Analytics & BI

Access and analyze any type of data to answer critical questions
  • Fast deployment: Get up and running immediately without requiring a new proprietary language; choose whether to build upfront modeling or model as you go, to quickly adapt to your business needs
  • SQL, Python and R together: Move from reporting past data to predicting future trends using SQL, Python and R in a single platform
  • Easily share and reuse models: Make ad hoc analysis reusable by centralizing business logic and making models easily accessible for other teams — this encourages best practice sharing and create cross-organizational collaboration
  • Empower the business: Enable non-technical users to explore data and find their own answers so you can have more time to answer more complex questions

Use Cases

Warehouse Optimization

Build a model based on a set of attributes to identify query clusters for optimizing concurrencies on the database. This centralizes reporting definitions and remove redundant views from the data pipeline. 

Query Monitoring

Internal monitoring of top level metrics, such as throughput per time unit, to help identify if a system is at risk or hitting a certain limit that would require additional resources to support the business needs.

Sentiment Analysis

Analyze documents, NPS comments, Saleforce leads, etc. using NLP to help business teams understand text feedback at an aggregate level. 

Use Cases

Warehouse Optimization

Build a model based on a set of attributes to identify query clusters for optimizing concurrencies on the database. This centralizes reporting definitions and remove redundant views from the data pipeline. 

Query Monitoring

Internal monitoring of top level metrics, such as throughput per time unit, to help identify if a system is at risk or hitting a certain limit that would require additional resources to support the business needs.

Sentiment Analysis

Analyze documents, NPS comments, Saleforce leads, etc. using NLP to help business teams understand text feedback at an aggregate level. 

There have definitely been times in the past where I’ve been discouraged from doing that extra analysis, because of all the additional work it entailed. But now with Periscope Data, I’m actually encouraged to do more powerful analysis because it’s so much easier to get done.

Carthook: Ben Fisher
AJ Francia
Data scientist at Pared

Additional Analytics Resources