Analytics

Keep the bigger picture in mind as you build and use your analytics dashboards. Between devices, websites, applications, online service providers, and platforms of all kinds, modern businesses rarely have a single data source to analyze in our continuously connected world. That’s why how information is presented is almost as important as the quality of the information itself, making the difference between leading with confidence or simply flying blind.

Continuous evaluation—the process of ensuring a production machine learning model is still performing well on new data—is an essential part in any ML workflow. Performing continuous evaluation can help you catch model drift, a phenomenon that occurs when the data used to train your model no longer reflects the current environment.

The data lakes concept has come back into popular focus with Amazon Athena, an innovative, serverless solution. But does it fit into your organization’s data stack? This article covers Amazon Athena capabilities, pros and cons, competitors, and use cases.

When you’re providing APIs to your customers, you want to ensure they are getting value from them. At the same time, the best APIs are designed to be fully automated without requiring human intervention. This can leave your customers in the dark on whether your API is even being used by the organization and if you’re meeting any SLA obligations in your enterprise contracts.

In the previous posts in this series, we have discussed Kerberos, LDAP and PAM authentication for Kafka. In this post we will look into how to configure a Kafka cluster and client to use a TLS client authentication. The examples shown here will highlight the authentication-related properties in bold font to differentiate them from other required security properties, as in the example below. TLS is assumed to be enabled for the Apache Kafka cluster, as it should be for every secure cluster.

How vulnerable is your sensitive data? Your data policies may put this information at risk of being breached. An ad hoc approach for dealing with this data makes it difficult to maintain your organization’s cybersecurity. Data obfuscation holds the key to improving your security and making it easier to use your data, but it must be driven by your policies to be effective.

Are you asking yourself the question “what is no-code”? You’re not alone. The concept sounds almost too good to be true: developing your own software applications without ever having to learn a programming language like Java or Python. Even your most technophobic employee can become a star software developer thanks to the proliferation of no-code development tools.

How can you tell when your organization needs to start building a modern data stack? Orchard Analytics provides technical data team services on flexible contracts. Reach out to Phil to learn more. The software abundance problem created the need for data tools, and now -- surprise -- there’s an abundance of data tools.