Growing Demand for New Skills in the Digital Economy
Today’s corporate environment is evolving. Atoms are giving way to bits. Online is replacing in-person interactions. Physical is being replaced by virtual. The Fourth Industrial Revolution, as it is known, will “fundamentally disrupt the way we live, work, and relate to one another,” according to the World Economic Forum.
The majority of us understand this change as the “digital transformation,” which, in the words of Forbes, “reshapes every facet of the business.” Information Technology (IT) is the cornerstone of this change, and it necessitates a fundamental reevaluation of IT’s position within the larger business.
IT’s primary responsibility in the past was to support the business. IT was supposed to create tools to support the operations of departments like sales, finance, and finance. IT is now a key component of the goods and services that make up the modern digital economy. Since IT is a crucial component of these services, it must be included in the team that develops and launches them. This change in responsibility is best described as “IT’s role used to be: support the business.” The time has come to do business. To support the greater corporate transformation, IT must go through its own digital transformation.
The following are some areas where IT must up its game to fulfil the demands of its new role:
A New Approach to the Application Lifecycle
It is obvious that the rate of application development needs to increase. Too many IT firms are unable to satisfy the needs of the digital economy because they are bogged down in cumbersome procedures like the Information Technology Infrastructure Library (ITIL).
Application groups frequently employ agile development as a test run to accelerate development. DevOps is frequently adopted by operations teams to facilitate more frequent deployments with less human labour.
Both are actually necessary, and both ought to be included in the lifetime of a new application. As seen in the accompanying figure, the new lifecycle includes cloud computing, integrated business and IT collaboration, agile development, and DevOps.
To acquire digital capabilities, the entire application lifecycle must be optimised. Without addressing the complete application lifecycle, fixing one component will only result in one group operating at digital speed while the others maintain their traditional pace, with no overall improvement in speed.
Welcome to the IoT World.
The majority of IT companies focused their apps on a single client device five years ago: a web browser. With the introduction of the iPhone and the ascent of smartphones as major computing devices, that rigid strategy began to fall apart.
Today’s IT businesses must provide support for a wide range of devices due to the emergence of new edge computing. Depending on their role and function, they have a wide range of form factors. As electronics undergo their own Cambrian Explosion, this trend will only intensify. IT professionals will remember fondly the time when their biggest issue was locating a Javascript framework that offered cross-browser compatibility in five or ten years.
Processing Events in Real Time
Based on the features of the environment they operate in, many IoT devices emit data in erratic patterns. It must therefore be ingested and processed by apps in real time because data arrives in an unpredictable manner.
For this requirement, “functions as a service” or, to put it more plainly, “serverless” is the new application paradigm. All of the major cloud service providers provide frameworks that make it simple to transmit event data to serverless operations in addition to serverless capabilities.
This application category will expand significantly as the previously mentioned IoT revolution intensifies.
Machine learning replaces data warehousing.
Due to the millions of devices and billions of events, IT businesses must have a strong understanding of data storage, management, and analysis.
The conventional approach of analytics, which relied on the extraction of data into a separate relational data warehouse, is no longer adequate due to the size, pace, and nature of this data. Additionally, business units must react to data analysis considerably more quickly, necessitating the deployment of end-user analytical tools that can delve deeply into event stream data.