Reverse ETL is an emerging piece of the modern data stack that enables you to productionize your analytics.

Our new Splunk integration enables your team to monitor and investigate your infrastructure data.

Almost all aspects of businesses are transforming to digital and internet-based solutions. It’s happening from the ground up, starting with developers. You’re building applications for your organizations, and you’re racing to get software and services out to the market faster. The faster your company moves, and the more you build, the more likely you need an API gateway governance strategy.

Over a few short months in 2020, COVID-19 accelerated what so many CEOs and CTOs have struggled to do for the past decade: It forced organizations to be agile and adjust quickly to change. Oil and gas companies in particular had to react quickly to get back to onsite work while protecting their workers’ safety. Russell Stewart, host of the Oil and Gas HSE Podcast, recently sat down with some experts from Appian who specialize in our Workforce Safety solution and in the oil and gas industry.

Reports and records. Sales sheets and spreadsheets. Files and financials. Your team has more big data than you can comprehend spread across multiple data sources in more locations than a James Bond movie. Isn't it time you kept this data somewhere safe? Moving data to a data warehouse like Snowflake is like keeping thousands of books in a library or a trove of treasure in an underground vault. Big data, your most prized asset, will be safe and snug.

When you write code, you learn quickly that it can be an exacting process. Spaces and semicolons mean something very different to a computer than they do to us. So what’s the best way to document your API in a way that both humans and machines understand? For starters, here are some practices for naming your API endpoints. Did you know you can generate a full-featured, documented, and secure REST API in minutes using DreamFactory? Sign up for our free 14 day hosted trial to learn how!

You’ve already figured out that your data science team cannot keep developing models on their laptops or a managed automated machine learning (AutoML) service and keep their models there. You want to put artificial intelligence (AI) and machine learning (ML) into action and solve real business problems.

Today, technology drives organizations. We rely on it, which is why a misstep in selecting technology partners and their SaaS solutions can impact an organization in regrettable ways. It can impede your ability to scale in a graceful manner. It can slow down your journey of automation. It can even introduce risk related to compliance or security, depending on the solution. Whenever you decide to buy, a proper assessment of any SaaS provider is crucial.

To accelerate business value and enable a first-class cloud experience for our customers, we continue to shift the focus from passive to active BI with new innovations on the horizon.

ETL, long a mainstay of data integration, is labor-intensive, brittle, complex — and ripe to be supplanted by ELT.