Data science
fromTNW | Data-Security
7 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.
"For too long, our industry has treated moving customers like brand new ones. EasyMove flips that model. Our customers shouldn't lose their history, their pricing or their trust just because they're changing addresses."
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.
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.
Too often, IT professionals feel like "order takers" for business groups - told what systems to implement or troubleshoot instead of being asked how technology can solve bigger business problems. Making the leap from support tech to strategic advisor takes time. The people who do it well don't just focus on fixing issues, they learn the business, talk in plain language, focus on results instead of tasks, and look ahead to prevent problems rather than just reacting to them.
This new reality is forcing organizations to undertake careful assessments before making platform decisions for AI. The days when IT leaders could simply sign off on wholesale cloud migrations, confident it was always the most strategic choice, are over. In the age of AI, the optimal approach is usually hybrid. Having openly championed this hybrid path even when it was unpopular, I welcome the growing acceptance of these ideas among decision-makers and industry analysts.
Most businesses, which includes modern ones, invest heavily in technology, but they rarely plan for its eventual and inevitable exit strategy. Generally speaking, companies spend millions on the latest hardware while overlooking the critical phase when those assets reach their end. This lack of planning creates a massive gap in the operational lifecycle of many otherwise successful global organizations. Decisions made at the end of a device's life carry real business risks that can impact the bottom line financially and environmentally speaking.
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?
Salesforce data migration sounds straightforward on paper. In practice, it almost never is. The system goes live, everyone gets access, and nothing seems obviously wrong at first. Then little questions start popping up. A report doesn't quite line up. A dashboard only makes sense after a few extra filters. Sales reps pull numbers into Excel just to feel sure. Before long, Salesforce is technically running, but confidence in the data hasn't caught up.
"If you look at the enterprise, there's just enormous enthusiasm to deploy AI, but the problem is that the infrastructure, the power, and the operational foundation that is required to run it just aren't there," Alex Bouzari, CEO of DDN, told The Register. "And so as a result, it pops up in the financial elements with IT projects getting delayed, the GPUs being underutilized, power costs going up. And so the economics, I think, for lots of organizations don't pencil out because of these challenges."
Developers spend more than 60% of their time debugging and maintaining code rather than building new features, Stack Overflow's Developer Survey reports. If you're running a software development team or building applications for your business, you can use Microsoft Visual Studio Pro to streamline coding workflows with an AI-enhanced development environment that reduces debugging time and accelerates deployment cycles. Best of all, Microsoft Visual Studio Professional 2026 is currently available for only $49.99 (reg. $499.99).
The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.