Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.
N/A
Looker Studio
Score 8.2 out of 10
N/A
Looker Studio is a data visualization platform that transforms data into meaningful presentations and dashboards with customized reporting tools.
Senior Manager, Digital Advertising & E-Commerce Team
Chose Looker
Google Looker Studio is an online tool for converting data into customizable, informative reports and dashboards. It is a free tool that turns performance data into informative, easy-to-read, easy-to-share, and fully customizable dashboards & reports. Google Looker Studio turns …
Looker works and exists in the Google ecosystem. If you are a Google Cloud Platform user, Looker is a no brainer. There is also Looker Studio, the small (free) brother with less features which is basically a report only viewer/creator. The reason we choose Looker is because can …
The dev/production environment distinction is constructive. Before, in Data Studio, all changes had to be made, which was very inefficient and risky as far as version control goes. Having a more centralized and organized space for all our data visualization is more helpful than …
Looker provides really excellent customer service in comparison to other similar products. The sharing aspect of Looker is also a big plus, which allows multiple users to access the data at the same time. We have also found it to stand out among competitors with its dashboard …
Unfortunately, I was not in charge of the decision to select Looker as it was before my time. I can see why the decision was made as I do see the potential. We have felt the need to supplement Looker with another free tool and, if our integrations weren't so deep and our …
The free version of Looker Studio is still better than the leading enterprise-embedded BI tools, despite its weaknesses. The leading embedded BI platforms have terrible visualizations that can be spotted a mile away. They are also primarily locked to a grid, making it very hard …
Google Data Studio is widely available and accessible, can be shared easily, and it only takes 20-30 min to build a rudimentary dashboard. It has very little setup and does not rely on internal data architecture and development. For later development purposes, Tableau, Power …
This is starting to feel redundant but we just Google Data Studio to supplement the areas that are lacking in our other BI tools. Because it's free it's an easy decision to make. It does not allow us the deep diving that we get with others but is often simpler to use, more …
Quick dashboards from Google Sheets - Easier to do the graphs than in Google Sheets - Operational dashboards to be used in the day-to-day work - It is good both for retrospective data and to do a pulse check of the current status - Better for not giant amounts of data and not multiple data sources. - If you need a lot of graphs to be displayed on the same page, it can be a bit glitchy during configuration (then the use works fine).
Does great at open canvas editing and letting you fully customize without the need for a grid. It is democratizing self-service no-code analytics. You do not need to be a data or analytics engineer to get started, and you can go very far based on how intuitive and straightforward the UI is. Some of the biggest challenges with Looker Studio relate to user management/security, embedding options, and issue support. For a long time, every user needed to have a Gmail to invite them to view a dashboard via login, not sure if that has been improved yet. You can let any user view without logging in, but that is not always recommended due to security reasons. In terms of embedding, you can only iframe dashboards. More sophisticated BI tools let you embed elements via API or Javascript. Iframing dashboards also make drill downs and dashboard to dashboard navigation tricky/near impossible. There is also no ability to contact Google for support when bugs or outages happen. They point everyone to the Data Studio community. There is some ability to get in contact with Google if you have an enterprise-level contract with Google Cloud, but the path for support is very ad hoc and not always fruitful.
Filtering - you can filter across different dimensions and metrics to get a more specific "cut" of data
Refreshing - data automatically ingests into Looker which allows reports to be updated and backfilled in real time
Conditional Reporting - you can leverage Looker's reporting features to flag when a given metric or KPI falls below or above a specified threshold. For example, if you had a daily sales benchmark in a SAAS organization, you could use Looker to flag whenever daily sales falls above or below the benchmark
Looker is less graphical or pictorial which makes it less attractive
Consumes a lot of memory when there are multiple rows and columns, impacts performance too
At times when we download huge chunks of raw data from Looker dashbords, the time taken to prepare the file is enormous - The user fails to understand if Looker has frozen or if the data is getting prepared in the background for downloading. In turn, user ends up triggering multiple downloads
We've been very happy with Looker so far, and all teams in the organization are starting to see its value, and use it on a frequent basis. It has quickly become our accessible "source of truth" for all data/metrics.
It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Google Data Studio has a clean interface that follows a lot of UX best practices. It is fairly easy to pick up the first time you use it, and there is a lot of documentation on line to help troubleshoot, if needed
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.
Looker is an off-the-shelf, free tool for Google business users. Other than the internal cost of time to build, we had no costs to set up what we needed to do. Knowledge sharing internally and using templates greatly reduced this cost, making the overall cost very low.
Google Data Studio provides a great feature set considering its price point, especially when compared to commercial options from Microsoft and Tableau. While it may not be as versatile when it comes to working with and developing complex datasets, there is enough charm in its simple, easy-to-use UI to allow not-so-complex analytics to be conducted without having to hire a data analyst.
Allowing others to self-serve their own analytics and connect it to Looker simply and easily has helped unblock the central data team so they can instead focus on validated dashboards whilst stakeholders manage their day-to-day analysis themselves. Countless engineering hours have been freed up by not having to manage every user permission for each BI tool; we have a BYOBI approach; Bring Your Own BI
Creation and management of a semantic layer (LookML =Looker Modeling Language ) allows peoples sandboxes and production databases to become clutter free. Minor adjustments, conditional fields, and even some modelling can all be done in LookML which doesn't need oversight or governance from the central data team.
LookML, specifying drilldown fields and their sub-queries, as well as generally creating dynamic parameters with Liquid are all great features, but can have a steep learning curve. it may take some time to understand how to create this middle layer correctly, or even pose a risk of inheriting complex code from another source which can be unmaintainable if it becomes too big. Some level of governance is recommended if Looker is used by a large number of editors.
