The amount of data volume and complexity within tech stacks is continuing to increase with no sign of slowing down. As a result, many organizations are facing significant challenges related to tool sprawl and the overwhelming amount of data that needs to be exchanged between all the different systems. The result is this new rapid pace of data which brings a need for faster flow and exchange of information.

Data laying all around an enterprise’s premises and over the cloud is of no use unless it forms part of a bigger and clearer picture. This is what a data stack does by helping enterprises leverage data to its fullest potential- it turns raw data into insights that can be acted on and lead to business benefits. The complicated modern enterprise of today cannot make do anymore with the obsolete ways of data management.

AI has certainly become the hallmark of digital transformation strategy. According to IDC, global AI spending is forecasted to reach $500 billion in 2024 with a CAGR of 17.5%. Likewise, Gartner predicts low-code application platforms (LCAP), robotic process automation (RPA) and AI are fueling the growth for hyperautomation, and the market will reach $596 billion in 2022, up nearly 24%.

AIOps (artificial intelligence in IT operations) in monitoring refers to the convergence of artificial intelligence, machine learning, and data analytics to make IT monitoring a responsive, intelligent, and agile business function. AIOps is not an alternative to DevOps but a great partner to it that provides intelligent insights when integrated with every stage of the cycle.

Waste is never a good thing. And rumblings of an economic downturn, alongside dire warnings of climate change, are making it increasingly necessary to address waste. As a society, we need to reduce consumption, data included. First, we all must acknowledge the high cost of data. Despite the prevailing opinion of the 2010s, data isn’t free. There’s a monetary and carbon cost to keeping data alive.

ITOps and DevOps are technology management practices that have been around long enough that anyone in IT should have a good grasp of what they mean. Here’s our experts’ take on ITOps vs. DevOps.