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IBM Launches New Class of Analytics Software for Big Data

IBM announced new predictive analytics software that automatically correlates and analyzes big data to help clients embed hyper-intelligence into every business decision.

In addition to generating insights on internal data in a matter of seconds, the software measures the impact of social networking channels and factors this information into organizational decision making.

The software represents a new class of Decision Management capabilities that revolutionizes the way organizations gain, share and take action based on information gathered as part of business processes such as marketing, claims processing and fraud detection. In these, and other data-rich areas – where anywhere from a thousand to five billion decisions are made daily – the software will put forward the next best action to front-line employees ensuring optimal interactions and outcomes.

The new Analytical Decision Management software, part of a series of IBM Smarter Analytics initiatives, helps clients apply automated, real-time analytics into any operational data no matter where it resides, and instantly analyze it to uncover trends and expose hidden paths to growth. As a result, insights can now be automated, socialized and used for predictive decision making.

In a single platform, IBM has combined the power of business rules, predictive analytics and optimization techniques through intuitive interfaces that allow users to focus on specific business problems. The resulting decision can be consumed by existing pre-packaged or custom-built applications, including many applications on the mainframe.

The platform also takes advantage of IBM InfoSphere Streams technology where big data can be analyzed and shared in motion, providing real-time decision making in environments where thousands of decisions can be made every second.

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IBM Launches New Class of Analytics Software for Big Data

IBM announced new predictive analytics software that automatically correlates and analyzes big data to help clients embed hyper-intelligence into every business decision.

In addition to generating insights on internal data in a matter of seconds, the software measures the impact of social networking channels and factors this information into organizational decision making.

The software represents a new class of Decision Management capabilities that revolutionizes the way organizations gain, share and take action based on information gathered as part of business processes such as marketing, claims processing and fraud detection. In these, and other data-rich areas – where anywhere from a thousand to five billion decisions are made daily – the software will put forward the next best action to front-line employees ensuring optimal interactions and outcomes.

The new Analytical Decision Management software, part of a series of IBM Smarter Analytics initiatives, helps clients apply automated, real-time analytics into any operational data no matter where it resides, and instantly analyze it to uncover trends and expose hidden paths to growth. As a result, insights can now be automated, socialized and used for predictive decision making.

In a single platform, IBM has combined the power of business rules, predictive analytics and optimization techniques through intuitive interfaces that allow users to focus on specific business problems. The resulting decision can be consumed by existing pre-packaged or custom-built applications, including many applications on the mainframe.

The platform also takes advantage of IBM InfoSphere Streams technology where big data can be analyzed and shared in motion, providing real-time decision making in environments where thousands of decisions can be made every second.

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Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...