Systems | Development | Analytics | API | Testing

When monitoring cloud resources, there are several factors to consider.

Data modeling is not about creating diagrams for documentation sake. It’s about creating a shared understanding between the business and the data teams, building trust, and delivering value with data. It’s also an investment. An investment in your data systems' stability, reliability, and future adaptability. Like all valuable initiatives, it will require some additional effort upfront.

Sports and gaming companies are forging ahead with the use of data science as a competitive differentiator. According to an industry report, the global AI in media and entertainment market size was valued at $10.87 billion in 2021 and is estimated to grow 26.9% annually until 2030.

Which metrics should you be tracking in a revenue cycle KPI dashboard? Here are the ones necessary for assessing your financial health at a glance.

A data lake is the perfect solution for storing and accessing your data, and enabling data analytics at scale - but do you know how to make the most of your AWS data lake? In this week’s blog post, we’re offering 10 data lake best practices that can help you optimize your AWS S3 data lake set-up and data management workflows, decrease time-to-insights, reduce costs, and get the most value from your AWS data lake deployment.

There are millions of data products out there, some successful and others…less so. But the truly standout data products are the ones that change users’ behavior. You know you’ve built something special when your users start forming habits around your product. The question is, how do you create something that stands out in a sea of data products? We believe it comes down to one thing: a relentless focus on delivering user value.

Amazon Redshift is a completely managed Data Warehouse, offered as a cloud service by Amazon. It can scale up to petabytes of data and offers great performance even for complex queries. Table of Contents Its columnar nature with Postgres as the querying standard makes it very popular for analytical and reporting use cases. These days it is very common to use Amazon Redshift as the backbone Data Warehouse for highly reliable ETL or ELT systems.

In a world where user experience and IT support can mean the difference between hitting or missing your ARR marks, businesses have to find smarter ways to build workflows and support their IT departments. That’s where companies like ServiceNow come into play. A few years back, we created our ServiceNow SpotApp, a pre-built analytics template to help companies analyze and understand their data—so they can increase efficiencies across their complex IT environments.