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Big data and Artificial Intelligence (AI) have brought about a major transformation in the way technology can be used to streamline business processes and operations. By performing complex analytical tasks powered by systematically extracted information, the big data architecture has proven to be a highly effective resource for identifying patterns, determining preferences, and predicting behaviours with utmost accuracy and precision.
However, for most organizations, the business analytics landscape remains dominated by the discipline of data mechanics. By merely focusing on data collection, mining, and storage, they tend to incur the huge opportunity cost of losing out on the most important data analysis outcome - value. In fact, it wouldn't be incorrect to state that without deriving value or gaining insights, unleashing the true potential of big data analytics and artificial intelligence breakthroughs would not really be possible.
This is precisely why changing the way AI and big data technologies are approached within the business environment needs to be our primary concern for the future.
Deriving value through action
The solution of leveraging data appropriately lies in the initiation of credible action. When focused, targeted, and measured, actions can bring about substantial changes across both, B2B and B2C verticals.
Using action as an instrument of deriving value from data involves:
Operationalizing various data analytics tools and employing them to get practical, dynamic, and workable information.
Lending context to all the insights acquired by mining and viewing them through the prism of data-based scalability.
Creating business models which use real-time prediction and interactive artificial intelligence to enhance efficiency.
Utilising data to strengthen long-term business perspectives instead of deploying it to decipher short-term technicalities.
Adopting processes like time-series data and streaming analytics in order to make optimal but transformative gains.
Developing cognitive models to include inputs from decision makers who can use data and AI to deliver strategic outcomes.
To put it simply, the concepts of big data and AI should not just be relegated to a non-functional storage corner. Rather, organizations should use them to monitor behaviour, observe patterns, and thereby make actionable predictions.
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The future of big data and AI
In an era of growing complexities, the future of big data and AI would be entirely dependent on how efficiently organizations are able to adopt an action-based approach and integrate it within their systems. Relying solely on collecting data that can be used later is not going to be enough. Interventions would have to be made to derive value out of it.
This veritable shift in paradigms can only happen when data and artificial intelligence basics are put to work.
To begin with, the obsession of businesses to hold on to a massive amount of unexploited data lakes will have to be eliminated. This would need to be replaced by the ideals of machine learning through which relationships between different data sets can be discovered and reconstructed. Furthermore, the specificity of the captured data will have to be enhanced so that it can be maneuverer by AI to drive customized business growth.
In other words, for both big data and artificial intelligence - a modern approach based on consistent action will have to be followed. It is only the notion of this action which can enable businesses to take long strides in a data-driven world.
After all, the future of big data and AI does indeed boil down to just one thing - values that are backed by action!
