Harness the Power of Big Data with Panoply: A Full-Service Solution for Collecting, Managing, and Analyzing Information with Ease

Harness the Power of Big Data with Panoply: A Full-Service Solution for Collecting, Managing, and Analyzing Information with Ease

TL; DR: Panoply, founded in 2015, is an all-in-one data management solution valued for its affordable price points, ease of use, and extensibility. Used by some of the world’s most data-driven companies, the full-service solution offers an agile approach to uncovering actionable insights backed by hands-on support from a team of data experts. Moving forward, Panoply will continue to introduce native data-source connectors, such as its recently announced LinkedIn Ads experience.

Media outlets have made a big deal over big data in recent years — and for good reason. These enormous volumes of information — generated by daily transactions, social media activity, industrial equipment, and IoT sensors — can be analyzed to reveal key decision-making insights.

But few good things in life come easily, and when you’re dealing with data of this magnitude, the burden is especially difficult to bear. Extracting value from massive amounts of data requires a ton of storage and processing power, not to mention analytics capabilities.

Enter Panoply, an all-in-one data management solution built on top of Amazon’s secure and flexible infrastructure that stores data across numerous AWS cloud regions and availability zones. Anyone can use Panoply to collect, manage, and analyze data via an intuitive and fast setup process — and they can do so affordably.

Panoply logo

Panoply is a turnkey data management solution designed with analysts in mind.

“While we do serve enterprise customers, our bread-and-butter, classic customer is one who has big data needs but doesn’t have the budget to support a data team,” said Jason Harris, Data Evangelist at Panoply. “It could be a data analyst who has killer skills in front of a SQL Workbench and can string tables together to build a report, but doesn’t want to manage a data warehouse.”

With Panoply, customers enjoy an agile approach to uncovering actionable insights backed by hands-on support from an expert data team. Moreover, the end-to-end cloud data warehouse and management service automates the data pipeline, saving time and resources while remaining secure, stable, and compliant. Built for anyone working with analytics, Panoply enables data-driven decision-making in real time.

All-in-One Data Management at an Affordable Price Point

Panoply was founded in 2015 by data analysts Yaniv Leven and Roi Avinoam, two seasoned data management professionals from Tel Aviv, Israel. The pair identified a gap in the market when it came to serving founders, CEOs, CTOs, startups, analytics teams, and data scientists who have significant data needs but lack a budget to hire a data team or develop a data stack.

Amazon Redshift, a hosting and data warehouse solution, was launched in 2012 as part of AWS. But while the solution is known for being nimble, fast, and extensible, Jason said it’s also quite complex to set up and maintain. Eager to create an affordable, easy-to-use alternative with the same speed and agility, Yaniv and Roi built Panopoly on top of Redshift.

Panoply's mascot completing data management tasks

Let Panoply handle the heavy lifting required for big data management.

Since then, it’s evolved to offer even more functionality. “If you were to ask me a year ago, I would have said we are a cloud data warehouse,” Jason said. “Today, we’re a full-service data management solution.”

According to Jason, data management entails collecting, managing, and analyzing data. On the collection side, Panoply offers everything you need to funnel data from multiple sources into one place.

The company features out-of-the-box integrations, or “connectors” with more than 150 databases, cloud services, and applications, including Google Analytics, MailChimp, Salesforce, and virtually any database, from MongoDB to PostgreSQL. “If there’s an integration that you have that we don’t support natively, we have partnerships with tools like Periscope and Stitch, which can push the number of connectors as high as 2,000.”

An Agile Approach to Uncovering Actionable Insights

When it comes to managing data, Panoply employs machine learning to save users time they would typically spend on coding and modeling for data ingestion, integration, and transformation. “We ensure everything is running as smoothly as possible,” Jason said.

Then comes analyzation. To that end, Panoply offers integrations with popular business intelligence tools like Tableau, Chartio, Looker, and Power BI. “You can connect any business intelligence solution to our software so that you can seamlessly build dashboards and reports in a flash,” Jason said.

But Panoply doesn’t stop there. The data management solution also optimizes these platforms to increase speed and performance, bringing analytics within reach more quickly. As evidence of this, Jason cited a case study detailing how Kimberly Clark’s EMEA Omnichannel team uses Panoply to speed data collection and aggregation.

“The one-two punch of using Panoply to speed up my results in Tableau was the best possible solution for my team,” said Helena Carre, Analytics Lead for the EMEA Omnichannel team at Kimberly Clark, in the case study. “It gave me the things I needed — speed, automation, efficiency, flexibility — without blowing up my budget, increasing my headcount, or adding unneeded complexity. It continues to be a great complement to my existing resources.”

In one instance, Carre’s team was spending more than eight hours a week assembling data for a simple weekly Tableau report, which cost the company $250,000 every two years to produce. With Panopoly, the team can create and update the report with zero human intervention.

Hands-On, Personalized Support from Data Experts

Overall, Jason — who works closely with customers on a daily basis — said users value Panoply for its pricing and ease of use. “They like our vast library of data connectors, and they like the simplicity in achieving super fast results,” he said.

Extensibility is also a major factor. For example, Motorsport.com — a media company operating more than 40 online publications in 17 languages — signed on with Panoply to streamline one data collection process before discovering a range of use cases for the product.

“They started using us to monitor article performance, but then they realized they could use Panoply to monitor ad spend,” Jason said. “Then they started bringing in their subscription data, then the marketing side said, ‘This is great, we can monitor how people are interacting with us.’ And before you knew it, there were multiple use cases.”

Speed, agility, affordability, and support combine for a customer experience that’s hard to beat.

Jason said he sees this story replicated again and again among customers who decide to implement Panoply’s smart data warehouse throughout their data stack, streamlining data management organizationwide.

Support also serves as a differentiator for the company, which boasts a team of experienced data analysts who are ready and willing to tackle the most challenging problems. Rather than spitting out generic responses, Panoply’s customer service team prescribes detailed solutions to individual problems.

“I’ve heard it time and time again — customers say we take the time and care to help optimize their queries,” Jason said. “We really roll our sleeves up and give concern to what the person is asking.”

Future Plans: Improving the Data Ingestion Engine

As for what the future holds, Panoply plans to do everything in its power to enhance the user experience, which includes expanding its already robust catalog of data connectors.

In July, the company introduced a new data source — LinkedIn Ads — as well as refinements to its Twitter Ads data source that ensure content is up-to-date and relevant to users.

On the product side, Jason said Panoply is always improving its data ingestion engine, ensuring data are being made available for analysis as quickly as possible.

“It doesn’t matter if it’s structured or unstructured data — we’re always adjusting it and making it available in minutes,” he said. “We will continue to focus on speed and agility.”

Christine Preusler

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