Looker vs Sisense For Cloud Data Teams

Looker is a forerunner in the business intelligence field for a reason; it generates reports that include easy sharing via link, automatic scheduling and a level of granular detail that allows for deeper analysis below the surface. It excels in its filter and drill-down features and creates unique URLs when users make changes to data, leading to enhanced sharing. However, one of its biggest strengths could also be considered one of its biggest weaknesses: its proprietary programming language, LookML which is used to construct SQL queries in the platform. While a flexible and powerful data querying language, of course, LookML isn’t the most accessible to non-technical users, which means that Looker requires an IT or data team to access its full capabilities and has a steep learning curve. Users also note that its data visualizations, while simple and easy to understand, are quite basic and lacking in customization options, particularly in comparison to competitors. Some users say that it may be more appropriate for internal reporting than presentation to shareholders and end-users because of its bare-bones visualization options. However, Looker truly shines when used by enterprises, with its scalability and data accessibility making it a stellar solution that can align departments and provide thousands of users access to data insights. Its price point reflects this, with its pricing being prohibitive to startups as about 88% of users who comment on its cost remark. Overall, Looker is a solid pick for larger businesses that have a team of power users who can maximize its functionality and set it up to deliver to employees across an entire organization.

Sisense for Cloud Data Teams is a powerful BI tool that excels in the hands of data analysts with coding knowledge. These analysts will be able to model, manage, prepare, manipulate and analyze data with ease. As the platform supports SQL, Python and R programming languages, the sky's the limit when it comes to extensibility, development and coding support. The platform allows for strong collaboration within an organization, designed to alleviate the time-consuming burden of reporting and data visualization on IT teams while allowing business users to access insights on their own time. Most of the features are built around making the analytics team’s job easier, with reusable code, built-in collaboration and more. The support team earned universal praise from users who contacted them, citing their swift, in-depth and informative answers as immensely helpful in resolving any issues they had with the solution. In addition to hands-on support, a speedy implementation process ensures that customers can get the platform up and running in no time. We found that users’ opinions of the platform’s functionality and ease of use differed significantly based on their own roles; analysts generally praised its robust data visualization and data querying features, while decision-makers often found it hard to use, due to the SQL language barrier. SQL is necessary for most functions, and even though there is a visual query editor that attempts to make SQL more accessible, some users said that the platform doesn’t do enough in this regard. Overall, users did agree that the tool makes it easy to collaborate with each other to bridge that gap, with most of the analytics being done on the technical end, letting business users simply access those results. Still, it’s difficult to accurately call Sisense for Cloud Data Teams a self-service analytics tool, as it requires an IT or analyst team’s involvement to truly shine. Additionally, the cost can be prohibitive to smaller businesses. Overall, Sisense for Cloud Data Teams can be extremely powerful in the right hands - for those who know SQL and how to use it, it’s a dream for querying data and delivering analytics, but for those who don’t have the necessary IT resources, it could prove difficult to fully maximize the value of this data solution.