Sales and marketing analytics is one of the most high-profile focus areas for organizations today, and for good reason – it’s the place to look to boost revenues.
Over the last few years, there has been a mad rush within enterprise organizations to move big data workloads to the cloud. On the surface, it would seem that it’s a bit of a keeping up with the Joneses syndrome with organizations moving big data workloads to the cloud simply because they can.
In this post we’re going to talk about how to integrate Intercom into your mobile apps. The company offers both iOS and Android SDKs and you’ve probably used them before in your different products (we certainly use them in Bugfender).
These days organizations commonly rely upon dozens of databases, applications, and third-party services for powering critical business infrastructure such as web and mobile applications, business analytics, and customer outreach initiatives. Examples of such indispensable technologies include Microsoft SQL Server, Salesforce, and Intercom.
Automation brings incredible value to data teams and hyper-growing companies. It removes hours of sweating over repetitive and mundane tasks, which frees up time for data engineers, analysts, and scientists to get on with more engaging and revenue-generating work. Now, imagine that you can extend the benefits of automation beyond the selected repetitive tasks… to the entire data pipeline.
When we consider performance testing most of the focus of the approach is placed on the script creation activity and making sure that requirements are covered, these are very important parts of your performance testing approach but so is the Test Execution. The frequency at which you run your tests is important and can save you time and effort in your script maintenance. A good performance testing execution strategy gives you the maximum amount of benefit it can by finding performance issues early.
2019 is almost over. The software testing landscape has seen numerous introductions in new testing approaches and innovations at an exponential rate. It has also witnessed the continuation of technological improvement, evolution, and reinvention. As we are progressing to 2020, let’s take a retrospective look at the top trends in test automation and see how we stand after one year.
Today, enterprises need to collect and analyze more and more data to drive greater business insight and improve customer experiences. To process this data, technology stacks have evolved to include cloud data warehouses and data lakes, big data processing, serverless computing, containers, machine learning, and more.
Billions of times each day, application programming interfaces (APIs) facilitate the transfer of data between people and systems, serving as the fabric that connects businesses with customers, suppliers, and employees. Having the right API strategy in place can make the difference between success and failure when it comes to utilizing APIs to deliver results, reduce response times, and improving process efficiency.
