The Top 5 Data and Analytics Trends For 2021

Artificial Intelligence and Machine Learning are not new concepts. Both have been around for a good number of years now and many organizations have at least dipped their toes in the water when it comes to AI and ML. But 2021 looks set to see AI and ML drive data and analytics forward in a way that may not have been obvious in the pre-Covid era.

As part of the global response to Covid-19 more than 500 clinical trials were implemented which combined AI, ML with data and analytics to help health professionals understand what had happened and how – but crucially to predict future events as well. This ‘crystal ball like’ phenomenon allowed scientists to make accurate, data-driven decisions in the best way forward. They were no longer adapting their route through a changing landscape. They were able to clearly see the landscape and thus navigate it in a smooth, controlled manner.

2021 is the year that business leaders are increasingly adopting the same approach. So, here are 5 top trends for data and analytics leaders to look out for over the coming months:

1. Cloud will make the landscape clearer

It’s predicted that by 2022, more than 90% of global enterprises will rely on hybrid cloud solutions. And yet, with data and analytics following this trend, leaders are still wasting valuable time and resources by failing to get to grips with how to implement efficient cost-effective systems. The challenge for data and analytics leaders is to change their focus from simply looking at cost to placing more emphasis on performance requirements. Get that part right and efficiency, savings and increased ROI naturally follow.

2. The decline of dashboards

Traditional dashboards have had their day and are being replaced by in-context data systems that stream relevant insights to each user rather than expecting the user to find them. Automated data stories will replace the need for users to point-and-click their way through their journey. These stories will be driven by AI, ML and analytics which have pre-processed what drives each user into action. Science will not completely replace knowledge and considered opinions, but it will enhance them.

3. Decision intelligence

Decision intelligence focuses on making accurate and efficient decisions based on understanding how actions lead to outcomes. Machines process data and information in the same way as the human brain, but are able to handle far more detailed information in a much faster manner. Neuromorphic hardware analyzes a chain of events in a stoic, unemotive way, evaluating existing data and insights and predicting actions and reactions to create a decision-making model that is far quicker and more accurate than the human brain can manage. The result is the end of ‘decision paralysis’ which affects 67% of CEOs. Instead leaders can make bold, confident decisions which will boost efficiency and increase ROI.

4. Augmented data management

Augmented data management systems use AI to examine vast amounts of operational data in a time-efficient manner. Identifying anomalies in large datasets, resolving data quality issues and tracing specific data directly to its origin. This process produces metadata to give leaders and decision-makers valuable insights into their business which can then be turned into practical changes that move the business forward.

5. Better, faster more scalable AI

According to research, AI will contribute up to $15.7  to the global economy by 2030 with a 26% increase in GDP for local economies. Businesses are turning to reinforcement learning and distributed learning to create more flexible systems that can handle complex business data. New chip architectures that can be deployed on edge devices such as smartphones, laptops and tablets reduce the reliance on centralized systems and will make AI far more scalable over time.

Better, faster AI and ML systems give organizations key data at their fingertips. Machines can do in a matter of minutes, what a team of humans might take weeks to achieve. In addition, they are not susceptible to human error.

Data and analytics are one of the most important tools available to business leaders. They examine performance and drive innovation. The future of work is in AI and ML. Customer experience decides brand loyalty. When it comes to data that drives improved customer experience, why not let machines do the heavy lifting and provide data and analytics insights and metadata far beyond what we would have even thought possible just a few years ago? 

Furthermore, AI and ML are now able to work seamlessly alongside each other to the betterment of both. From operations to employee experience, machines are creating a holistic approach to the future of work that ensures less focus, effort and resources are being spent on collating data, and more are being spent on actioning the outcomes of it.

Agile Fuel recruits and supports high-quality dedicated engineering teams that work out of Ukraine and are tailored specifically to each client’s technical requirements, culture, and communication requirements. The agency is stack-agnostic, focusing on finding the right people for each client irrespective of how commonplace or esoteric they may be. By taking care of recruiting, HR processes and administration, Agile Fuel allows its clients to focus on direct engineering management and team culture.

Find out how Agile Fuel can help you by sourcing a dedicated engineering team to give you the latest in cutting edge data and analytics solutions.

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