Advanced Analytics & Cloud Data Platform for Data Teams

Get Deeper Insights with Powerful Tools
for Advanced Analytics

With increasing volumes and complexity of data, the process of transforming raw data into actionable insights requires more powerful tools. Sisense for Cloud Data Teams (previously Periscope Data) provides data teams with the ability to build cloud data pipelines and quickly perform advanced analysis using the languages they prefer, all while utilizing software development best practice workflows.

Write Queries, Analyze Results

Profile, transform, investigate and visualize large volumes of raw data using SQL, Python, and R

Build Cloud Data Pipelines

Model data with code, optimize performance with materialized views and visualize pipelines with data lineage exploration

Employ Development Best Practices

Develop advanced analytics with the same Git tools and workflows used by software development teams

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Write Queries, Analyze Results

Avoid the pitfalls of fragmented open-source toolchains and single-user workbenches with the integrated suite of capabilities in Sisense for Cloud Data Teams

Explore Data with Code

Write queries in SQL, analyze results using Python and R. Create reusable analysis frameworks for a more iterative experience through code views and snippets.

Visualize Results

Visualize query results or convert them to models written back to AWS Redshift or Snowflake. Visualize massive quantities of data with server-side matplotlib and ggplot.

Deliver Custom Insights

Deliver interactive visualizations with powerful charting libraries. Allow users to slice and dice, pivot, filter, and download data with ease.

Build Cloud Pipelines

Extract and transform data without the fragility of production ELT infrastructure with Sisense’s Cloud Data Pipelines.

Launch Your Cloud Data Warehouse

Utilize Managed Cloud Data Pipelines to transition to your own AWS Redshift or Snowflake deployments with no downtime.
The built-in Summary Statistics functionality helps you quickly understand data at a glance to identify patterns, relationships, and unexpected values.

Integrate New Data

Ingest new sources directly into your warehouse and respond to requests without the overhead of semantic modeling by working with both unmodeled and modeled data.visualizations using Python libraries or R packages such as plot.ly.
Create advanced, highly customizable visualizations using Python libraries or R packages such as plot.ly.

Improve Query Performance

Prototype new transformations before introducing them into nightly ELT processes. Reduce query times and computing costs by materializing views and reporting tables.
Automate and manage changes by syncing all user-generated content through Git, using GitHub, GitLab, BitBucket, or your own Git server.

Employ Development Best Practices

Level up your data team by developing your analytics like you develop software.

Unlock Advanced Analytics

Augment your data with predictive and statistical libraries or custom scripts and write results back to your warehouse to add crucial insights and generate advanced analytics.

Centralize Code

Collaborate with your team and save time on new projects by centralizing frequently used in-house code and logic with snippets and views.

Use Git Version Control

Control, track and manage changes to your queries and dashboards with a bi-drectional sync into the Git repository of your choosing.

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Learn How These Companies Drive Their Entire
Business with Advanced Analytics

Pared

Pared helps restaurants fill staffing gaps on demand. Learn how the data science team at Pared uses Sisense for Cloud Data Teams (previously Periscope Data) to take complex analytics projects to the next level with the Python and R integration.

Crisis Text Line

Using Sisense for Cloud Data Teams’s (previously Periscope Data) natural language processing and machine learning functionalities, the data science team at Crisis Text Line identified issue trends through topic modeling and built a stack-ranking queue that prioritizes incoming messages based on severity.

GitLab

GitLab is a complete DevOps platform committed to accelerating software lifecycles by as much as 200%. GitLab uses Sisense for Cloud Data Teams (previously Periscope Data) to stay agile with the ability to query in SQL, and move into Python and R to perform more complex analysis.

Crunchbase

Crunchbase is the master database of the startup ecosystem, with more than 500,000 data points profiling companies, people, funds, fundings, and events. With over 31 million visitors to their website each year, Crunchbase collects and uses an incredible amount of data, and therefore needed a powerful analytics platform to aggregate all its data to ask the right questions