More data is accessible to your business than ever before thanks to the rapid growth of the web. Right now, you could be sitting on mountains of valuable data, if only you could make sense of it all. That’s both the challenge and benefit of data—the quantity. You have so much, with more coming in every day. Anticipating your data, organizing it, and deriving insights from it is a struggle that traditional methods of analysis can’t possibly keep up with.
Grow has a library of ready-to-use data connectors.
Most of your tools—your CRM, CMS platform, or ERP, for example—offer an API that can be used to communicate directly with other systems. Everyone’s tech stack is different, and building a custom API connection can take time.
Grow’s library of data connectors provides three benefits:
We have over 115 data connectors built for systems such as:
You can see the full list for yourself in our Data Connectors Library.
Grow’s ultimate goal is to increase the amount of governance that both technical and non-technical users can have over their data.
Looker will connect to any SQL database. But while many systems use SQL, not all of them do. Additionally, you do have the power to connect to new databases directly via Looker, but the process is more IT intensive.
Looker is flexible and can be customized to match a business’s tech stack, but it will require more technical expertise to do so. Grow’s process of connecting with your tools is much more simple—we’ve already done the bulk of the work by building out the data connector for you.
Traditionally, BI and analytics platforms serve up insights and visualize data from a data warehouse. The data warehouse stores data that has gone through an ETL (Extract, Transform, Load) process that normalizes and cleans it. The downside of this is that the data you use in your BI platform has already been prepped and stored in the data warehouse—you don’t have access to the raw data.
Grow removes the need for a data warehouse, and allows you to perform the ETL process and store the data in Grow directly using point and click tools to normalize and clean data.
Looker uses data that has already undergone the ETL process. It can be connected to other open source ETL tools. Looker has also announced recently that it will eventually roll out ETL capabilities.
Grow allows you to work with your data all in one place. Rather than only working with data after it’s undergone the ETL process, you can specify in Grow what that process looks like and change it later on. You don’t have to manage an additional system or work with a third-party to do so, you can control it directly.
Grow has 20 different methods of visualizing data, including stacked column, pareto, radar, funnel, and bubble types. Using a variety of charts, users can build out dashboards that tell a complete story and provide insights.
You can see how clients have used Grow’s data visualization tools to build out unique dashboards on our Dashboards We Love page.
Looker provides a wide variety of methods you can use to customize the layout of your data in your platform via Looker Blocks®—which act similarly to plugins. Looker has six Looker Blocks® specifically for data visualization and allows you to customize more. These can be responsive, allowing the user to dive deeper into an individual data set. Additionally, Looker provides simple and straightforward drop-down menus for filtering.
Although Looker provides many different opportunities for data visualization, adding them to your platform will still require some coding. Grow offers a similar variety of data visualizations without requiring you to build or customize them at the code level.
As a SaaS platform, Grow hosts everything for you. When you want to query data, Grow uses its API data connectors to query the data stored in your various systems—removing the need for a data warehouse.
You don’t have to worry about configuring your server or creating a separate data warehouse—you simply sign in to Grow’s online portal.
Like we said, setting up Grow with your data connectors is a point-and-click process. Grow will need permissions to access each of your data sources. Once it has those, it can begin piping in data.
You can host Looker on your own servers or opt to have them host it for you. If you do choose to host Looker on your own servers, the set-up process is more time intensive. Fortunately, they provide extensive documentation and customer support to help guide you through it.
Alternatively, if you choose to use Looker’s hosting service you can avoid the server-side set up. Getting Looker up and running will just require connecting to your data sources (whitelisting your systems, creating logins for Looker, and configuring PDT’s (Persistent Derived Tables) between your data source and Looker) and creating user accounts.
Looker offers the flexibility of choosing between self-hosting and hosted-as-a-service, which can be really convenient for larger enterprises who want to retain the ability to configure their system to their exact specifications. Either method is as simple as Looker can make it, with added documentation and support to make the process smoother. Their method is also proven to be one of the most secure. All of these things can really make a difference to a large business that needs a more complex BI solution.
Alternatively, Grow’s implementation process is just as secure and takes less time. Grow hosts everything on its own, which can be convenient for businesses that don’t have the resources to manage and secure their own server. For a business with less complex BI needs and a smaller IT team, Grow would be the perfect solution.
Grow has been built largely with the non-technical user in mind. Although the initial data transform process will require a professional data analyst to configure, once your data sets have been defined you can manage them directly yourself.
