Last Updated on March 24, 2023 by
If you are pursuing training in data science, you should know about the biggest trends or megatrends as colloquially referred to in the industry. In this article, we bring you the three megatrends that directly affect the way enterprises are operating today and delivering results based on their roadmap.
Megatrend 1: Cloud computing
What big data training can do to cloud computing in the coming years?
Currently, all enterprises are looking at acquiring big data to scale their operational efficiency through agile processes and resilience. While storage costs continue to soar higher, the recent developments in big data integration and cyber resilience are showing ample results to boost the job market for certified big data analysts in India.
The era of cloud computing precedes the introduction of big data management and analysis by at least a decade. The contemporary rise of cloud computing tools has given a massive incentive to the way IT analysts and data engineers have latched onto big data.
Today, almost every cloud native company is using big data to run its operations. By adding newer cloud computing concepts, enterprises are able to project their big data applications onto key business domains where innovations are required.
A great example of big data and cloud computing synergy is seen in the IT and IT ops market where a large number of managed service providers are fundamentally utilizing advanced programming and automated coding to process the enormous volume of data for addressing queries. These could be mostly founded on the public cloud, allowing enterprises of any size to leverage big data advantages at a budget best optimized for their scale.
Megatrend 2: Fog Computing
The growing number of IoT and sensors has produced so much data in recent years that it is now impossible to mine, analyze, store and re-engineer all of it with traditional computing techniques. So, almost coinciding with the rise of big data trends, we saw a massive evolution in the world of IT based data management techniques.
In 2011, fog computing arrived to solve the challenges pertaining to evolving needs of data storage and data applications for users of cloud computing. With big data training, you would be able to understand the basic differences in how centralized and decentralized distributed information architecture frameworks work. By reducing the computational load for computing, big data analysts are able to gain a high level of latency, especially in remote working conditions where security and resilience are needed.
In 2030, 90% of the IT ops could completely switch to fogging techniques.
Megatrend 3: Robotic Process Automation or RPA
What is the biggest buzzword that every enterprise is looking to gain in the modern era?
Yes, you are right, it’s digital transformation. The digital transformation can be measured by analyzing the degree to which a company has managed to automate its processes and replaced mundane human work with robots or AI tools.
Chatbots and AI based document scanning tools are the best examples of this transformation. But, 90 percent of the companies are not generating ROI from their AI investments. RPA is able to fill in for the gaps with big data tools and analytics that decision makers utilize to drive their digital transformation goals.
Experience with RPA for big data is a must have to grow exponentially in the future. In today’s big data market, RPA has emerged as a megatrend, sweeping past all that the AI and machine learning models are possibly demonstrating theoretically.
Together with AI investments, RPA software adoption has increased massively in the last 5 years, bringing a lot of simplicity to the way enterprises function. The alignment between RPA and Big data is so important in the current context of back office document processing, IT automation, AI-based robotics, and website management, it is clear that without RPA training with big data architecture, it is impossible to optimize digital transformation for any enterprise.
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