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Move Google Play Data into a Data Warehouse in Minutes

Google Play is an online media market that both sells and distributes mobile apps, music, movies, books, and other digital content for the Android operating system. Panoply’s Google Play integration lets you load its data directly into your own Smart Data Warehouse. Your analysts will have quick and easy access to all your data, without the need to maintain any ETL process, and can begin creating custom dashboards and reports from within the platform itself.

With Panoply, your Google Play data can be instantly combined with other data sources from within the cloud warehouse. Panoply makes it possible for your analysts to review Google Play data, manage their applications from beta, and learn more about customer downloads and purchases instantly, without the need for a full data infrastructure.

Panoply makes it easy to analyze Google Play 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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