We are in an age where the entire business world across the globe is controlled and managed remotely. We have entered into the Data Age where data analytics has become an essential service. We are already seeing the emergence of two categories of organizations – One that uses data to make things happen and the second category that may not be able to sustain owing to their refusal to evolve into a technologically and digitally competent organization.
Survival in the market now demands that organisations increasingly rely on new technologies like cloud, IoT, machine learning and more. Businesses need to design and streamline their data strategy to use the growing data resources. This implies a greater need to analyse the burgeoning data to make insightful business decisions that promote sustenance. A recent data survey revealed that 86% of the organisations are unprepared for the Data Age and 66% of IT and business managers report that half or more of their organisation's data is dark (untapped, unknown, and unused).
Data-driven technology is Integral to Business survival
Data analytics is no longer an optional tool but the only tool for organizations to stay ahead of the competition. With such radical changes in the business process dynamics, the types of challenges faced are also changing. Hence, the focus on developing a high-end digital infrastructure to drive digital transformations is the only solutions to majority of the challenges across all sectors.
Scaling the digitally-driven business demands implies round-the-clock Working-mode
Traditional approaches such as data silos, lakes, working across countless legacy systems and fragmented cloud services create massive data volumes. As a result, organizations spend billions of dollars and countless man hours to extract the true value of this data. Moreover, organizations that are moving to cloud are facing further complications with services coming from different places.
Hence, there is an increasing need for a solution/platform that is designed to accommodate all the challenges rising because of an always-online, always-connected world of today.
In order to thrive in this Data Age, organizations have to integrate traditional models with evolving technologies to eliminate barriers between data and action and, thereby, seamlessly maneuver the transition. With such a hybrid infrastructure, organizations will possess the potential to investigate, monitor, analyze and act on data in one place while gearing up for the data challenges of the future. Furthermore, the right infrastructure will enable businesses to unlock previously untapped value by identifying the correlations between data stored throughout different databases and systems. It is also beneficial in enabling systems and teams to evaluate and respond to contingencies and solve critical pain points across organizations.
Data Analysis supports the process of developing critical and meaningful insights that organizations need at every point of growth. It helps organizations create productive data strategies which serve as guides to adopt a digital infrastructure that is compatible and progressive, thus, evolving with the always evolving needs of the end users. Incorrect data strategies lead to rapid transformation that may or may not be profitable causing massive complexities. It can be the biggest drawback when translating the data into action. Organizations that are able to capture, make sense of their data and channel them using the apt tools will be much better-armed for a smooth transition into the Data Age.