Only a few years ago, 5G was introduced as a technology that could change the world. Telecom companies such as Nokia, Verizon and Huawei have demonstrated how to achieve 5G.
In just a few years (and thousands of hours of work, behind-the-scenes testing and trials), 5G has become more than just an idea. It is now a full-fledged technology available to businesses and consumers around the world.
One of the most commonly discussed business applications in 5G is how to support and enable the Internet of Things (IoT). IDC predicts that there are 55.7 billion connected devices worldwide, collecting all types of data and distributing it to cloud or edge IT systems.
5G and IoT are all profitable technologies, but only useful if you can store, manage, use, and analyze the data you collect to provide meaningful insights. This means that the cloud and edge, and all support technologies, are expected to help businesses understand this data.
Nick Hoskins, Cloudera’s Australian and New Zealand country manager, believes 5G will drive innovation, with two key forces: increasing data volume and network speed.
“When we talk to our customers, we listen to the fact that they want to collect all this incremental data, but as the data moves, we gain insights from that data faster and in real time. Promote. This is important for companies to stay competitive and improve customer service. ”
“When thinking about the edge now and in the future, companies want to be able to gain real-time insights at every touchpoint and ingest large amounts of data from thousands of devices to navigate the data lifecycle. . 5G services support it. “
He states that traditional business intelligence insights often do not match the business needs of an organization, so streaming analytics are critical to providing insights before an “accident” occurs.
He points to a large retail chain as an example. Of course, retailers can collect data about customers and purchasing habits from point-of-sale terminals. However, the focus is on understanding customer online behavior and IoT across the connected supply chain.
“Retailers are thinking about processes and production cycles to support and understand customer demands in real time. There are two ways to collect that data, such as getting data and analytics from a data warehouse, etc. It’s a traditional retail source, but more and more data is being collected on the move through sources such as IoT partner systems. “
Whether the data is moving or stationary, the data needs to be directed somewhere. Both multi-cloud and hybrid cloud infrastructures provide an extensible means for storing and analyzing data. In particular, on-premises infrastructure may not be flexible enough to handle workload spikes.
Organizations that need ultra-fast insights may consider Edge, but Edge comes with challenges such as infrastructure costs and limitations.
Hoskins believes that edges will become smarter and more autonomous as technologies such as machine learning go through edge solutions. This is becoming more common in industries such as healthcare and even in the fight against financial crime.
“Banks and credit card companies are increasingly relying on streaming data and machine learning for real-time customer marketing, fraud detection, and anti-money laundering (AML) activities,” explains Hoskins.
“Often it retrieves and integrates data from a huge number of devices at the edge. These features discover new suspicious fraud patterns (and develop preventive triggers to identify fraud incidents. ), Helps predict customer needs and determine which offers to offer to each customer in real time. Send alerts to customers in real time about potential fraud to improve the customer experience and make customer complaints. I will reduce it. “
However, for most organizations, hybrid and multi-cloud are the best places for data storage and analytics.
“In both cases (edge and cloud), companies need a data management platform that connects all the dots and helps them work seamlessly across multiple clouds in the data center and even the edge. I think that’s what Cloudera does, and that’s what we do to help. “
Cloudera Data Platform is a big data analytics platform that can process and analyze all the insights that come from the IoT and connected devices. Among them is a feature called Cloudera Data Flow. This is a scalable real-time analytics feature that provides insight and actionable intelligence. It is also important to be able to track the source of the data and the phylogeny of the streaming data to manage and monitor edge applications.
“Many organizations have relied on data to date and have moved to data warehouses and data lakes before meaningful analysis and analysis,” explains Hoskins.
“Some companies are adopting different tools to facilitate real-time insights into streaming data. The downside is that they have yet another silo to understand how to integrate these components. And a new problem arises. “
“Companies need a platform that provides their ingestion transformation queries and predictive capabilities. Integrate them into an end-to-end data platform that supports multi-cloud and hybrid clouds.”
Cloudera’s view of how 5G drives will change across the cloud and the edge
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