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Move Mailchimp Data into a Data Warehouse in Minutes

Panoply’s easy to use integration systems allow MailChimp customers to store and analyze their eCommerce, email marketing, and advertising data in one central location, without requiring a complete data warehousing infrastructure.

MailChimp is an automated email marketing and newsletter platform, used in the eCommerce industry. MailChimp’s data reporting provides companies with detailed information about their emails, from demographic data to engagement.

The Panoply platform extracts that data directly from MailChimp, integrates it into its cloud based data warehouse without requiring any ETL or ELT processing, and makes it immediately accessible for analysis. It is instantly available to be combined or compared against other data sources and can be analyzed to help you make more effective emails and marketing decisions that improve your ROI.

Panoply makes it easy to analyze MailChimp data
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Why Panoply?

Use-Case Optimization

Analyzes queries and data – identifying the best configuration for each use case, adjusting it over time, and building indexes, sortkeys, diskeys, data types, vacuuming, and partitioning.

Query Optimization

Identifies queries that do not follow best practices – such as those that include nested loops or implicit casting – and rewrites them to an equivalent query requiring a fraction of the runtime or resources.

Server Optimization

Optimizes server configurations over time based on query patterns and by learning which server setup works best. The platform switches server types seamlessly and measures the resulting performance.

Updates, Upserts, and Deletions

Supports standard SQL update and upset operations out of the box – without worrying about vacuuming or rebuilding- unlike many analytical databases.

Semi-Structured Data Parsing

Supports semi-structured text values like nested JSON, user-agent strings, some standard log formats, CSV, and serialized Ruby objects – parsing these objects and normalizing them into a relational database design.

Nested Structures

Handles nested structures automatically, flattening them into several tables with a one-to- many relationship. The result is a ready-to- use relational database design for all current and future datasets.

Columnar Storage

Provides seamless data storage and management in a multitiered, columnar storage based on Amazon Redshift, Elasticsearch, and Hadoop or SS3.

Data Tracking and Alerts

Simplifies how you keep track of vast amounts of data – by identifying patterns, providing notification of anomalies, and generating alerts when the results of arbitrary SQL queries exceed predefined thresholds.

Backup and Recovery

Automatically backs up changes to data to a redundant S3 storage, optionally saved in two different availability zones across continents – enabling full recovery to any point in time.

From raw data to analysis in under 10 minutes

Sign up now for a demo or a free trial of the Panoply platform

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