Context Analytics

Harnessing predictive data through machine learning

A significant challenge for any business is finding and leveraging competitive advantages before others even know they exist. That’s precisely what Chicago-based Context Analytics (formerly Social Market Analytics) delivers to financial professionals who rely on it daily to make smarter investments.

The company’s patented technology, Sentiment Engine, has the ability to harness unstructured, yet valuable information embedded in social media streams and provide actionable intelligence in real time.

Asset managers, hedge funds, and brand managers rely on it daily to make smarter investments and more strategic decisions.

Challenge #1: an incredible amount of data to process

Social media platforms such as Facebook, Twitter, Instagram, SnapChat, and even industry-specific networks like StockTwits, represent a significant portion of people’s online experience.

These platforms also generate an incredible amount of data:

• 500 million tweets are published every day on Twitter
• 500,000 new Facebook users sign up every day
• 85 million photos and videos are added to Instagram daily

As Context Analytics’ datasets massively grow in size and complexity, so must the infrastructure that processes it.

Context Analytics is faced with the ongoing requirement to scale their datasets, compute, storage, and network capacity faster than their customers can use the data.

Challenge #2: more customers and more data

At the end of the day, Context Analytics’ customers are all seeking alpha in the name of differentiation and competitive advantage.

“Back in 2012 and through 2014, really, it was about stock symbols. We were exclusively focused on the continuous improvement of our sentiment analysis and the rigorous back-testing of this analysis,” said Context Analytics. “One of the first evolutions of this analysis and testing is our pre-market Edge Reports: a valuable way for our customers and for us to verify that we have the proper data with the proper algorithms, and accurately reflect sentiment tilting.”

From this foundation came Act Two: Context Analytics’ Sentiment Engine. The Sentiment Engine is designed to handle non-purchasable elements like interest rates and brand names, bringing the same value to brand managers that only financial professionals were able to enjoy until that point.

“The focus on creating alpha moved beyond sentiment associated directly with ticker symbols.”

Context Analytics

Context Analytics’ updated Sentiment Engine opened the door to brands and brand managers.

“As our customer base continued to expand, and the sophistication of their use of the platform grew, it became critical for us to provide 100% infrastructure SLAs and, specifically, have always-on connectivity to data providers and to customers,” said Context Analytics. “If we’re not connected, we’re not in business. Period.”

“If we’re not connected, we’re not in business. Period.”

Context Analytics

Challenge #3: A cloud migration with no maintenance window

“The criticality of market data is obvious,” stated George Nelson, former VP of Cloud Services at Deft.“Factor in the unique nature of social media-driven data being always on, and the standard migration or maintenance window no longer applies. All Context Analytics data connections and services had to remain online and available throughout the cloud migration.”

“Context Analytics made their high standards very clear. Nothing short of a robust, always-on platform would be good enough for their clients.”

Lauren Hood

Former Account Manager at Deft

Solution: a Cloud Migration, a Managed VMware Cloud, and Managed Network services from Deft

Deft’s Managed Services team successfully migrated Context Analytics’ data and core processing services from a third-party data center to a Deft Managed VMware Cloud.

Today, we manage Context Analytics’ production cloud out of our flagship data center in Elk Grove Village, IL. We manage their backup and R&D clouds from our presence within the world’s largest data center at 350 E. Cermak in Chicago, IL.

Deft additionally provides Managed Network Connectivity for Context Analytics to data partners, the Internet, and critical customers. The setup is architected to provide dynamic capacity with unparalleled speed and resiliency as demand changes. It’s also optimized for improved security and overall application performance.

Looking ahead

“Having a partner like Deft to handle all aspects of our cloud and network connectivity — including data store redundancy, application migrations, and state-of-the-art network security — who clearly understands the importance of our SLAs, is critical to our success,” said Context Analytics. “It’s cliché to say we can now focus only on our work, on our applications and research — but we can, and we do.”

“It’s cliché to say we can now focus only on our work, on our applications and research — but we can, and we do.”

Context Analytics

“Working closely with the entire Deft team is a solid foundation for our success,” said Context Analytics.