Data Ideology, LLC’s Post

Sharing in case of interest. I think the UK water industry is a fascinating place when it comes to leveraging data and enabling digital transformation. The scrutiny that water companies are under when it comes to controlling pollution discharges, preventing water loss, and the overall EAG agenda is huge. Added to this are the challenges of managing a massive, geographically dispersed asset-base - plant, equipment and connected devices, to control energy consumption and prevent/fix failures. This work has the associated challenges of workforce management. Then layer on top customer experience (commercial and residential), and you have a massive cocktail of challenges and opportunities, all reliant on data. Details of this Data Architecture job at Anglian Water Services below #dataarchitecture #datacareers #utilitiesindustry #datajobs

Data Architect opportunity with international NGO

I'm keen to get your thoughts on something.... I'm currently working with an organisation that are hiring for an Enterprise Data Architect, who when I got the brief for them, they insisted a technical person wasn't needed. So, of course, this is one of the first questions I speak to my candidates about and it's interesting to hear that many people in this space are still getting down with writing code and being technical. 👩💻 I got speaking to an individual and he mentioned that the step-up is all about 'the shift in mindset.' Yes, technical architecture is still very important but the step up means dealing with business and information architecture and understanding the difference is key. Enterprise Data Architecture takes a holistic view and ensures that every component of the business work together for the success of an organisation's aim and objectives. Whereas a Data Architect is hands on with designing and implementing the Data Architecture. Do you have both responsibilities in your current org? 🤔 #enterprisearchitecture #dataarchitecture #data #analytics

Data Architect

The core of Trivium’s Digital Transformation is our Data & Analytics Platform. Especially now we have embarked on our AI journey, having a high quality, reliable, and secure data infrastructure in place is crucial. Are you the Data Platform Architect that can help driving this further?

Data architects play a critical role in managing and structuring data. Explore the career guide to becoming a data architect.

Data Architect 101 for Data Engineers (Complete Guide) Understanding how to build end-to-end data systems can be a catalyst in your career growth as a Data Engineer, let's understand the basics of building a data system 👇🏻 The goal of every data project is to solve business problems! It can be anything from reducing current system costs to building a full-fledged data system helping businesses to make data-driven decisions. Today I want to take you on a journey of architecting a data system, if you are an aspiring data engineer or have been working in this field for a few years, understanding how to architect a data system can help you see the bigger picture. What is Data Architecture? Here is the technical definition you will find in The Fundamentals of Data Engineering Book by Joe Reis and Matt Hoursely Data architecture is the design of systems to support the evolving data needs of an enterprise, achieved by flexible and reversible decisions reached through a careful evaluation of trade-offs. In simple terms, before the construction of any building, architects design a blueprint, the same thing we replicate for the data system Building Architecture contains various components - Foundations, Floor plans, Elevations, Elevators, Stairs, Offices, Restrooms, and many more... Data Architecture contains Storage, Software, Data flow, Interfaces, Transformation, Staging areas, Data warehouse, Reporting, and many more… As per the technical definition, decisions should be flexible and reversible, which means if every component in the architecture does not meet the requirements then should be easily reversible =====There are two parts to it===== 1. Business Needs (Operational Architecture): We focus on the business goals and requirements. For example in an e-commerce platform - What is the impact on the XYZ category of product? - Why is there a delay in product shipping? - How do we manage data quality from third-party vendors All focus is on business and how it will impact everyone 2. Technology Integration (Technical Architecture): We focus on the technical side of things, and how to ingest, store, and transform data. What happens when we have sudden orders spike? You can read the complete blog here - https://lnkd.in/dqqkJvtE This is my first post on my newsletter, consider subscribing for quality content :) Tag someone who might find this helpful 👇🏻 #dataengineer #dataengineering #dataarchitect

Data Architect 101 for Data Engineers (Complete Guide) Understanding how to build end-to-end data systems can be a catalyst in your career growth as a Data Engineer, let's understand the basics of building a data system 👇🏻 The goal of every data project is to solve business problems! It can be anything from reducing current system costs to building a full-fledged data system helping businesses to make data-driven decisions. Today I want to take you on a journey of architecting a data system, if you are an aspiring data engineer or have been working in this field for a few years, understanding how to architect a data system can help you see the bigger picture. What is Data Architecture? Here is the technical definition you will find in The Fundamentals of Data Engineering Book by Joe Reis and Matt Hoursely Data architecture is the design of systems to support the evolving data needs of an enterprise, achieved by flexible and reversible decisions reached through a careful evaluation of trade-offs. In simple terms, before the construction of any building, architects design a blueprint, the same thing we replicate for the data system Building Architecture contains various components - Foundations, Floor plans, Elevations, Elevators, Stairs, Offices, Restrooms, and many more... Data Architecture contains Storage, Software, Data flow, Interfaces, Transformation, Staging areas, Data warehouse, Reporting, and many more… As per the technical definition, decisions should be flexible and reversible, which means if every component in the architecture does not meet the requirements then should be easily reversible =====There are two parts to it===== 1. Business Needs (Operational Architecture): We focus on the business goals and requirements. For example in an e-commerce platform - What is the impact on the XYZ category of product? - Why is there a delay in product shipping? - How do we manage data quality from third-party vendors All focus is on business and how it will impact everyone 2. Technology Integration (Technical Architecture): We focus on the technical side of things, and how to ingest, store, and transform data. What happens when we have sudden orders spike? You can read the complete blog here - https://lnkd.in/dqqkJvtE This is my first post on my newsletter, consider subscribing for quality content :) Tag someone who might find this helpful 👇🏻 #dataengineer #dataengineering #bigdata

Following to previous blog on what is Data Architect role, this article aims to provide the skills required in the data architect journey... Leave your valuable comments.. #dataarchitect #dataarchitecture #data #datamodeling

Data architects play a critical role in managing and structuring data. Explore the career guide to becoming a data architect.