Looker Reviews

Looker is a great place to be a one-stop shop for daily (or real-time) info into the company's performance. We have a business intelligence database that syncs with production daily (over-night). So, this is a good tool to use first thing in the morning to see what happened yesterday. This tool needs high organizational alignment to do some finance specific use cases like scenario comparison or near term P&L modeling. It is best suited to output historical data, we've found it cumbersome to have our forecast models live (and calculate) within Looker.

Totally fitted to become the visualization tool for any type of company with a basic IT department to implement it. It also requires a BI function with a more business-like view to address proper business questions.

Looker is well-suited to visually display and scale data accessibility, and is a fantastic BI tool. The tool enables the end user to pull the data they are looking for and minimizes the need for an ad-hoc reporting team.

Looker is well suited for use as a BI tool and, in my opinion, is a sleeker and user-friendly alternative to Tableau. It is great for visualizing data with minimal setup and minimal SQL knowledge for analysts. If your analysts are tech savvy and are comfortable with SQL there might be cheaper alternatives to Looker.

Looker is excellent when there is a large team and when there is a lot of data required to be integrated. It does an excellent job in visualizations and creating charts. It is less appropriate for smaller teams as it is very expensive. If visualizations require too many customizations then Looker is slightly less appropriate. Overall, it provides great visualizations and drill-down analysis. Visualizations can be improved based on the current technology in the market.

Small to medium sized businesses are perfect for Looker.

Depending on organization size and the amount of data that you collect, that will strongly determine if this is appropriate for you. For less complex scenarios, I may suggest Excel/Google Sheets because you're probably already familiar with the tools. I only suggest it if you have more basic things to analyze.

When you've had a technical expert spend the significant time required to customize your Looker experience, then it could very well be one of the top contenders in its space. You are able to log in, see what you need immediately, dig deeper quickly, and integrate smoothly with your other tools. This one caveat, however, is a big one; and thus the lower score.

Looker is great for understanding performance data and making adjustments on the fly. It is great for truly "exploring" data.

Well suited:
- Self service analytics
- Realtime reports and dashboards
- Scheduled reports and dashboards
- Embedded reporting

Not well suited: Statistical reporting

Looker can be used for almost everything, but the solution might not be the most straightforward in more technical cases. With the latest upgrade to Looker 5 it is super simple and fast to build dashboards. Looker is great for automated reporting using scheduling feature. Looker is not so great for ad-hoc complex queries as you would need to build it in LookML first - however, this can be now solved using SQL runner built-in Looker and create temporary Explores

Looker is a great solution if making data available is a priority, or if flexibility/customization is really important. Dashboards and visualizations are good, but it's not Looker's strong suit. Looker is also not a tool for blending different datasets, however there's now a beta feature that takes a stab at this. The Looker UI is pretty intuitive from a user perspective.

Looker is well suited to showcase the company progress and trend visually where the data is noisy and huge. Multiple types of data visualization can be included in a single frame. Best in Dynamic dashboard creation and data projection in real time.
Less suited when OLAP datasources are connected which increases the data retrieval time and loading to looker is slow.

Looker is strongly recommended as a Business Intelligence tool when you wish to work with huge amounts of data. Moreover, Looker capitalizes on the power of your own database, and does not have its own analytics engine. This cuts down cost and makes it more performance-oriented.

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.

Looker is best for environments in which users are empowered to perform some of their own exploration and analysis. Although it is an excellent dashboard tool in its own right, its potential isn’t realized until data models specific to each line of business are created and users understand how to explore their own data.

Looker is good if you want one source of truth and have business users willing to spend some time learning its capabilities.

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.

Very well suited for modeling and exposing data of any data source with a SQL interface including but not limited to Hive and Spark.

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.

Th reason why I did not rate it 9 points is because of the price but I rated it 8 because if its use. Users can discover details behind the picture because all dashboards and queries can be drilled into. Looker offers a free trial but if a small business team decided to buy the software, sometimes they can't afford that.

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.

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.

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.

Well suited for teams that wish to focus on software development and not BI development. Looker has the cloud architecture that we believe all next-gen BI platforms must have. We chose them because they seemed to have the right thesis and the ability to deliver continuous improvements. We've not been disappointed.

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.

Do you have a central SQL database that stores all your data? If not, the tool won't apply.
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.