Skip to content
Tiatra, LLCTiatra, LLC
Tiatra, LLC
Information Technology Solutions for Washington, DC Government Agencies
  • Home
  • About Us
  • Services
    • IT Engineering and Support
    • Software Development
    • Information Assurance and Testing
    • Project and Program Management
  • Clients & Partners
  • Careers
  • News
  • Contact
 
  • Home
  • About Us
  • Services
    • IT Engineering and Support
    • Software Development
    • Information Assurance and Testing
    • Project and Program Management
  • Clients & Partners
  • Careers
  • News
  • Contact

How the Edge Is Changing Data-First Modernization

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. To reap the benefits, organizations need to modernize with a decentralized data strategy that delivers the speed and flexibility necessary for driving smarter outcomes for the business.

The concept of the edge is not new, but its role in driving data-first business is just now emerging. The advent of distributed workforces, smart devices, and internet-of-things (IoT) applications is creating a deluge of data generated and consumed outside of traditional centralized data warehouses.

At the same time, the availability of 5G connectivity and an influx of robust, cost-effective edge processing power have made it possible to decentralize data storage and real-time analytics processing power and position it closer to the actual data source.

IDC estimates that there will be 55.7 billion connected IoT devices by 2025, generating almost 80 billion zettabytes of data at the edge. In addition, IDC projections show worldwide spending on edge computing reaching $176 billion in 2022, an increase of 14.8% over last year.

A recent survey conducted by IDC and sponsored by Lumen Technologies and Intel Corporation indicates that two-thirds of global IT leaders are implementing edge computing. IDC predicts that by 2023 over half of new enterprise IT infrastructure deployed will be at the edge; by 2024 the number of apps at the edge will balloon by 800%.

Momentum is surging because edge computing opens up a whole new world for data-first business, reducing latency, relieving bandwidth pressures, and enabling fluid data movement. As a result, business users are treated to insights that weren’t possible before, with enhanced agility to act on data in the moment.

“With all this storage and compute capacity at myriad edge locations, we now have the ability to solve new problems that couldn’t be solved before,” says Denis Vilfort, HPE’s director of edge marketing. “The nature of the old centralized data center basically imputed a round trip tax that stopped certain things from being possible at the edge.”

With more compute power at the edge, here is a snapshot of what’s possible:

Manufacturers are collecting data directly from industrial assets such as fluid pumps or oil rigs distributed around the globe or out in the field, driving insights used to optimize processes, identify bottlenecks, keep tabs on quality issues, and even initiate proactive maintenance and take corrective actions in near real time.

  • Retailers are tapping sensor data and in-store camera images to identify potential theft across multiple store locations to augment human intervention.
  • Autonomous vehicles draw on copious amounts of sensor, camera, and lidar data to power the machine learning and algorithms used to drive the car and react to changing road conditions.

“If we can take the data center with us, we can do all kinds of things that weren’t possible before,” Vilfort explains. “You can’t move these types of applications to the cloud for processing, because you don’t have enough time to process real-time data streams.”

How edge refines data strategy

To support these new data-first business strategies, organizations need to rethink and redefine traditional data warehouses and architectures with an eye toward decentralized strategies that still encompass centralized controls such as governance and built-in security along with frictionless data movement. “We don’t want to apply a centralized paradigm to a decentralized problem,” Vilfort adds. “That’s the promise of edge computing.”

HPE GreenLake brings the benefits of a cloud experience — specifically hardware, software, orchestration, metering, and billing — serving as a unified edge-to-cloud platform that brings end-to-end visibility to a decentralized data estate. The HPE Ezmeral data fabric and file and object store, delivered as a service through HPE GreenLake, integrates files, objects, NoSQL databases, and multiple types of streaming data from existing platforms, including edge locations, into a unified layer to drive analytics applications and promote more intelligent insights.

HPE’s unified analytics capabilities work across a diversity of data types, reaching from the edge to hybrid cloud, in support of decentralized use cases while the machine learning operations (MLops) platform helps automate the end-to-end processes surrounding artificial intelligence (AI) and analytics pipelines, from planning through model development, training, deployment, and monitoring.

Getting edge-to-cloud data strategy right

Turning data-first business from strategy to reality starts with taking stock of where data resides — determining the data footprint — since data is really where the action is. “Being data-first means we get to look at the edge first and then figure out what goes into the data center, the colocation center and so on,” Vilfort explains. “We need to know how much data there is, where it’s going, how long we need to keep it, and who can see it — this is a data conversation and a data management challenge.”

