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Top 10 Edge Computing Trends Shaping the Digital Landscape in 2024

Olivia Carter — Mon, 30 Oct 2023 14:05:26 +0000

Data is generated extremely fast in today’s digital world. This pace is pushing cloud computing to the edge and resulting in data processing inefficiencies. By bringing data computation and storage closer to the source, edge computing technology offers benefits like higher performance, speedy response, and scalability. With the emerging cloud computing trends, edge computing will continue to transform the digital landscape in 2024.

Here Are Top 10 Edge Computing Trends We Can Expect to See in 2024:

1. Emergence of Edge-as-a-Service

One of the critical edge computing trends that will be witnessed in 2024 is the evolution of edge computing into a service. Edge computing companies will leverage edge-as-a-service (EaaS) to scale their resources without investing in costly infrastructure. EaaS can facilitate edge-to-edge collaborations, provide edge autonomy and resource elasticity while managing a wide range of cross-node resources for users.

End users can use EaaS to deploy services, intelligence, and computation from edge computing platforms with a lot of flexibility. Some of the areas where EaaS will open new possibilities for businesses in 2024 include asset recovery, predictive analysis, edge device management, and tracking, as well as software and operation automation.

2. Rise of Cloud-Edge Integration

Edge computing improves real-time processes and reduces latency by pushing computation closer to data sources. Cloud computing offers businesses economies of scale and flexible resources by giving them access to computing services like storage, networking, analytics, and databases via the Internet.

In 2024, we’ll see growing integration between edge and cloud computing to facilitate efficiency in the processing and analysis of data. Cloud and edge computing integrations will be crucial in supporting a wide range of applications including the Internet of Things (IoT), autonomous vehicles, and smart cities.

3. Stronger Focus on Data Security

A report by IBM showed that in 2023, the average cost of managing a data breach stood at $4.45 million globally. With several companies planning to invest more in cybersecurity, the focus on data security for edge computing is increasing.

As such, we’ll see edge computing focus more on implementing better hardware security features such as trusted platform modules to give edge devices robust security foundations. Edge computing will also be used to enhance booting security to ensure that edge devices only execute trusted firmware. To improve data security, both at rest or in transit, we’ll see improvements in encryption algorithms.

4. Higher 5G Adoption

Edge computing can boost performance and offer users better digital experiences through 5G networks. 5G offers users high bandwidth, low latency, and higher data transfer speeds. Globally, 5G mobile uptake is set to hit 1.5 billion subscribers by the close of 2023.

In 2024, we’ll see higher adoption of the 5G network. This adoption will lead to the emergence of new use cases for edge computing technologies that were initially restricted by connectivity limitations. Combined with edge computing, 5G networks will change the way businesses operate, enabling them to deliver new data experiences from different data centers.

5. Rise in Deployment of Edge Containers

Edge containers refer to decentralized computing resources that save bandwidth, reduce latency, and improve digital experiences for users. By decentralizing computing, edge containers help companies to decentralize services by shifting critical components to the edge of a network to reduce network costs and improve response time. They also help in redistributing traffic to other containers using a single IP. As companies seek to meet customer demands, we’ll see increased deployment of edge containers in 2024.

6. Application of Edge Data Analytics

In 2024, we’ll see increased adoption and application of edge data analytics. Edge data analytics leverage intelligent clustering and real-time stream processing to generate comprehensive reports on edge items. These analytics help companies to overcome bandwidth, lengthy data transmissions, and latency. Edge analytics also offer companies contextual insights to support decision making and identify anomalies, patterns, and optimization opportunities to boost operational efficiency.

7. The Edge-AI Integration

2024 may be the year when Edge AI becomes a reality. As edge computing decentralizes data processing, AI could make it easier for companies, governments, and organizations to handle huge amounts of edge data through AI models and machine learning algorithms. This will lead to real-time data analysis and processing and reduce bandwidth requirements and latency.

8. More IoT Edge Computing Solutions

2024 will be the year when more intelligent, high-performing, IoT edge computing solutions launch. IoT facilitates data exchange and efficient interconnection between multiple devices, allowing for efficient collection of data at edge. IoT also enables edge computing devices to interact and respond to actual conditions and events for better decision-making. 2024 will see increased deployment of edge-based platforms in IoT platforms.

9. Blockchain-Edge Solutions

More digital solutions leveraging blockchain technology and edge computing will emerge in 2024. Blockchain maintains data integrity while offering security and immutability within distributed edge environments. This alleviates fears of data counterfeiting and unauthorized access. Decentralized economies, asset tokenization, and digitization are some of the new opportunities blockchain will facilitate in edge environments.

10. Growth in Edge Computing Data Centers

Data centers continue to pioneer the development of novel architectures that adapt to edge computing demands. Agile, scalable, and robust solutions that integrate seamlessly with the growing data landscape are continually being developed.

For this reason, edge computing will continue to transform data centers in 2024. Data centers leverage edge computing to build tech infrastructure that can handle the influx in data traffic to facilitate quick, efficient, and seamless data processing close to data generation points.

Final Thoughts

Edge computing has been shaping the digital landscape in the past. This will continue in 2024 as the edge computing trends above take center stage. By decentralizing data processing, this technology will continue to provide foundational capabilities that will underlie business strategies that rely on AI, cloud computing, blockchain, and data in the coming year.

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SoftServe Achieves Document AI Expertise in Google Cloud Partner

Tech Research Online — Tue, 09 Feb 2021 15:55:09 +0000

A leading digital authority and consulting company, SoftServe and Google Cloud Premier Partner has achieved the Document AI Expertise. They have received this in the Google Cloud Partner Advantage Program.

