Five Ways to Beat the Trading Platform Data Bottleneck

The #1 Issue Facing Deployments: Data Agility For banks, accessing trading platform data has become a bottleneck. Enabling teams that work with trading platforms—creating more data volume, and requiring massive volumes of data from apps like Summit or FIS/Sunguard Front Arena to more development and test environments: quickly and securely flow to developers, testers, risk management, data analysts across environments so they can build new apps, integrations to counterparty systems, and adapt to industry change is now the #1 challenge. For example, MiFID II places a substantial burden creating potentially petabytes of more granular time stamped trading data and adding more fields for reporting. PSD II mandates stronger integration, requiring banks to open their payments Copying full cuts of production data to dozens of development, test, and risk infrastructure and some data assets to third parties. Basel III requires internal modelling environments is putting the brakes on processes—from compliance risk management teams get seamless access to their trading platform, for building to innovation. Banks need more, not fewer non-production environments and testing new risk models around market, liquidity and counterparty credit populated with the latest trading data to cope with change—but practically risk. And all of it takes place with the backdrop of GDPR, that puts individuals doing so is nearly impossible. back in control of their data—in turn requiring internal teams to bolster how A raft of industry measures, like MiFID II, PSD II, Basel III, as well as general privacyfocused regulations like GDPR are putting further pressure on development they manage it, refresh changes to it, and mask it across their production and non-production landscape. A Blueprint For Breaking Through The Data Bottleneck Take the pressure off DBAs with self-service access to trading data Access to data, shouldn’t mean development teams are waiting days for a DBA to fulfil a data request, while also burning DBA time meeting a barrage of tactical asks. Deploying a self-service portal for data enables any team interacting with trading platform data to refresh their data at any point in time, whether throughout automated APIs, or interactive self-service—without manual, administrative support. Use data virtualisation to refresh data efficiently across non-production environments Data volumes are growing exponentially—making it increasingly difficult to extract and update for downstream developers, test, and modellers. Data virtualisation enables teams to cut non-production data footprints by up to 80-90% by storing virtual copies of data. The benefit isn’t just lower storage cost—it’s faster data refresh too.