found that data to be worth its weight in gold, so the value proposition was definitely a net positive.
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.
- Adam RhubergDirector of Analytics
Because Looker actually functions as a database querying tool, there's no need for building extensive ETL processes that require you to pre-configure every aggregation and dimensional cut you would ever want to do in your BI front-end, it avoids the long and expensive implementation process many of these other tools require. Another great benefit of this architecture is that the tool makes for rapid and flexible data exploration that doesn't require additional developer time - just because no one else has created a specific report before doesn't mean it can't be done quickly and easily by a business user with no knowledge of the underlying data structures. Looker is also a great value compared to some of these other tools.
If your organization relies on a team of analysts to write SQL every time a new data request is submitted with output expected in the form of Excel spreadsheets and charts, this tool can help avoid that process altogether and free up analysts to do more value-added work instead of just being a glorified back-end data pulling team. I don't think it would be very useful if a company is already using an enterprise-wide BI tool, especially one that might encompass both an ETL-like modeling layer and flexible visualization tools.
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.
- Christian LubaschManaging Director & Co-Founder
This question is very complex and depends on the concrete business needs. Looker plays very well when focus is on data discovery, ease-to-use and complex data modeling done straight in the tool. For a super complex dashboard, reports and in a huge enterprise environment with extreme dependencies, there are tools that are currently better suited. One of Looker's strength is to truly enable self-service BI, by giving almost everybody access to the system in a browser environment without the need of a thick client software and for a relatively low marginal price per user.
When focus is on understanding, playing, discovery and standard reporting needs, Looker is a very interesting tool to use. When done right, you can go up and down, back and forth in your data, link different "looks" or dashboards together and very interestingly, you can define what happens (i.e. is shown) when users drill down on a certain metric. With teams of analysts in place, a shared LookML, version controlled repository will help to keep data models right and in sync - no more 20 different versions of an Excel file or such. 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.
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).
- Verified User
I haven't used a very similar software to Looker. However, for the same means, I have extensively used Google Analytics. While Google Analytics is great for e-commerce, it has some issues for businesses where you need to input conversion from different sources, and that is something that Looker treats better. Moreover, Looker gives more freedom in leading with different dimensions. Google Analytics, on the other hand, has more pre-done dashboards that are interesting for websites, such simple cohort analysis and conversion attribution. This way, Looker doesn't substitute it completely.
While Looker has good usability, it still needs a strong presence of developers. If a colleague of a different company has a constant contact with the company's developers, I would recommend Looker. Otherwise, I would alert that for different kinds of analysis, the creation of different explore windows or auxiliary tables are needed and, therefore, the work of a DBA is needed.
It is easy to use for someone who has previous experience with Excel. This way, it doesn't take a long time to start working proficiently with Looker. The developers don't seem to take a long time to create a new explore window for a different kind of analysis that is needed. This way, it also seems to have a straightforward usability for them. The formulas it has for in-screen content are sufficient to see information such as accumulated sum and share between channels.
It would be interesting if it was possible to expand or collapse a field for further details in the same way it is done by a pivot table on Excel. The process to segment after clicking takes some time and it is not very usable as it demands the user to change windows. The charts could have more options such as adding a target line in a column chart and changing the bar color if it is under or over the line. It would be nice if inputing some kinds of data was possible to do for a non developer. Some data don't come from APIs and therefore need to be uploaded manually.
- Spencer WongVice President of Products
I chose looker because I like that you can always see the SQL being generated in case you run into an issue. I like that it supports very advanced reporting requirements provided we have internal resources who can build the required SQL I also like that Looker is a growing company so I expect their feature set to continue to advance faster than other competitors.
Ability to join across to separate data sources. We ended up having to do workarounds to get all data into one connection but it would have been useful to join across datasets which some other competitors allow. 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.
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.
