• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

Enterprise Architecture Blueprint for Utilities Part 1

Thorsten Heller / 3 min read.
November 6, 2020
Datafloq AI Score
×

Datafloq AI Score: 83.67

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/ew97m

The Good, The Bad and the Ugly

Some days ago, I was co-hosting a webinar on Piecing together the Enterprise Architecture Puzzle for Utilities . During our virtual roundtable, our guests including Klaus Wagner, (Enterprise Architect, Netze-BW / EnBW) and Rinse Veltmann (Director Solutions, Energyworx) discussed an enterprise architecture blueprint for the Utility 4.0 future and highlighted specific related topics including:

  • Challenges or shortcomings with this kind of an Accidental IT , that is quite often the As-Is architecture for many utilities.
  • Strategies such as Make vs Buy , Cloud vs. Data Center , Best-of-Breed vs. 1-Stop-Shop or Pull IT vs. Push IT .
  • Principles and concepts like Event Driven Architecture (EDA), API-driven development, domain driven design (DDD), cloud native, microservices and data mesh.

Our lively debate, in which the panelist shared their views on what was good and bad architecture emphasized: What characterizes a good or bad architecture? What does good and bad mean? Does good , bad and even ugly mean the same for all of us? And can we measure it? See it? Feel it? Or otherwise sense it?

So let me start by sharing some of the typical indicators and symptoms of a bad architecture from my point of view:

  • Monoliths determine the processes, routines or services, meaning the utility has to adapt the systems’ capabilities.
  • Siloed applications offer no or minimal standardized integration capabilities and make entirely digitized processes impossible.
  • Core systems are heavily customized and therefore expensive to update or upgrade.
  • Custom built or developed solutions serving commodity functionality (i.e. CRM, ERP, etc.).
  • Critical solutions need special knowledge or expertise to operate, manage or adapt and create vendor lock in.
  • Black-box applications nobody (internally or externally) wants to touch anymore as no one knows how those work.
  • Adaptions (i.e. some new fields in an API) take several months, are costly and slow therefore down innovation.
  • Applications provide overlapping or competing functionality and lead with that to inconsistent decisions, processes or data.
  • Systems have been thickened, meaning new requirements are always realized in the same application by the same vendor, even the functionality would have belonged into the domain of another.
  • Underlying infrastructure (i.e. storage, messaging, integration) cannot be scaled elastically or require substantial investments to meet the upcoming requirements to handle big energy data in almost real time.
  • IT landscape is built on a huge variety of (partly aging) technologies, different (maybe antiquarian) architecture styles or (old-fashioned) proprietary integrations create enormous operational complexity and fragility.
  • Each solution or system uses different mechanism to manage security or data privacy and its own logging & tracing framework.

At Greenbird, we work to simplify the complexity of big data integration for utilities to kickstart their digital transformation. We have put together an e-zine with articles which speak to these questions. Download the digital magazine to get more information on enterprise architecture, the build vs buy debate, understanding the digital integration journey and how to simplify the IT/OT relationship.


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

Working with utilities, we sometimes meet an IT landscape that has evolved (or even mutated) over many years with lack of architectural management or strategy. That is what I call an accidental IT or accidental architecture .

A system of siloed systems:

  • Defined by business units’ specific needs and preferences for a given solution or vendor,i.e. a cloud and web-based CRM for customer service, but a on-premise classical client-server GIS implementation
  • Often centered around some big monolithic applications, i.e. CC&B (Customer Care & Billing)
  • With many manual, batch-style or file-based integrations,i.e. file based meter reading exports from HES to MDM and from MDM to CC&B,i.e. manual synchronization for metering point info in MDM and GIS
  • With unclear or random separation of concerns , i.e. VEE for profile-based meters done in the CC&B and VEE for smart meters done in MDM,i.e. Asset management for meters / metering points done in CC&B, asset management for grid infrastructure done in GIS

There might be by far more symptoms or examples for accidental IT or The Bad, and the Ugly . But it is more important to think about, how to fix and how to handle the shortcomings.

Therefore, my next blog posts in this EA blueprint series will focus on The Good . What is good architecture, how can we measure it and establish a set of architecture KPIs. Ready to Read part 2?


Originally published here

Categories: Cloud, Strategy
Tags: architecture, digitalisation, digitization, energy analytics, strategy

About Thorsten Heller

CEO @ Greenbird, data- and cloudifying Utilities with Utilihive - the Energy iPaaS and Energy Data Mesh - to drive Sustainability and the Energy Transition. CEO, Co-Founder and Chief Innovator / Disruptor @ Greenbird - a VC backed B2B SaaS - providing Utilihive, the leading Energy iPaaS (#eiPaaS) and Energy Data Mesh. Utilihive is the Domain specific #iPaaS purpose-built for Utilities driving the Digital Transformation and empowering the Smart Grid, Smart City and Industrial IoT.

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app Apple application Artificial Intelligence BI Big Data business CEO China Cloud Companies company content costs court crypto customers Data digital future Google+ government industry information machine learning market mobile Musk news Other public research revenue sales security share social social media strategy technology twitter

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app Apple application Artificial Intelligence BI Big Data business CEO China Cloud Companies company content costs court crypto customers Data digital future Google+ government industry information machine learning market mobile Musk news Other public research revenue sales security share social social media strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!