Xenomorph Adds Python to TimeScape

Xenomorph has integrated Python scripting language into its TimeScape analytics and data management product, in an effort to accommodate users who had experience deploying Python for data analysis, according to Brian Sentance, CEO of the company.

"They wanted to combine that way of working with gold copy data, data that's been cleansed and validated so there's an end-to-end process from the data coming in ... right through to it being cleaned up and made fit for purpose, and being brought into the program and environment to use for whatever algorithms and strategies, as might be used in risk management for portfolios," he says.

Xenomorph's inclusion of Python language began with one client who wanted to access TimeScape using the language, adds Sentance. The company then extended the capability to other users through a full production release, and now has other firms deploying that, he says.

Python programming language can be used for data validation. Xenomorph's offering makes it easier, with TimeScape, to assemble golden copy data from reference and market data in many kinds of environments, according to Sentance.

"It's really about trying to maximize the usage people make of the golden copy data that's created in our system, so they get the most benefit and efficiency, primarily from not having to do reconciliation," he says. "Everyone views the data in the same spot, whatever environment they want. It's a transparency play."

In April, Xenomorph added a Data Validation Dashboard to TimeScape, enhancing the service's ability to validate and remediate data, comparing pieces of reference data in correct context. The addition of Python language implements management of data more effectively and consistently, says Sentance.

"People want data to be very consistent in analytics," he says. "It's often the derived data that is used for report. If that derived data is generated outside your data management process, it's a lot harder to justify to regulators and auditors. This pulls analytical and derived data into the data management process."