Looker vs. SAP Crystal

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).

Incentivized

Generation of templated reports is the strong suit of SAP Crystal. Allows users to change formats in templates bases on requirement with minimal effort. Automated report delivery requires the user to be aware of sql which cannot be expected from all users. Should support more document export formats and improve the UI for SAP B1 Users

Incentivized

• 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

Incentivized

• Crystal Reports allows us to create a consistent template for all of our reports.
• Crystal Reports and Server allows us to house a repository for all of our reports to make them easy to find and update when necessary.
• Crystal Reports can connect to a wide variety of data sources.
• Crystal Reports can be a little daunting when first implementing. There are a lot of nuances in learning how to truly master this software and it can be frustrating at times.

Incentivized

• 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

Incentivized

• The export of reports to Excel is very cumbersome and the results are difficult to format.
• The design of reports and the graphical features (e.g. charts) feel quite rigid.
• The learning curve for a non-programmer is incredibly steep, making Crystal a specialty tool.

Incentivized

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.

Incentivized

We have been using this product for so many years and it has truly become a cornerstone to our business processes when it comes to developing and distributing information via reports. We currently have over 500 reports developed to date over about 30 systems and that will continue to grow as user needs change.

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.

Incentivized

Crystal is very robust, but not always easy to use. It create wonderful looking reports, and so deserves a high rating. However, I have to take a couple of points off for the simple fact that I cannot hand it to a user and expect them to be able to do development with it.

Incentivized

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.

Incentivized

The support community can be difficult to navigate. I've also run into issues with my login. The SAP system has a bizarre mechanism for validating users that requires users to have what is called an S-ID. A basic ID may not give you access to all the features in the portal. The limitation may include not being able to perform a simple task like downloading patches and updates. This isn't a big deal for single user license but for teams it can be a pain.

Incentivized

Trainer was patient and thorough in going through the basics and willing to answer questions by email after the initial training

Incentivized

Just like any other implementation: When designing the differing reports, get end users' input, make sure to design the reports so that they display the information that the company requires, in the best and clearest way possible.

Test, test, test, revise when needed, and, particularly, do sufficient training so users are comfortable using Crystal Reports!

Incentivized

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.

Incentivized

Crystal reports is useful in case we want to import data from data base . We can write queries in it but Google Charts require to be implemented in our application using code so crystal reports is better than Google Charts.

Incentivized

• 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.

Incentivized

• It is a decent buy for specific departments in terms of reporting capabilities but updates and cost (frequent) demands are higher with the benefits offered.
• So long as the requirements are not ever changing, with scheduling functionality, it's a handsome tool.

Incentivized