Data science
fromTNW | Data-Security
4 hours agoWhy data quality matters when working with data at scale
Data quality should be prioritized from the start to prevent costly issues later in data engineering projects.
Western Union is six months into a migration of 900 to 1,200 applications that run across a 3,900-core server fleet. The decision to move came during a period of re-invention at Western Union, a 175-year-old company that is currently working to become more customer-focused and therefore is open to new suppliers to help reach that goal.
The model's other capabilities, including support for multimodal inputs, multiple reasoning modes, and parallel sub-agents for complex queries, could help enterprises build faster, task-focused AI for customer support, automation, and internal copilots without relying on heavier models.
When civilian banks, logistics platforms, and payment processors share physical data center infrastructure with military AI systems, those facilities become legitimate military targets under international humanitarian law - and the civilian services housed inside lose their legal protection.
The IDEA program aims to help organizations make their data infrastructure AI-ready, addressing the challenge of data primarily designed for human use, which is not suitable for AI applications.
DataBahn's AI-driven connectors automatically normalize, enrich, and route telemetry from more than 500 sources to Microsoft Sentinel. DataBahn's Cruz AI engine determines which data to send to the analytics tier and which to the Sentinel data lake for long-term storage. Customers report cost savings of up to 60 percent on Sentinel ingestion thanks to this intelligent tiering mechanism.
A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?