Anodot recently took part in the 2021 Data Agility Day, an event dedicated to examining how organizations are extracting value from data. CEO and Co-Founder David Drai was joined by David Ashirov, VP of Data at Freshly, where he has worked to build a data stack that departments across the company could leverage to drive business. Ashirov is a senior executive with two decades of experience in data engineering, business intelligence, and marketing.

It’s the second holiday season since the pandemic broke out but, with many brick-and-mortar stores reopened, will it be more like 2020 or 2019? Will shoppers stick to online behemoths like Amazon or will they shop in-store? And how are retailers planning to offer a competitive experience amid ongoing supply chain issues? We partnered with Researchscape to survey thousands of eCommerce companies and consumers in the U.S. about their plans for this holiday season.

On October 4, Facebook and its family of apps, including Instagram and WhatsApp, suffered a global outage of its services that lasted approximately six hours. The massive outage has been blamed on configuration errors in backbone routers that are used to connect network traffic to the company’s data center. Facebook apologized to its 3.5 billion users who were unable to access any of the company’s services during the downtime.

In the first four parts of our series on correlation analysis, we discussed the importance of this capability in root cause analysis in a number of business use cases, and then specifically in the context of promotional marketing, telco and algorithmic trading. In this blog we walk through how to leverage correlation analysis to address the challenges in ensuring a seamless online payment experience by the end-user.

For modern businesses faced with increasing volumes and complexity of data, it’s no longer efficient or feasible to rely on analyzing data in BI dashboards. Traditional dashboards are great at providing business leaders with insights into what’s happened in the past, but what if they need actionable information in real time? What if they want to use their data to estimate what may happen in the future? Companies are taking notice.

When organizations track metrics by the thousands, millions, or even billions, it’s helpful in many ways to understand which metrics have close relationships, meaning when one metric behaves in a certain way, one or more additional metrics can be expected to behave in a similar or opposite way.

AI-based monitoring and anomaly detection is the key to ensuring that businesses can keep pace with the high level of service required for mission-critical applications. Early, contextual detection is a basic requirement for speedy resolution. AI-based monitoring creates more visibility and provides the agility needed to mitigate the outages, blackouts, glitches and issues that do and will happen.

According to a recent Capgemini research, fewer than half (48%) of consumers feel that the connectivity services that they have today adequately meet their remote needs. Still, many CSPs openly admit that they often hear about service issues via social media and sites like Downdetector. And with the fixed/mobile convergence, a negative home broadband experience now has the potential to cause churn for CSPs’ mobile customers too.