- Daniel d.CIO
It's a great product for giving people in all departments of your company access to data and allow them to explore what your data can provide. Rather than having to always go to the Business Intelligence or Analytics team, people of any level can query data without any SQL knowledge or understanding and yield results that are either directly actionable or ask more questions that can be answered using Looker. We ran an initial 30 days trial with a view that only our analysts and BI team members would use it. By the end of the 30 days, everyone from the COO down to the account teams were using it. It's amazing. Furthermore, the vendor is smart, responsive and constantly improving the product, delivering a new version approximately every month. Their customer service is second-to-none and they are always happy to hear about new features that you need in the product. Very pleased overall with their service, strategy and plan to expand our use of them to our clients over the next few months.
Looker are still very heavily US based. They have just started an EU office, but support is still largely limited to US West Coast hours (although they seem to wake up at stupid o'clock to deal with some of our issues and plan to have support in the EU soon).
- Nicholas P.Director of Analytics
I could not be happier with Looker. My one hesitation in recommending it is that other tools seemed to be able to provide 80% of the value at 20% of the cost, but I've only demoed those tools and not actually used them so I'm not sure if they could actually deliver.
Tableau is an antiquated architecture (permanent license desktop app) and was going to be prohibitively expensive to roll out to the whole company. Having used it, I also had concerns about adoption since there's more of a learning curve.
Looker is incredibly easy to use for a casual user, which most of our users are. As soon as your email is activated, you have access to the product and new users need very little direction to start getting value out of it.
Relative to other BI tools, the advanced charting functionality is somewhat limited, but frankly that's not the main reason we bought Looker. Data scientists can use another tool of their choice, we have Looker for people who aren't data scientists.
- Jonathan P.Head of BI
Looker is a game changing tool insofar as it provides a 21st century approach to data tooling that massively amplifies how organisations can get access to, explore and power applications through data without making sacrifices from an accuracy perspective. Looker's company culture is fantastic and the focus on customer support really helps to extent the impact of the product itself.
Cloud-first architecture, faster development cycles, decentralised BI.
* LookML because it enables a scalable semantic layer wherein business rules can be defined in a single place and logic is code based thereby enabling version control, testing and auditing. * Extendability because the data platform focus enables businesses to serve data to applications and people through a single component * Customer experience focus
* It can be hard to navigate the huge volumes of content that users build on Looker and find the canonical/VIP products that are the foundation for any company
- Alan C.Analytics Developer
So many things are done right: - The simplicity of creating a meta schema using lookml, the learning curve is lightning fast - The flexibility of the system, making data available to intern customer has never been so easy - The support team is really knowledgeable and fast to answer - The roadmap is clear and moving forward as a great speed. Most missing features that we have in mind are usually in development when we ask - A really fun team, every meeting with looker is always a pleasure
Even if the team is moving fast and offering more and more features, they still lack on some of them. Mainly on dashboards. It went a long way since the early days and now I'd say that 95% of our needs are covered. On the other hand, their releases are so fast it's hard to keep track with all that was already implemented, the documentation is always a bit behind and searching for something precise on the discourse page can be a nightmare.
- John B.Senior Quantity Surveyor
Looker helps automate most periodic reports, reduce the report compilation time, and increase team effectiveness. Since it works on all phones and tablets, we can always use it for various analysis methods and functions, as it helps us continually find the best solutions.
Looker allows companies to create all business intelligence initiatives using comprehensive data sorting and analysis features, from ideation to visualization. The platform is professional, easy to use, and integrates with many other programs, making data entry and export a breeze. Looker enables non-technical managers to use reports and dashboards to explore, discover, and view data dynamically. It also stores all data in the cloud, allowing the members to work together at any time and get the best results.
Looker is a great program that efficiently produces the best analytics, and with proper training, all members will complete tasks as required.
- Darren O.Associate Strategist
Looker is a daily driver for me. We are helping to monitor how loyalty programs are performing for our clients and Looker really allows us to dig into any questions the client might have for us, as well as any questions we might come up with on our own. Very customizable in the metrics that can be created in here and easy to deploy. Would recommend.
I like creating dashboards for clients. Looker has many different visualization options to choose from and these dashboards can be sent out on a regular recurring basis for our clients.
I wish there was a way to take the data visualization and embed that into a Powerpoint presentation. Sure, we can do this with taking a screenshot, and then pasting into Powerpoint, but I'd love to be able to manipulate the size, font, etc to fit with what I'm trying to show in Powerpoint.