Get More Value From the Data You Collect in Snowflake
Customer Company Size
Large Corporate
Country
- Worldwide
Product
- Anodot
- Snowflake
Tech Stack
- AI/ML
- Data Warehousing
- Real-time Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Real Time Analytics
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Predictive Maintenance
- Real-Time Location System (RTLS)
- Supply Chain Visibility
Services
- Data Science Services
About The Customer
The customers of Anodot are companies that generate a large volume of data and require real-time monitoring and analysis. These companies span various industries such as fintech, ecommerce, gaming, adtech, and streaming. They have millions of customers across the globe and must manage millions of daily business metrics involving product usage, application performance, APIs, log-ins, and payment gateways, among others. These companies use Snowflake warehouse for their data storage and management needs. They require a solution that can handle the volume and complexity of their data, provide real-time alerts on mission-critical anomalies, and reduce the time and cost of incident resolution.
The Challenge
Companies are generating more data than ever before, and traditional dashboards are unable to keep up with the volume and complexity of the vital business data collected. This is particularly true for companies using a Snowflake warehouse. The businesses served by Anodot have millions of customers across the globe and must manage millions of daily business metrics involving product usage, application performance, APIs, log-ins, and payment gateways, among others. Traditional manual business monitoring solutions cause significant delays of at least 24 hours or longer in detecting and resolving critical incidents, which threaten to impact customer satisfaction, brand equity, and the company’s bottom line. Transactional and customer experience data is too volatile for static monitoring. Since business data is complex and dynamic, AI/ML-based autonomous solutions are critical for achieving business outcomes and avoiding blind spots. Static monitoring approaches based on dashboards, and manual thresholds aren’t sensitive, robust, or agile enough to withstand this challenge. AI-based early detection of revenue issues and business system failures is nonnegotiable.
The Solution
Anodot’s AI-driven platform uses patented technology to learn the normal behavior of business metrics. It can automatically detect any deviations with zero configuration burden or margin for error. Anodot provides companies using Snowflake the tools to detect and diagnose issues early, resolve them quickly, and take preemptive actions before they turn into crises. This is in stark contrast to the standard BI scenario of using dashboards and manual investigation that can’t keep up with vast data sets. Anodot’s patented correlation engine correlates anomalies across the business for holistic root cause analysis and the fastest time to resolution, leading to significantly improved availability and customer experience relative to traditional dashboards. Anodot is entirely autonomous, which is critical when dealing with large-scale Snowflake datasets as there’s no need to define what data to look for or when and no manual thresholds to set up or update. When the business needs change, operators create new use cases on the fly across the entire spectrum of Snowflake warehouse data.
Operational Impact
Quantitative Benefit
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