"Anodot shows us an anomaly in real time, and correlates it to a specific event, like a feature update. With Anodot, we know about issues immediately.”

Anomalies are the proverbial needles in a haystack. The problem is that the needle is sitting in an increasingly larger haystack.  Moreover, the subtle anomalies can just slip under the radar and go undetected for much longer.

Find out how Anodot is helping Credit Karma quickly identify abnormal behavior in their time series data and locate the root cause, so that it can be resolved before business suffers and revenue is lost.

Optus Networks Director of New Services Engineering Jason Wong shares how the Australia Telco giant is leveraging the powerful anomaly detection capabilities of Anodot’s AI analytics to proactively address business incidents in real time, protect revenue and keep their customers happy.

Data analysts end up spending a lot of time investigating issues that are hidden within the vast volume of data and events, and often don’t know what to look for.

Should data analysts and other "knowledge sector" employees feel threatened by AI? Here's what industry experts have to say on the subject.

Read the case study to see how Uprise used Anodot to avoid major problems such as server outages.

Whether you’re in it for the game or the commercials, the excitement around the Super Bowl draws people of all ages, all around the world to their screens - many different screens. All that excitement produces a mountain of data. Just as there are few subjects in our world where stats and data are discussed any more than in sports, one of the main sporting events to talk about is  the Super Bowl. When the Eagles and Patriots squared off on Sunday in the most-watched sporting event of the year, nearly 188.5 million Americans will be tuned in, according to a survey by the National Retail Federation – about the same as last year. Collecting Reams of Data On and Off the Field While data has been collected on and around football games since the very beginning of the game, today’s collection techniques are smarter, real time data is the new standard. With new sensors around the stadium and even on a players' pads and helmet collecting real-time data about what is happening on the field, for brands, Super Bowl Sunday means collecting data across many platforms, including  through social media listening tools. The real data driven aspect of the Super Bowl comes from the advertisers. These companies try to get a picture of what people talk about most before, during, and after the game. Advertisers are paying over $5 million on average for a 30-second shot at those eyeballs, says research group Kantar Media. That’s just one side of the game, the second screen has also become a powerful opportunity to reach a highly targeted audiences, whether it’s a big-name brand looking to optimize their high-profile TV ad or a smaller brand simply looking to enter the fray. According to Rubicon Project’s survey of “more than 800 self-described “die-hard football” fans, more than a quarter of NFL fans regularly engage in second-screen content while watching their favorite team on television.” Data-driven Companies Need Real-time Business Insights Today’s environment allows very little margin for error. With Super Bowl ads costing millions of dollars, and their influence able to spur online shopping spikes, lack of detailed awareness of possible glitches can lead to larger losses, both monetarily and reputationally. It’s impossible to manually track the millions of metrics that are generated across today’s digital businesses. Static thresholds for seasonal data are becoming either meaningless or generate overwhelming alert-storms. Dashboards can’t keep up with these sudden spikes, where the data ends up being yesterday’s news. Analytics Makes Sense of the Data It’s in these areas that analytics comes into play. Just as on the field, the data may indicate the likelihood of the success of a play, data can’t reveal all the variables alone, like what a coach may know about a certain opposing player or Tom Brady’s coolness under pressure. While the  Patriots may have believed that the Eagles would run the ball wide, their coach could have decided to run the ball inside. Businesses can draw from this as well when it comes to data analytics. The data can point to  particular anomaly, but the analytics needs to put all the pieces together and make that data into data-driven decisions for the best action to take. Data analysts can’t rely upon what happened in the past will occur again in the future.  Today’s organizations need to leverage data to their advantage – to win a game, to drive revenues, to get better performance results, etc. This data is not just about what is being watched on millions of screens during the game, but what happens daily for piles of streaming data across many different industries. AI Analytics Spots Business Opportunities Before, during or even after the big game, the data gathered about browsing history and purchases, help advertisers to identify who is interested in what and what is likely to have the biggest impact on them. Hence, by applying AI analytics tools, companies can keep their finger on top of developments in advertising campaigns to drive more engagement, allowing not just their Super Bowl ad to have a better return on investment, but their ongoing business operations. The Super Bowl is an exciting game that tens of millions of people around the world will enjoy, and big data is changing the game. Whether it be in terms of trying to predict the most likely winner of the game or how advertising is handled. AI-powered analytics can ensure that advertising platforms, retail customers’ sites and online businesses interact with consumers perfectly and consistently across platforms. Effectively tracking exact customer activity and delivering concise data that is dependable, AI analytics allows you to ensure that  your customers have a best-in-class experience.

In this session at White Hall's BDA conference, AppNexus VP of Engineering Travis Johnson discusses how the company uses Anodot’s AI Analytics for insights about unknown unknowns, to confidently and proactively address incidents quickly.