Finding relationships between disparate events and patterns can reveal a common thread, an underlying cause of occurrences that, on a surface level, may appear unrelated and unexplainable. The process of discovering the relationships among data metrics is known as correlation analysis. For data scientists and those tasked with monitoring data, correlation analysis is incredibly valuable when used for root cause analysis and reducing time to remediation.
With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics.
We are excited to announce the general availability of cross-cluster search and replication on Elastic Cloud. These two features allow you to search and replicate data across clusters in different regions and cloud service providers globally, making it possible to: Be sure to dive in and learn more about the features below! Cross-cluster search lets you search remote clusters across multiple regions and cloud service providers. When you break down regional data silos, you can get insights faster.
As your Elastic usage increases and your use cases expand, it's important to know the benefits and cost savings that you can achieve by running Elasticsearch as a service. But since every Elasticsearch implementation can vary by use case and deployment model, it can be complicated to tackle on your own. So with that in mind, we are excited to share the Elastic Cloud Value Calculator.
Are you interested in performing time series forecasting or anomaly detection, but you don’t know where to start? If so, you’re not alone. There is an overwhelming variety of libraries, algorithms, and workflow recommendations for these tasks. As a Developer Advocate at InfluxDB, the leading time series database, I’ve researched time series data science methodologies and best practices for forecasting and anomaly detection.
In an expanded and commercial industry space new and innovative opportunities are presented to retail organizations from several novel sources of data, log files, and from transaction information to sensor data to achieve unmatched value and combative advantage in their respective fields. In order to attain customer satisfaction and to flourish their business, people across the organization must be empowered, so that swift and accurate decisions can be attained.
