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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Sisense for Cloud Data Teams
Score 6.6 out of 10
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Sisense for Cloud Data Teams (formerly Periscope Data) is a data visualization tool that allows users to connect to their SQL databases to create sharable, interactive dashboards. In addition to SQL, its analytics integrate with R and Python, allowing users to prep datasets, perform analysis, and create their own visualizations. Sisense acquired Periscope Data in mid-2019.
Most of the other BI tools are fairly similar in terms of charting capabilities and performance. Looker stands out with its modeling layer and SQL free end-user interface. It also has a feature-rich API enabling you to embed Looker into your own web app to customize it further …
We use JIRA here at SDC, as well as Periscope. These programs are use together and they work in tandem to get the issues resolved.
Verified User
Director
Chose Sisense for Cloud Data Teams
LookML was able to simplify development of views involving window calculations, but slowed down the overall development cycle as minor SQL edits required heavy code reviews.
Tableau has great interactive options but has proved non-performant with our database mix (MySQL, …
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).
Sisense for Cloud Data Teams is suited so well for our project that works with lots of data and needs some ways to share data internally or externally with our clients. It's very easy to pull out the data from the sense in best and in a suitable format and moreover a huge number of options are available there to represent the data. All features of this Sisense for cloud data teams software can be taken advantage of if you have a team who are well versed in data analytics, data management, and programming.
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
Rapid deployment of polished T-SQL-based data visualization charts and dashboards. Periscope supports a variety of database technologies, and allows users to write custom queries to display data.
Included caching to reduce server load.
Outstanding customer service/support, with expert advice as needed.
Constant updates and new features.
Built-in SQL formatters take the pain out of manipulating date/time objects.
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
Include more appropriate updates in their monthly newsletter as opposed to the general overview that doesn't always have the most pertinent information at the forefront.
There are bugs at times when certain dashboards are down, though not in an overwhelming way.
If you do not tag something it shows up in multiple views and may be accessible to people that it should not be, though that is a user error it may make sense to prompt for a tag and security setting.
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.
My company has had Periscope for various use cases in the past and I think that this program opens up complex data reports to non-technical people in a really accessible way (even though the learning curve is a big one). We are now integrating Sisense for Cloud Data Teams at a larger level both for internal data exploration and for customer facing dashboards and reports.
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.
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 Analytics works well but it does not have all of the bells and whistles that Periscope Data offers. Google Analytics is best used in a Google environment but if you are using other tools and programs outside of the Google universe, then Periscope Data is a much better option.
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.
