OpTier announced OpTier Big Data Analytics (BDA), a revolutionary product that changes the game for companies who are inundated with unprecedented volumes of Big Data.
Click here to read OpTier's recent announcement: OpTier APM 5.0 Released
"Through 2015, 85 percent of Fortune 500 organizations will be unable to exploit big data for competitive advantage," said Gartner, Inc. in its "Predicts 2012: Information Infrastructure and Big Data" report published in November 2011. A major reason for this is that it is extremely time-consuming and expensive to cleanse, normalize and infer data relationships through statistical modeling. That time can be not only reduced, but eliminated if contextual Big Data software is employed to capture Big Data with context, generated from transactions at the time of execution.
With OpTier BDA, companies can reduce the time and costs spent on analytics by 50-90% because OpTier’s business transaction-based platform enables immediate, real-time analysis of data that are already in context.
OpTier BDA tracks and analyzes billions of transactions each day. Its patented Active Context Tracking (ACT) technology tracks every interaction from the end-user, through the data center, through the cloud, with very low overhead. It stores each transaction in the context of the business activity such as make payment, search, or purchase, how well it performed, who initiated it, where the user was located, and more. The new product stores Big Data in a Cassandra database, adds new free form analytics that includes any 3rd party data integration and easy custom executive views.
"Big Data is becoming a source of innovation and deep enterprise insight," said Shawn Rogers, vice president of Research at Enterprise Management Associates. "OpTier’s new Big Data Analytics offering addresses the challenges of handling this high volume data by organizing it contextually and quickly making it available to key stakeholders. OpTier’s focus on fast, accurate, quality information is fueling the analytic demands of its clients."
"Big Data is only going to get bigger! Companies need to rethink how they are going to analyze their data and moreover the contextual nature or value of the data they collect," said Mark Thompson, CEO of OpTier. "The alternatives to contextual data are complex, slow, and expensive because they have to infer or guess at the relationships and interdependencies – the who, what, where, information associated with a transaction. However, if you are already capturing business data in context, as OpTier does, you can literally eliminate the guesswork and quickly take advantage of your Big Data."
OpTier BDA offers CMOs, business executives, BI architects and business analysts data that are already in context as opposed to having to connect data from various silos to answer questions such as:
- How are my current customers behaving?
- Where is my highest revenue-generating business location?
- If my application is performing poorly on the Web, what impact does that have on my Call Center?
- How are the customers behaving on existing applications when using a mobile device vs. a tablet or desktop?
- Given my budget, which IT investment will have the largest impact on revenue?
- What improvements in IT performance will have the greatest impact on reducing the churn of high value customers?
OpTier Big Data Analytics is available immediately.
The Latest
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...