A trusted data model is the cornerstone of the Looker data platform, which is centrally-defined, version-controlled, and collaborative. Customers tell us that Looker’s flexible yet powerful foundation is their key to delivering actionable insights to internal and external customers.
Looker automatically generates a data model based on the relationships between tables in the schema and presents users with an agile and collaborative way to expand and refine the central model in parallel in a version-controlled environment. This function ensures that the data model can be instantly updated as requirements evolve, so data consumers of all skill levels can get their business questions answered quickly and accurately.
In contrast, typically for performance reasons, many Sisense customers choose to deploy Sisense using their optional architecture based on in-memory data models called ElastiCubes, which can become cumbersome.
In deployments where customers choose to deploy Sisense using the ElastiCube-based architecture, development time is needed up front to build them before any query can be run — something their past customers tell us is an extremely tedious process. As the data models expand, it often becomes more difficult to maintain ElastiCubes, delaying the development process and making it hard to scale. Also, it can be cumbersome to make modifications if the database or logic changes, forcing the developer to go back to modify the ElastiCube.
Feedback we received from four Customers who had chosen to use the ElastiCube-based deployment option in Sisense cited the following benefits and core differentiators as the reason for ultimately choosing Looker:
The Looker platform is uniquely designed to allow anyone on the data team to update data definitions and relationships in the metadata layer easily and work together to maintain a centralized and well-governed data experience effectively. Business definition changes only need to be made once in the data model, and the changes will propagate automatically to all dependent objects. This simplified process makes managing and maintaining the data model easier.
Looker doesn’t require data to be extracted from underlying databases and then loaded into proprietary data stores which can significantly increase the maintenance overhead for IT while also increasing risk of errors and synchronization issues. Data is always changing, and so are business requirements. Instead of involving IT to make modeling changes to the data pipeline processes, physical data model and cubes, business analysts already familiar with SQL can contribute to Looker’s git version-controlled data model and define or maintain business rules for their organization. Each data analyst gets their own development environment to try out new analyses without affecting everyone else so that every change to your data model can be audited, examined, and rolled back, if necessary.
Looker provides a real-time data and analytics platform, powered by a modern in-database architecture that gives organizations unconstrained access to all data while leveraging the unique data-processing capabilities of the underlying database. Looker connects directly to any SQL compliant database for a real-time view of the business which allows users to go beyond pre-built dashboards to get answers to all of their business questions, not just the ones that have already been thought of in advance by someone else. With Looker, users are empowered to drill into their reports down to the row-level, create new queries, and explore the entire business in real-time, without running after data teams and waiting for the ETL process to finish.
Looker provides fresh data because of its native connectivity to the underlying database, unlike Sisense, which is designed to work best when data is extracted from underlying data stores into its proprietary in-memory Elasticubes. Some customers report that ElastiCubes can exhibit scalability and performance problems as the amount of users and volume of data increase. Under some circumstances, Sisense may recommend that customers purchase more servers to address performance issues sometimes seen in larger deployments.
Direct connectivity to any SQL database ensures no more stale data residing in Elasticubes waiting to be updated, and no need for inflexible physical schemas or in-memory cubes. And perhaps most importantly, no need to wait for IT to make modeling changes. Looker follows a more agile approach by leaving the data in the database so users can ask more questions without having to rely on IT teams to build additional cubes.
With Powered by Looker, organizations can embed world-class analytics directly into their existing applications, as well as build innovative data products to take to market and generate new revenue streams. Looker delivers a rich development framework that lets developers build data experiences using pre-built components that ensure these custom experiences fit in any application naturally.
Looker is the first modern analytics platform that lets developers use the modern GIT software development workflows and tools they love. Looker’s secret sauce is a code-based modeling language that allows you to:
Looker also lets you quickly grow and improve your product over time by scaling up with predictable performance and pricing. As you grow your customer base, you can maintain your model in one place and have changes update everywhere automatically. And you can rapidly and cheaply add new use cases, personas, user types, and customer types by taking advantage of the security and user provisioning already in place.
For more information on how Looker differentiates itself from others for Embedded Analytics, read the whitepaper on The Looker Platform vs. Alternatives.
Looker is 100% web-based and designed specifically for new-age data engines using modern technology. Looker supports today’s ever-evolving data ecosystem, so organizations can build their own data stack confidently, knowing that they have the flexibility to make modifications easily as the business needs change.
On the contrary, Sisense is a ‘heavy’ application that can carry a high infrastructure cost and requires a certain amount of memory and space resources for the application to function fully. Some organizations have reported that they incurred exorbitant hidden costs as they had to purchase new servers to scale with their growing users and data.
With Looker’s unique architecture, organizations can also take advantage of public, private, hybrid, and multi-cloud environments and the features and benefits each provides. Looker’s multi-cloud capability makes your data strategy future-proof. You can easily change where you choose to deploy Looker and which underlying cloud database(s) you use with no downstream impact to your end users.
Looker’s powerful explore section gives users of all levels a drag-and-drop experience so they can go beyond pre-made dashboards and reports to ask their unique questions. This flexible interface allows users the opportunity to iterate on questions in real-time and better understand their piece of the business.
For Sisense customers that decide to build Elasticubes in order to optimize performance, data bottlenecks can sometimes result and self-service can be limited, where most non-technical users cannot create or explore content and are limited to predefined dashboards and cubes. Typically only one internal “Admin" builds ElastiCubes, and one internal “Designer" creates dashboards based on the cubes. To ask a totally new question typically requires an admin to write a manual SQL query to build a new ElastiCube, and a designer to then build a dashboard for viewers.
Most BI tools can create beautiful visualizations that roll into impressive dashboards. Looker’s dashboards are live, interactive, and dynamic, so you can go beyond the surface and dive into the underlying data. Looker sits on fresh, governed data, giving you access to row-level detail so you can drill through charts to gain a deeper understanding of your business.
Looker prioritizes customer feedback and relationships above all else. Rather than following a traditional support model where customers can experience long wait times in a technical support queue before receiving a response, placing customers in a technical support queue, we connect customers via chat with a live person who knows the product and cares about solving their issue.
Looker’s support team earned the title of Department of Customer Love because of their outstanding service. The DCL elevates Looker beyond the competition and beyond Sisense.
Customers consistently rate Looker support as one of the most appreciated features of our product.
Looker customers can have an in-product, live chat with a DCL support engineer any time they need help with a particular feature, or have a question about the product — without leaving the platform.
Gartner regularly produces reports on business intelligence, among other topics. Sift through their unbiased analyses for better business intelligence comparison of platforms. Criteria include critical capabilities, leaders in the field, research on BI vendor abilities and more.Learn more
Forrester focuses on business analysis, producing reports on everything from artificial intelligence to branding, cloud computing to business intelligence. They provide an in-depth view of BI firms and developments in the field.Learn more
G2 provides consumer-focused reviews for business capabilities across a wide array of fields including staffing firms, legal service providers, cybersecurity firms and BI intelligence providers.Download report
BARC’s The BI Survey is the world's largest and most comprehensive survey of business intelligence (BI) software users, providing feedback from over 3,000 respondents across 95 countries using 36 BI solutions.Download report
Business intelligence, big data analytics, or a 360° view of your customers. Whatever you need, Looker can help. Talk to our data experts.Request a demo