Panoply’s main dashboard gives you full transparency into your data pipeline processes and performance optimizations to make it even easier to view the status of data source integrations, storage space, and query processing times. You can also easily assign Admin rights for better governance controls.
Panoply automates the modeling schema so you don’t have to spend endless hours on reindexing the data.
Whether your data is structured or not - including file types CSV, TSV, JSON, and regardless of the data cloud service APIs or marketing tools you use - such as Google Analytics, you can pull in all your data into one streamlined, smart data warehouse.
Seamlessly connect to any business intelligence tool you need to help you visualize or analyze your data in just minutes, so you can right away export and share valuable insights across your organization.
It’s easy and simple to transform data using simple SQL in Panoply’s built-in SQL workbench to get your analytics done quickly and efficiently. Don’t know SQL? No problem, just connect Panoply to a BI visualization tool.
Panoply learns as you use it - saving and caching your queries, and optimizes them to save you time across all your data analytics reporting tasks. Similarly, it adapts server configurations to accommodate greater scalability to solve the issue of concurrency, which means your queries will get results fast even if others are running queries at the same time.
Panoply is like having a personal data engineer and data base administrator on hand 24/7. It does the heavy lifting for you by automatically backing-up and sorting all your uploaded data neatly and clearly into tables and node clusters so you and your data engineering team don’t spend hours on data transformation, re-indexing, and schema modeling.
Panoply offers FAQs, how-to documentation, in-product chat, a friendly community of Panoply users, and even our very own Data Architects that you can use should you need any help.
Easily upload data yourself, no need for savvy tech skills, help from IT or engineering resources - you don’t even need to know SQL to get started, in fact almost 75% of our clients are non-technical. Panoply does all the heavy lifting for you thanks to our data warehouse automation engine.
“A great way to manage your data.”
- Natasha S, Marketing Ops Manager
Panoply automates the ingestion of any diverse data sources and makes tables clear, configurable, and immediately queryable. It also seamlessly connects you to any BI tool you need so you can start visualizing, analyzing, and sharing data insights in just minutes.
“As the lead analyst on a small startup team where data is imperative to our success, Panoply has been incredible."
- Justin M, Data Analyst
We’ve accelerated and optimized the querying process with machine learning. Panoply saves you precious time and resources, and makes sure your data is up-to-date and ready to be shared.
“Easy, fast and reliable”
- Vitali M, Head of R&D
As with any AWS cloud-hosted solution, responsibility for security is shared between Panoply and AWS.
Panoply is SOC 2 certified and in adherence with HIPAA protocol guidelines, in addition, it rests on Amazon’s AWS, which complies with standards such as: PCI-DSSL SOC 2, SOC 3, FISMA, and FedRamp.
We take multiple precautions to ensure that all data is safe and secure.
Security measures are taken regularly and frequently to make sure Panoply is using the latest and greatest in security protocols.
Smart cloud data warehouse automation manages the data pipeline to save you time and resources.
Our AI-powered solution is based on an ELT process that uses natural language processing to automate extract, load, and transfer processes to save you endless hours of coding and modeling for data ingestion, integration, and transformation.
Panoply can ingest data from over 100 data integrations, including databases, APIs, file systems and Panoply's SDK for pushing data from any current and future data source into Redshift, which is all done through Panoply.
Adaptive schema changes at real time along with the data. You don't need any prior knowledge and changes are seamless. Just load data in, everything else is automatic.
Panoply automatically performs common transformations, including the identification of structures & semi-structured data formats like CSV, TSV, JSON, XML, and many log formats – and immediately flattens nested structures like lists and objects. Structured data can also be transformed into different tables with a one-to-many relationship.
Panoply automatically reindexes the schema and performs a series of optimizations on the queries and data structure to improve runtime based on your usage.
Panoply offers several tools for automated maintenance of your analytical infrastructure, but also provides transparency and full control over all processes, enabling you to apply changes manually when needed.
Panoply utilizes statistical algorithms to inspect query and dashboard runtime over selected data to constantly look for ways to optimize query performance. For example, popular queries and views are automatically cached and materialized.Learn More
Multi-cluster replication allows the compartmentalization of storage and compute. The number of available clusters scales with the number of users and the intensity of the workload, supporting hundreds of parallel queries that are load balanced between clusters.
Panoply exposes a standard JDBC/ODBC endpoint with ANSI-SQL support to allow instant, seamless connection to any visualization or business intelligence tool, such as Chartio, Looker, and Tableau.
Panoply is constantly running periodic processes to mark the data and optimize the storage based on your usage. Full and incremental backups are automated so you don't have to schedule them.
Panoply automatically scales up and down based on the data volume. Scaling happens automatically behind the scenes, keeping your clusters available for both reads and write, and thus ingestion can continue uninterrupted. When the scaling is complete, the old and new clusters are swapped instantly.
Panoply automates the vacuuming and compressing of tables to help improve Redshift database performance, continuously analyzes tables to better utilize the queries its receiving, and give you fresh metadata.