From there, other best practices emerge:

  • Heighten the focus on security and governance. As data analytics and AI and machine learning workloads are increasingly directed to the edge, the attack surface for potential security breaches vastly expands. Data-first modernization requires organizations to redefine practices to build in security from the onset, not as an afterthought. They also need to pay close attention to long-standing issues, from data sovereignty to adherence to regional and global regulatory requirements.
  • Establish cross-functional teams. It’s important to establish data stewards that hail from different parts of the organization to define and scope data needs as well as to identify all relevant data sources to get a true picture of the decentralized data estate and specifically edge locations.
  • Create a center of excellence (CoE). Even though data strategies and data insights are orchestrated from the edge, it’s still important to cross-pollinate ideas and create and promote shared data policies. A CoE can also foster support for strategies, enlist executive buy-in, and help drive the necessary cultural change.

Edge environments promise to open up a whole new world of insights and innovation. Yet with the possibilities comes a paradigm shift requiring organizations to modernize with a decentralized data strategy that propels data-first business.

Click here for more information.


Read More from This Article: How the Edge Is Changing Data-First Modernization
Source: News

Category: NewsMay 16, 2022
Tags: art

Post navigation

PreviousPrevious post:How the Sports and Entertainment Industry Is Reinventing the Fan Experience and Enhancing Revenues with Computer VisionNextNext post:Experts Offer Guidance on Balancing User Experience and Security in Data/File Transfers

Related posts

Barb Wixom and MIT CISR on managing data like a product
May 30, 2025
Avery Dennison takes culture-first approach to AI transformation
May 30, 2025
The agentic AI assist Stanford University cancer care staff needed
May 30, 2025
Los desafíos de la era de la ‘IA en todas partes’, a fondo en Data & AI Summit 2025
May 30, 2025
“AI 비서가 팀 단위로 지원하는 효과”···퍼플렉시티, AI 프로젝트 10분 완성 도구 ‘랩스’ 출시
May 30, 2025
“ROI는 어디에?” AI 도입을 재고하게 만드는 실패 사례
May 30, 2025
Recent Posts
  • Barb Wixom and MIT CISR on managing data like a product
  • Avery Dennison takes culture-first approach to AI transformation
  • The agentic AI assist Stanford University cancer care staff needed
  • Los desafíos de la era de la ‘IA en todas partes’, a fondo en Data & AI Summit 2025
  • “AI 비서가 팀 단위로 지원하는 효과”···퍼플렉시티, AI 프로젝트 10분 완성 도구 ‘랩스’ 출시
Recent Comments
    Archives
    • May 2025
    • April 2025
    • March 2025
    • February 2025
    • January 2025
    • December 2024
    • November 2024
    • October 2024
    • September 2024
    • August 2024
    • July 2024
    • June 2024
    • May 2024
    • April 2024
    • March 2024
    • February 2024
    • January 2024
    • December 2023
    • November 2023
    • October 2023
    • September 2023
    • August 2023
    • July 2023
    • June 2023
    • May 2023
    • April 2023
    • March 2023
    • February 2023
    • January 2023
    • December 2022
    • November 2022
    • October 2022
    • September 2022
    • August 2022
    • July 2022
    • June 2022
    • May 2022
    • April 2022
    • March 2022
    • February 2022
    • January 2022
    • December 2021
    • November 2021
    • October 2021
    • September 2021
    • August 2021
    • July 2021
    • June 2021
    • May 2021
    • April 2021
    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    Categories
    • News
    Meta
    • Log in
    • Entries feed
    • Comments feed
    • WordPress.org
    Tiatra LLC.

    Tiatra, LLC, based in the Washington, DC metropolitan area, proudly serves federal government agencies, organizations that work with the government and other commercial businesses and organizations. Tiatra specializes in a broad range of information technology (IT) development and management services incorporating solid engineering, attention to client needs, and meeting or exceeding any security parameters required. Our small yet innovative company is structured with a full complement of the necessary technical experts, working with hands-on management, to provide a high level of service and competitive pricing for your systems and engineering requirements.

    Find us on:

    FacebookTwitterLinkedin

    Submitclear

    Tiatra, LLC
    Copyright 2016. All rights reserved.