Data Complexity And Velocity Are Growing – Why That Doesn’t Have To Be Bad
Ever since the dawn of this decade, the business world has been enduring game-changing transformations in almost every sector. The COVID 19 pandemic left a trail of disruption that mandated the shift to digital channels by businesses everywhere. Even airlines, that could not fly even a single passenger, managed to put some revenue on their balance sheet by diversifying digital retail options for their loyalty programs. As normalcy is gradually being restored, the digital traits embraced by businesses are likely to remain a dominant factor in deciding market competitiveness in the future.
But with increasing digital penetration, comes the added growth in complexity and velocity of enterprise data. Is that good or bad?
Studies estimate that the volume of enterprise data will reach a staggering 2.02 Petabytes in 2022, up from the roughly 1 Petabyte volume experienced in 2020. You might point at the cloud as the end-to-end solution to handle explosive data growth in a business. But did you know that Gartner expects 75% of an enterprise’s generated data will be processed outside their centralized data center or cloud infrastructure? The rise of edge computing networks, IoT, smart devices, and other modern digital assets along with the proliferation of high-speed internet courtesy of 5G will result in enterprises having to deal with data having complexity levels far greater than they have ever imagined. To make the case more challenging, the volume of data will be complemented by an increased velocity of generation.
Do you need to worry about the explosive growth in data velocity and complexity?
In the traditional sense, such a prolific growth rate would set off alarms in ops and data management teams. Measures might be contemplated to contain the growth. However, this combination of speed and complexity is not as bad as you may think it is for enterprises today. In fact, several industry leaders have found ways to grow profitably by not obstructing this growth combination. Here are 4 ways in which businesses can flourish by allowing their enterprise data pools to expand rapidly and with increased complexity:
Discover deeper insights
With more data across the enterprise now available, different departments or business functions can dive deep into previously uncharted territories in their operational ecosystem.
For example, when we consider the case of smart factories or manufacturing plants, manufacturers suddenly have greater visibility into granular facets of their production units. Predictive maintenance data from sensors can help them be prepared for upcoming service or replacement schedules. By connecting this equipment health data to the resource management data stream, they can forecast budgeting and resource allocation metrics well in advance. This would not have been possible had they stayed with basic data generation and analytics strategies that did not expand the data pool over time.
Uncover revenue opportunities
Understanding your operational workflows better is just one part of the picture. The other top-line part is the revenue optimization and new revenue stream discovery capability. By better managing data and deploying insights for decision-making at the right customer-facing channel, enterprises can drive more revenue opportunities faster.
For example, deep-dive analytics into social media activity, past shopping history, budgetary preferences, etc. can help an eCommerce website offer additional items as recommendations to shoppers which they are more likely to purchase. This influence of data in cross-selling as well as in other up-selling initiatives helps in driving more revenue purely driven by growth in data complexity and velocity. In fact, as the data builds up, these recommendations become more powerful and personalized.
Make decisions faster
Data-driven decision-making in today’s business environment is a tough initiative primarily because of the large number of business information systems involved in the digital ecosystem of a business. Interdependencies and the impact of interleaved processes need to be factored in when decisions are made. Traditional data processing and management strategies that focus on a linear model of data generation, acquisition, and processing will be grossly inadequate to help in accurate decisions moving forward.
When a growing number of complex data streams from even the most granular of business components are brought under the purview of data operations at speed, more magic can happen. This comprehensive view of data helps decision-makers move in a direction guided by trusted decision frameworks driven by insights generated from massive volumes of fast and complex data at a near real-time pace.
The future of digital initiatives will always be guided by innovations spearheaded by emerging technologies like Artificial Intelligence and Machine Learning. However, for AI initiatives to become more resilient, they need to be trained with a wide range of data sets and decision algorithms. This is where increasing data complexity and velocity can become a critical differentiation factor.
AI systems can be fed with vast volumes of data with complex constituents. Moreover, the increased velocity of data streams will ensure that the AI systems would have exposure to constant real-time insights. The AI can grasp and add this heft to their response modeling capabilities. In other words, data complexity and velocity can help in molding a better innovation ecosystem powered by AI within enterprises.
We have seen how complexity and velocity growth in enterprise data is useful for businesses in the long run. However, the real challenge here is that most enterprises do not have the means to accommodate, store, and manage the influx of complex data sets at speed. They may struggle to apply the data analytics strategies necessary to get the most bang out of their data buck. They often need access to best practices and modern data tools that help manage their transition to becoming a data-centric organization effortlessly. This is best achieved when the enterprise’s data initiatives are guided, managed, and maintained by a knowledgeable partner like Ellicium. Get in touch with us to know more about driving better ROI from your data investments.