In today’s business landscape, the only thing better than building a tech stack to answer questions with data is building a more efficient stack to answer those questions even faster. Every step of the data analysis workflow is an opportunity to shorten the amount of time it takes to uncover data-driven insights. For each of those discoveries, faster analysis translates directly to increased value from the insight.

To help every team make data-driven decisions at the fastest speed, we created Data Engine. It offers faster query performance and data ingestion at scale for any kind of workload regardless of concurrency, size or complexity. Data Engine adds to our already-impressive data science platform, allowing teams to pair it with any warehouse to run every query on a stack custom built to achieve the fastest results.

The Sisense for Cloud Data Teams advanced analytics platform offers any data scientist the flexibility to combine powerful data languages to uncover deeper insights. Sisense for Cloud Data Teams can quickly shine a spotlight on the data models you have already built within Snowflake, while also allowing a data scientist to materialize views using SQL, Python and R.

Last week, sales engineering manager Ryan Waters spoke at the 2019 Snowflake Summit to share the story of one of our customers who combined Sisense for Cloud Data Teams and Snowflake’s data warehousing to speed up their complex workloads. To solve the problem of slow-running queries, ezCater implemented Snowflake to separate compute and storage, giving them more control over how their queries are prioritized and letting them answer the most pressing questions as soon as possible.

Using Sisense for Cloud Data Teams as the end-to-end data platform, ezCater could connect their data sources, analyze information, visualize the insights and share with teammates all from one location. Without the need to switch tools for different steps of the process, ezCater’s analysis improved dramatically. To speed things up even more, their team of data scientists used materialized views to avoid duplicative work on future queries.

With the powerful stack of Sisense for Cloud Data Teams and Snowflake, the ezCater team increased the speed at which they could run complex new ad hoc queries, giving them even more powerful answers. These results can instantly be shared with the rest of the team for further exploration, reducing the time from question to action even more. With the materialized views, they can even reuse portions of those complex new queries when similar questions come up. Using this powerful tech stack, they’ve reduced time to answer at every step of their process.

To learn more about how Data Engine works, check out the video below. If you want to see how fast your queries can run with our innovative technology, try Sisense for Cloud Data Teams for yourself.

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