For your data analyst, Grow’s data workflow process is straightforward with drop down menus, moveable columns, and customizable tables, in addition to systems analysis functions that help with complex data combinations.
For your business user, once the data has been prepped and normalized they have full control over the creation of dashboards, metrics, data visualization charts, and more without requiring any coding.
Looker’s data modeling process does require some coding, which can be a hurdle for non-technical users. In addition, Looker also lacks tools for building data visualizations and manipulating visualizations in native mobile apps.
Looker has taken strides to make their platform more user-friendly for the business user. They can now perform more complicated functions—like merging queries from different data sources—more directly.
If you are a technical user, Looker may be a better option because it allows you to customize it at different levels. However, in any business setting you’re going to have a variety of technical backgrounds, which means that someone is going to find themselves frustrated with Looker’s interface.
Grow is easier to use at any point and for any type of user, whether an experienced data analyst or a business user attempting to put together a dashboard of metrics for their team.
With Grow, you have complete administrative control over user accounts, designating who has access to data, dashboards, and management capabilities.
You can keep your team up-to-date with custom dashboards, wallboards (metrics specifically designed for a mounted display) scheduled email updates, or through the Grow app. These reporting tools all represent your data in real time, and are updated automatically.
Looker provides you with the same administrative controls that Grow does where you can add and delete user accounts and set permissions.
As far as sharing goes, there are different methods that Looker permits that help with different sharing situations. For example, for one-off sharing, can share data visualizations, query results, and dashboards, and other insights by simply sending a link to the URL.
Alternatively, you can share regularly scheduled reports with your various teams through email sends. You can embed Looker dashboards into webpages or make Looker pages public and share them publicly.
We have to acknowledge defeat to Looker on this point. As a browser-side system, Looker provides users with more opportunities for sharing that include Grow’s capabilities and go beyond to more complicated sharing functions.
As a purely SaaS system, Grow hosts everything for you. Grow stores your data sets and metrics, and caches your data to a certain extent. But for the most part, your data isn’t stored in Grow.
Data is communicated to Grow from your designated systems, and then prepped directly within Grow itself. Your data is stored in the systems that report to Grow, which keeps Grow fast. Any time you query data, Grow pings your various systems.
There’s a few benefits to this:
Like we said above, Looker can be deployed either on the cloud or on-premises. Additionally, Looker uses the data source (whether your own data warehouse or your reporting system) for processing, leveraging the power of the data source itself instead of slowing down trying to process for you.
Because Looker offers both options, cloud or server-side set up, Looker wins this comparison.
BI platforms exist along a spectrum. At the higher level, utilized by massive enterprises, BI systems are just a single layer sitting on top of a data warehouse and an ETL system. At each level, individual teams are responsible for supporting data processing and storage.
At the opposite side of the spectrum, BI systems are a direct one-to-one display of data. You have no control over how it’s displayed, all your data from your separate systems is centralized in a single place.
Grow’s platform exists in the center of the spectrum. You don’t need an additional ETL layer, an IT team to create custom API integrations, or a data warehouse—Grow does all of that for you.
At a certain point, a business can grow large enough that outsourcing data processing and storing a massive amount of data will require a data warehouse and a separate ETL layer and team. Eventually, having the flexibility to build out your own BI technology stack will become important. At this point, this is when a tool like Looker becomes a good option.
Simply put, companies anywhere between $1 million – $50 million go with Grow's end-to-end BI platform. Enterprise companies larger than $50 million that have their own data warehouse and dedicated analytics team opt for Looker.
It’s not so much about revenue as it is about data. The deciding factors between Looker and Grow will be the size of your organization, the number of systems reporting data, the quantity of data, the number of key stakeholders dependent on data insights.
Pricing for Grow varies depending on data and integrations, but our price starts at $500 a month.
Looker offers different prices depending on the client, but various reports estimate Looker’s pricing can be around $48k a year.
Pricing is one of Grow’s strengths. Cost tends to be a blocker for most businesses looking for a BI solution (Looker is, in fact, one of the cheaper systems on the market). But when you compare cost to value, you get a significant amount from Grow for a fantastic price.
Data can be frustrating, even more so if you find yourself saddled with the wrong kind of tool. Looker is a robust BI system, but Grow is much more straightforward. Ready in minutes, constant access to data, fast, and easy to use by non-technical admin, Grow is the winner.
Although Looker is a strong platform in its own right, its coding requirement makes it a difficult tool for non-technical business users who are much happier with a point-and-click platform.