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Move Tune Data into a Data Warehouse in Minutes

Tune integration comes standard within Panoply. This integration makes it simple for companies to integrate their Tune data directly into their cloud data warehouse, and begin analyzing and assessing that data in minutes.

Tune is a mobile marketing platform and technology that provides analytics on app store sales, marketing intelligence, and other in-app data. Panoply makes it possible to store Tune data without requiring an ETL process, combine and connect Tune data with any other data sources or tools you use, and begin creating reports or analyzing marketing trends instantly.

Panoply lets SMBs manage their Tune data without a costly data infrastructure, so companies can begin improving their mobile marketing strategies and creating winning campaigns with a cloud based turnkey end to end data platform.

Panoply makes it easy to analyze Tune 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

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