Are they basically just an evolved version of service-oriented architectures (SOA)? Since a microservice must be exposed via an application programming interface (API) for an organization to scale it to new developers, does that mean managing microservices is basically the same as managing APIs? As this article will discuss, the answer to both of these questions is a clear “no” — and companies looking to get the most from their microservices need to understand why.

Continuous integration, delivery and deployment, known as CI/CD, has become such a critical piece in every successful software project that we cannot deny the benefits it can bring to your project. At the same time, containers are everywhere right now and are very popular among developers. In practice, CI/CD delivery allows users to gain confidence in the applications they are building by continuously test and validate them.

There is a common misconception about data-informed decision making. It goes that once we implement the right tools, and figure out how to analyze the data correctly, the data will automatically turn into insights and will translate to better business decisions. It sounds great in theory.

All marketers have to deal with essentially the same problem when managing their online campaigns and looking for the right attribution model: the data they need for evaluation is scattered across various systems, and collecting and collating it takes too much time. If they decide to use solutions intended to help them to handle this problem, they often find such solutions are not, in themselves, enough.

When I speak to people who are thinking about implementing BI, they are often overwhelmed by all the things they could measure. Many start by wanting to measure everything, which doesn’t necessarily help them. That’s because there’s an inherent cost in measuring things – everything you report and track creates an ongoing burden that your organization has to maintain. That’s why it’s important to be selective about what you measure from the get-go.

In our last blog, we talked about developing data processing jobs using Apache Beam. This time we are going to talk about one of the most demanded things in modern Big Data world nowadays – processing of Streaming data. The principal difference between Batch and Streaming is the type of input data source. When your data set is limited (even if it’s huge in terms of size) and it is not being updated along the time of processing, then you would likely use a batching pipeline.

The sole purpose of SEO is to attract search engine traffic to your website.

Predict and measure the ROI of your next website redesign by following this 11-step playbook, compiled from dozens of experts.

Makeover Monday is a global initiative started by Tableau to encourage people to build visualizations. It involves releasing a new dataset each week and letting people reimagine the way it is visualized. It’s a really interesting experience and anyone can participate.

Log management solutions play a crucial role in an enterprise's layered security framework— without them, firms have little visibility into the actions and events occurring inside their infrastructures that could either lead to data breaches or signify a security compromise in progress. Splunk is the “Google for log files” heavyset enterprise tool that was the first log analysis software and has been the market leader ever since.