Analytics

Augment Data Preparation With New, Collaborative Query Library

By Davide Russo - September 2, 2020

In analytics, speed is everything. Analysts are under constant pressure to move quickly, deliver consistent answers, and proactively inform the business about changing metrics.

At Sisu, we focus on augmenting every part of your analytics workflow — including the often arduous, repetitive process of data preparation. While SQL is the preferred method for analyzing rich, wide data stored in data warehouses, analysts write and rewrite queries across applications, meaning queries can quickly become convoluted.

To help, we’re introducing two new ways to augment your data preparation with Sisu: a shared query repository, and an Athena connector for your Amazon S3 data. Let’s take a look at how these new features help data teams work faster, more collaboratively, and more effectively across data sources.

Accelerate diagnosis, reduce data preparation by saving and reusing queries

As an analyst, you’re constantly navigating undocumented issues with data tables and writing complicated SQL queries to analyze common business metrics like free trial conversion rate, average revenue per user (ARPU), and customer churn. Inevitably, you get more questions from the business a week later and have to re-write everything.

Instead of writing a query once and throwing it away, the new query repository creates a central place for collaborative data teams to write and share queries in Sisu, allowing you to accelerate data preparation and deliver faster answers to the business.

The new library stores all of your saved queries for each data source. You can quickly select the best one, or write your own custom query. As you’re writing, Sisu auto-completes your queries and gives you the ability to preview your new table before saving and running the analysis.

Sisu also simplifies reusing your queries across tools. For example, if you set up a table in DBT you can easily use that in Sisu, or if you use Looker, you can pull queries from LookML views and add them to your Sisu repository.

Demonstrating how saved SQL queries reduce data preparation

(Product image uses mock data.)

Collaborate and deliver consistent answers across the business

As your query schema and logic become increasingly complex, it’s often difficult to choose the “right” version for each metric — especially when multiple analysts are working together. Ultimately, analysts calculate a common KPI, like churn, in slightly different ways. This leads to errors and inconsistent analysis.

Sisu’s new collaborative workflow gives your whole team instant visibility into the best queries for each metric, enabling your team to deliver consistent answers that the business can trust.

Once you’ve written the queries, you also create new opportunities for business stakeholders across product, sales, marketing, finance, and other functional areas to start answering questions in Sisu on their own – no SQL or BI skills necessary.

Enabling self-service is just one benefit of augmented analytics, and you can explore more in “Four Reasons Why Now is the Time for Augmented Analytics.”

Connect to even more data sources quickly

In addition to our existing catalog of fast, secure data warehouse connectors, you can now use Sisu with Amazon Athena to query your S3 data stores. This is the fastest way to complete detailed diagnosis of data stores and to start taking advantage of your wide, rich data in S3.

Using the new Athena connector, there’s no need to set up complex ETL pipelines. With Sisu and Athena, you have the power to efficiently store and query data and begin delivering answers.

Whether you’re seeking to understand customer segments and preferences or identifying opportunities to lift revenue, we’d love to show you how Sisu can augment your team’s ability to work faster, more collaboratively, and effectively across data sources.


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