Reveal embedded analytics enables teams and customers to drive data insights with embedded intelligence, transforming the user experience of apps.
Built with embed in mind first, on modern architecture, Reveal’s API aims to remove the complexity of embedding analytics into applications. Reveal’s native SDKs can be integrated into applications on any
platform and tech stack including: .NET Core, Java, NodeJS (coming soon), and
front-end technologies such as React, Angular, WebComponent,…
$0
Looker
Score 8.2 out of 10
N/A
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.
Lacks ability to generate analytics as complex as Tableau and not as easy to embed and interface with other software and databases as Looker. But a very good option for those not needing the complexities found in other products.
While Reveal is relatively pricey, it offers some of the best features I would say it is more resourceful than most competitors. Being resourceful means it is more capable and delivers better reports - comprehensive reports.
Reveal's integrated .NET component approach is interesting. Many solutions have an iFrame only option, which limits your applications ability to interact with dashboards.
Looker stacks up very well against the other tools we have evaluated and used. All the tools have their own pros and cons. Looker had a better edge in terms of visualizations when we chose to use it. After several updates, other tools began to have newer features. Looker still …
As a company responsible for people money we have to deal with following challenges every day: Clients who want to track the status of their transfers. Licensing agencies who need to ensure professional standards are met. Internal team managers who need to track client and staff progress to ensure company progression and success. Reveal does a good job as self-service tool enabling the accountable parties to have full access to important insights 24/7. The prebuilt dashboard themes save time and investment as we don’t need to hire a dedicated data analyst. The interactive dashboards give full transparency. The ability to easily create, analyze and report keeps clients, partners and stuff on the same page.
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).
Ease of Use - Reveal is super intuitive when it comes to creating dashboards. You don't need to be a data expert, which is key for me.
Sharing - The ability to share across our teams, locations, and with clients is great. We create teams for our different clients and share dashboards there that also are connected to our company dashboards.
Support and Roadmap - Reveal support has been great. They care about the needs of their customers. They have released 3 updates in the last few months, and they are adding a lot of value.
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
As a developer of the project, I feel comfortable with this tool for its peculiarities: acceptable costs, simple configuration, creation and maintenance of simple reports, fairly complete account management, also, not least, I appreciate the work done by their technical support always timely intervention and, above all, resolutive. Furthermore, as far as end users are concerned, I found a good appreciation of the proposed reports
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.
Reveal has a great usability for any level of computer user. The only major thing I see that is not exactly user friendly, is the color scheme issue I stated earlier in my review. Although, I am coming from a graphic design background, I need a platform that every team member in our office can use.
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.
This assessment is due to the fact that I have not yet found Reveal not available for use. Apart from some problems of development crash, then fixed by the product assistance service, I have not found any particular problems or loss of time caused by the instrument.
The pages load rather quickly even in the presence of several elevations in the same dashboard that insist on different data sources and with visualizations that insist on different types of graph. I can only be satisfied with these performances.
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.
None in particular, however, would be welcome if improvements were made in the personalization of the prospects and in the connection between them (perhaps being able to transfer the selections present in one prospect to another recalled by the first).
While Reveal is relatively pricey, it offers some of the best features I would say it is more resourceful than most competitors. Being resourceful means it is more capable and delivers better reports - comprehensive reports.
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.
This evaluation is the result of the fact that I have not had the opportunity to deepen the Reveal interface with other tools and / or other software, so the evaluation that I am giving follows what I have been able to read regarding the characteristics of the product online.
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.
