Nearly every business function now has a ‘stack,’ a group of tools used to achieve that function. It’s true for productivity, communication, marketing, development and more. But what makes this group of tools a ‘stack,’ and how should you understand, plan, and optimize yours?
Software development is often broken down into front end, back end, and full stack. In this post, we’ll clarify what the terms refer to and cover the kinds of tools, languages and skills each domain covers, before looking at how your business can get the talent you need. We’ll start with definitions:
IoT security is as multilayered as IoT implementations themselves. See the matter from an attacker’s viewpoint and the reason is obvious: if devices are secure but the network is weak, they’ll gain control of the devices via the network. If both are solid but the applications that manage or control them are poorly-protected, that’s their in. It’s a case of one building, several doors. And for attackers, IoT is a huge opportunity: all that computing power, great for productivity, if only we could access it.
Data warehouses exist to give users rapid, complex data analysis. They’re far better at this than traditional databases, and use different architectures and data management techniques. There are several effective cloud-based solutions that can provide businesses with insights derived from their data. Selecting from and, particularly, implementing these solutions can be complex. In this post, we’ll give an explanation of what a data warehouse is, explain what they’re for and how they differ from other forms of data storage, and look over the biggest players in the space before talking about our own experiences managing data migrations between data warehouse platforms.
IIoT is the Industrial Internet of Things: sensors and analytics devoted to monitoring, analyzing and managing industrial processes. It’s not limited to factories and transportation — think property and asset management, business process automation and more. It promises to be transformative, and the process of transformation has already begun: initially, we’ll see sharp improvements in the efficiency and reliability of structures and processes already in place, but within a decade we can expect to see industry operating primarily as an interlocking web of IIoT implementations.
Big data is the technology that underlies many of our most important advances. Enabled by machine learning and connectivity, large tranches of data can now be mined for insights rapidly and used to improve effectiveness, reduce waste or accelerate processes.
