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 provides data teams with the ability to build cloud data pipelines, perform advanced analysis using languages they already know like SQL, Python, and R, and create advanced, custom visualizations to easily share insights.
Easily connect to your cloud data sources and increase visibility and control over your entire data pipeline.
Securely connect and ingest data into cloud data warehouses to create a single store for your data.
Reduce query run times from hours to seconds by materializing views with high complexity directly back into your cloud data warehouse, such as Redshift or Snowflake.
Reduce compute costs with flexible view scheduling options that give you full control over when and how often your data is refreshed.
Advance from reporting on the past to predicting future KPI movement with powerful tools for advanced analytics.
Powerful features including query revision history, autocomplete, formatting, snippets, and exploration mode enable you to go from query to answer in seconds.
The built-in Summary Statistics functionality helps you quickly understand data at a glance to identify patterns, relationships, and unexpected values.
With support for SQL, R, and Python in the same environment, you can perform predictive analytics, natural language processing, and data preparation for machine learning on a single platform using your language of choice.
Create advanced, highly customizable visualizations using Python libraries or R packages such as plot.ly.
With the Git integration, data teams get a sophisticated version control system, release management workflows, and file-level access to all user-generated content.
Automate and manage changes by syncing all user-generated content through Git, using GitHub, GitLab, BitBucket, or your own Git server.
Explore modeled and raw data to answer unpredicted questions in minutes, reusing common code snippets to avoid timely rebuilds.
Answer complex and ambiguous business questions without having to rebuild any upfront models. Data teams can query data directly from the source to get answers fast, even if the source data or assumptions have changed.
Augment modeled data with new insights from ad hoc analysis to quickly iterate on hypotheses and uncover new insights for the business.
Centralize frequently used in-house code and logic using snippets and views to easily collaborate with the rest of your team. Data teammates are up-leveled to work on more impactful projects, without having to start each new question from scratch.
Flexport is a licensed freight forwarder for modern logistics teams that move freight around the globe. Learn how Flexport uses Sisense for Cloud Data Teams to respond to unforeseen factors and alter shipping routes in minutes.
Pared helps restaurants fill staffing gaps on demand. Learn how the data science team at Pared uses Sisense for Cloud Data Teams to take complex analytics projects to the next level with the Python and R integration.
Using Sisense for Cloud Data Teams’s 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 is a complete DevOps platform committed to accelerating software lifecycles by as much as 200%. GitLab uses Sisense for Cloud Data Teams to stay agile with the ability to query in SQL, and move into Python and R to perform more complex analysis.