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.
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TIBCO Data Virtualization
Score 8.5 out of 10
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TIBCO Data Virtualization is an enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the datasets and IT-curated data services foundation for nearly any solution.
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).
TIBCO Data Virtualization is well suited for customers who are challenged to deal with extracting data from dozens of different sources and systems, and do not have the time and liberty to hire data engineers and/or ETL developers to write dozens or hundreds of complex ETLs. However, there are situations where TIBCO Data Virtualization severely underperforms, and those are where we are dealing with large volumes of data, in tera bytes or peta byte scale system. For example, a messaging queue which sends 200 million messages every hour will choke TIBCO Data Virtualization if the technology is chosen to route the data.
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
Performance of TDV repository database is rather poor for larger numbers of objects .(Note: We have approx. 9tsd objects introspected in TDV and approx. 20tsd objects generated in upper DV layers.)
Propagation of privileges to parent/child dependencies does not work when applying recursively on a folder. (It's a huge setback when working with large number of objects organized semantically into subfolders.)
Lack of command line client interface for scripting at the time of version 8.4 (I had to write my own CLI.)
TDV Studio does an absolutely horrible job with its own code editors when indentation is in place. Also, the editor is brutally slow and feature-poor.
Tracking privileges on the level of table/view columns causes occasional problems when regranting.
TDV's stored programs ("SQL scripts" in their own terminology) compiler leaves out many syntactic and semantic checks, making them hugely prone to run-time errors.
TDV Server's REST API is a very poor (in terms of features) and flawed cousin to its SOAP API (at the time of version 8.4).
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.
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.
TDV's interface is a bit dated and not entirely intuitive. Would recommend some UX design review as the interface leaves a bit to be better understood to be used by users without inherent knowledge of Tibco. Overall I'd suggest more improvement here to ensure usability by a lesser tech audience.
This product's performance is very consistent. It is extremely rare for templates to fail. I've been using this software for 5 years and find it to be both simple and powerful. The impact within the company has been very positive as different processes in different areas, such as data analysis, development, and integrations, have been improved, and, best of all, it has not affected the users. Various systems with which it is connected in order to obtain information.
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.
On a few occasions I have asked TIBCO technical support for help because I have adapted perfectly to their tools, but in those few that I have communicated with their technical team I have received personalized, attentive, responsible attention and I am always assisted by an expert staff the topic. A TIBCO technical support technician spent more than an hour helping me to solve a problem in the initial stage of implementation in my department and this is something that I always appreciate.
The training was helpful. I was able to understand how to use TIBCO for the data load process that we implemented and how to perform various troubleshooting steps based on the training I received. The technician was thorough and took the time to answer any questions. Once we were shown how to use TIBCO in the test environment, we were able to configure the production environment ourselves.
Other vendors have clearer, more visual implementation documentation. We also did not have our data architect and and server administrator available full-time for implementation. In the future, we will secure the necessary internal resources.
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.
We did not need to evaluate another technology in the same category for data virtualization, since we are 100% sure of the capabilities and benefits that we would have with TIBCO Data Virtualization, both for market positioning as well as success stories from other companies. great renown worldwide. From the first day of use, it meets our needs to provide the expected solutions.
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.
