In 2012, 2.5 Quintillion bytes of data were created every day, and as Big Data architectures gain adoption the rate of data growth in the enterprise will only increase. Clearly, enterprises don’t have a problem generating data, but getting the most out of this data has been a consistent problem. The challenge is not just in reliably accessing much of this data, but integrating multiple sources of unstructured data, achieving real-time visibility and automated analysis for trends, patterns and anomalies. The implications are wide spread; operational agility is inhibited, business decisions are based on insufficient or stale data, and blind spots in technology performance that lead to repeated incidents and outages. Consider these challenges faced by actual FireScope customers:
- North America’s largest local search, media and advertising company could only extract critical data regarding customer transactions generated by their in-house developed application through considerable manual efforts. This forced business owners to make decisions based on data that could be weeks old, and severely limited their flexibility to use this data in different ways.
- A national pre-paid credit card provider had no visibility into the transaction pipeline between their data center and their partners. Issues with these message busses, at the very heart of their business, had lead to significant financial penalties due to breach of contract.
- A financial services organization’s high-frequency trading business had no insight into the distribution of transactions across their custom-built trading application farm. As the load became imbalanced across assets, or utilization was nearing capacity, trades became delayed or lost, resulting in penalties and revenue losses that could reach millions in a single day.
Each of these organizations turned to FireScope to solve these critical business challenges by delivering automated, efficient and highly accurate collection of this non-standard data into a single Big Data repository. FireScope gave them the ability to analyze this data in real-time to generate alerts when anomalies occurred, deep historic trending reports to evaluate the impacts of iterative changes, and predictive analytics for improved strategic planning. Furthermore, the solution allowed them to correlate this key business data with traditional technology metrics to help them connect the dots between technology performance and business outcomes.
All of this was achieved without the need for custom programming or complex professional services engagements, which meant that these organizations were able to start realizing value from the first day while avoiding the largest expenses related to enterprise software. This white paper will detail how each of these customers solved this fundamental business challenge, and how it transformed the way they operated.