The Expertise from the program reinforces SoftServe’s technical experience in using artificial intelligence (AI) and machine learning (ML) to reveal crucial insights from text data and documents. The company has also recognized the proficiency of AI and ML for document insights. It increases operational efficiency, inform decision making, and improve customer experience using Google Cloud.

Also Read: Twitter and Google Cloud are Expanding their Strategic Partnership to Improve Data Insights

“Our AI/ML competencies applied to Document AI customer use cases allow enterprises to efficiently scan, analyze, and understand their documents while reducing the costs of manual data entry and collection,” said Andrew Greene, Associate Vice President, Cloud Partnerships & Alliances at SoftServe.

“We help our customers discover key insights to better understand the value in their documents by simplifying unstructured data using Google Cloud’s optical character recognition (OCR) and Cloud Natural Language technology.”

Google Cloud’s Document AI Expertise is bestowed on partners demonstrating success. They should be able to leverage a suite of document processing tools including pre-process, digitize (scan), classify, and extract text entities from documents.

Google Cloud Document AI helps businesses improve operational efficiency by automating the process of extracting information in the form of structured data from unstructured documents. Hence, it makes this information securely accessible and useful to customers.

This gives businesses the ability to turn document data into actionable insights. They can do this by combining the power of Google Cloud artificial intelligence, machine learning, and predictive analytics to generate insights and drive smarter decisions.

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Twitter and Google Cloud are Expanding their Strategic Partnership to Improve Data Insights

Tech Research Online — Mon, 08 Feb 2021 10:15:36 +0000

Google Cloud has officially announced that they are expanding a new, multi-year, strategic partnership with Twitter. Under this partnership, both the company will deepen their initial work and move their offline analytics, machine learning, and data processing.

Besides, Twitter will be shifting their workloads to Google’s Data Cloud which will allow a faster analysis of data and improve the experience for everyday users of their service.

Behind every Tweet, there are a series of data points that helps the team understand how people are using the service, and what types of content they might want to see.

Also Read: Ford and Google Will Reinvent Connected Vehicle Experience

Their database is huge as the platform ingests trillions of events, runs tens of thousands of jobs and processes hundreds of petabytes of data every day. All this data is then processed.

With companies expanded partnership, Twitter is adopting Google’s Data Cloud and along with that, they will include Dataflow, BigQuery, Cloud Bigtable, and machine learning (ML) tools.

These tools will power the rapid growth of the data ecosystem and enable faster data-informed decisions. Along with this, it will also deeper ML-driven product innovation.

Hence, the company will have the ability to democratize data access by offering a range of data processing and ML tools. With the help of Google’s Data Cloud, they will be able to better understand and improve how Twitter features are used.

Parag Agrawal, CTO of Twitter, said “Our initial partnership with Google Cloud has been successful and enabled us to enhance the productivity of our engineering teams. Building on this relationship and Google’s technologies will allow us to learn more from our data, move faster, and serve more relevant content to the people who use our service every day. As Twitter continues to scale, we’re excited to partner with Google on more industry-leading technology innovation in the data and machine learning space.”

Thomas Kurian, CEO of Google Cloud, “Helping customers manage the entire continuum of data – from storage to analytics to AI – is one of our key differentiators at Google Cloud.”

“It’s been phenomenal to watch this company grow over the years, and we’re excited to partner with Twitter to innovate for the future and deliver the best experience possible for the people that use Twitter every day.”

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Finastra launches Next-Generation Fusion Data Cloud Platform for Financial Services

Tech Research Online — Mon, 26 Oct 2020 13:48:20 +0000

Today, Finastra announced the availability of its next-generation Fusion Data Cloud. The suite is designed to help financial institutions to grow revenue, improve customer engagement, digitize processes for efficiency, and decrease manage risk.

Also Read: IBM Announced a New Spinoff to Accelerate its Cloud and AI Growth

Fusion Data Cloud provides:

Data ecosystem that is supported by secure Microsoft Azure technology and Fusion Data Cloud. This will enable banks to share their data with leading fintech from external data sources. These solutions are integrated with Finastra core products to enable fast delivery, drive scale, and provide flexibility to increase customer value.
Actionable insights created by artificial intelligence (AI) and machine learning (ML) algorithms that predict and prescribe analytics and delivery of real-time decision-making service. For example, potential churn and better understand customer behavior.

Connected experiences: Business Intelligence (BI) tools provide analytics visualization and omnichannel interaction with six AI- and ML-driven BI solutions. For example, gain an operational and 360-degree view based on payment data based on mortgage data.

Eli Rosner, Chief Product and Technology Officer at Finastra, says “Finastra is uniquely placed to connect fintech, financial institutions, and third parties to accelerate the creation of innovative data solutions for our customers and our partners. Those that embark on this data journey with us can kick start their move towards deeper customer insights and business growth. Our open ecosystem revolutionizes the innovation process – advanced analytics can generate crucial insights for financial institutions to help them personalize and transform the customer experience, reduce risk, and amplify business results.”

Justin Taylor, Managing Director at Vector Risk said, “Without access to Finastra’s Fusion Data Cloud, we would need to take each institution’s unstructured data, understand it, clean it, and apply a structure. This could take many months, if not years to achieve. With Finastra managing the data securely for all, it’s a win-win for all parties. We’re excited to be live in the FusionStore with our app.”

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