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Bridging Data and Product Management Practises and Patterns with Juha Korpela
Join Shane Gibson as he chats with Juha Korpela on how to adopt patterns and practises from Product Management and apply them to the data domain.
Business Agility with Evan Leybourn
Join Murray Robinson and Shane Gibson as they chat with Evan Leybourn from the Business Agility Institute about business agility. We discuss how to define and measure business agility, examples of agile organisations, and the struggle with traditional bureaucratic models. We delve into the different types of leadership, the nature of internal cultural and political changes, and the challenges faced by organisations in adopting and implementing agility.
Unmanaged with Jack Skeels
Join Murray Robinson and Shane Gibson as they chat with Jack Skeels about agile for digital and marketing agencies. Jack advocates for reducing the managerial overhead in organisations to promote productivity and improve communication. We discuss common hurdles in agile implementations. The value of a manager as a sports coach. The importance of scoping the work. Over managing and how real change must start from the top. This episode is full of practical advice and critical insights into organisation dynamics. This conversation is especially useful for those seeking to implement agile in a more holistic, efficient, and outcome oriented way in a service provider.
Innovation and disaster with Ron Westrum
Join Murray Robinson and Shane Gibson as they chat with Ron Westrum about how organisational culture drives innovation and disaster. We discuss generative, bureaucratic and pathological cultures, using real-world examples from NASA, Boeing and others. This episode highlights the importance of leadership integrity, openness, honesty, the free flow of information, and a mission-focused approach to achieving organisational goals. Listen for insights on identifying and promoting a generative culture, dealing with bad news, the role of technical maestros, and much more.
OKR’s with Adrian Howard
Join Murray Robinson and Shane Gibson as they discuss objectives and key results with Adrian Howard.
Adrian explains how OKR’s can be used as a strategic instrument for aligning goals within your organisation. We walk through common pitfalls and misconceptions emphasizing the importance of using OKR’s focused on outcomes rather than outputs. We discuss the potential for using OKR’s with vendors. The idea of paired metrics. And how OKR’s can serve as indicators of underlying problems within your organisations culture and structure.
Patterns for being a successful internal data consultancy with Dylan Jones
Join Shane Gibson as he chats with Dylan Jones on how to adopt patterns used by successful data consultancies and apply them in your organisation as an internal data team.
Combining agile and data five years on with Blair Tempero
Guests Blair TemperoShane GibsonResources Join Shane Gibson as he chats with Blair Tempero on that last five years since they started the AgileData Podcast together.Listen on your favourite Podcast Platform | Apple Podcast | Spotify | Google Podcast | Amazon...
The state of product management with Jason Knight
Join Murray Robinson and Shane Gibson as they chat with Jason Knight on the state of product management.
Jason shares his insights and experiences on the responsibilities of a product manager, the evolving nature of the role. Differentiating buyer and user features the importance of testing and validating ideas. Supporting cross-functional teams and fostering a mindset of continuous improvement. Jason shares insights from his experiences and discussions with thought leaders and provides advice for those navigating the product management field.
The Heart of Agile with Mike Leber
Join Murray Robinson and Shane Gibson as discuss business agility and the heart of agile with Mike Leber.
We talk about how the heart of agile liberates you from rigid process frameworks by focusing on collaboration, delivery reflection and improvement. We talk about how the agile industrial complex has turned agile into a heavyweight waterfall process. And how innovation is happening outside the traditional agile bubble. And lastly, we talk about agile leadership. If you’re interested in getting to the heart of agile and exploring business agility.
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#AgileDataDiscover weekly wrap No.2
We discuss the ongoing development of a new product idea, emphasising feasibility and viability through internal research (“McSpikeys”). Initial tests using LLMs have been promising, but strategic decisions lie ahead regarding its integration. The team grapples with market validation and adjusting their workflow for optimal experimentation.
#AgileDataDiscover weekly wrap No.1
We are tackling challenges in migrating legacy data platforms by automating data discovery and migration to reduce costs significantly. Our approach includes using core data patterns and employing tools like Google Gemini for comparative analysis. The aim is to streamline data handling and enable collaborative governance in organisations. Follow their public build journey for updates.
We are working on something new at AgileData, follow us as we build it in public
The AgileData team is dedicating 30 days to exploring a novel data use case, which might lead to a new product, feature set, or module. They’ll document their daily progress publicly to share learnings and insights. Follow their journey on their blog for updates as they build and experiment in real-time.
Introducing Hai, AgileData 2024 Data Intern
I’m Hai, a name that intriguingly means “hi” in English. Originally from Vietnam, I now find myself in Australia, studying Data Science and embracing an internship at AgileData.io. This journey is not just about academic growth but also about applying my knowledge in practical, impactful ways. Join me as I explore the blend of technology and community, aiming to make a difference through data.
Defining self-service data
Everybody wants self service data, but what do they really mean when they say that.
If we gave them access to a set of highly nested JSON data, and say “help your self”, would that be what they expect?
Or do they expect self service to be able to get information without asking a person to get it for them.
Or are they expecting something in between.
I ask them which of the five simple self service patterns they want to find, which form of self service they are after.
There are 3 strategic / macro data use cases
I often ask which of these three macro data use cases the Organisations believed were its priorities to achieve their business strategy:
Providing data to Customers
Supporting Internal Processes
Providing data to External Organisations
Each of these three strategic / macro data use cases come with specific data architectures, data work and also impact the context of how you would design your agile data ways of working.
Eventually the data maintenance Tortoise will catch the new data work Hare
When you work in a data team you have to split your time between building and delivering new Information Products and maintaining the ones you have already delivered.
DataOps patterns can help reduce the time you spend on the maintenance work.
Building the Data Plane while flying it
In the data domain you typically have to balance between building the right thing and building the thing right.
The days of being able to spend 6 months or a year on “Sprint Zero” creating your data platform have gone.
One team I worked with called it “building the airplane as you fly it”
Here are 5 patterns I have seen data teams adopt to help them do this.
2024 the year of the Intelligent Data Platform
AI was the buzzword for 2023 and it will continue to be the buzzword for 2024.
I have been thinking about our approach to AI in our product for a while and landed on 3 patterns that I use as a reference.
Ask AI
Assisted AI
Automated AI
Adopting these patterns moves a data platform from being a manual data platform, towards a data platform that can do some of the data work for you.
An Intelligent Data Platform.
The 3 patterns of AgileData AI
Having AI embedded in your product have become table stakes it seems.
I have been thinking about our approach to AI in our product for a while and landed on 3 patterns that I use as a reference.
Ask AI
Assisted AI
Automated AI
Demystifying CDP’s vs. Data Warehouse’s
In this article we describe the concepts of Customer Data Platforms (CDP) versus Data Warehouses.
The magic of DocOps
TD:LR Patterns like DocOps provide massive value by increasing collaboration across team members and automating manual tasks. But it still requires a high level of technical skills to work in a DocOps way. For the...
Iterations create milestone dates, milestone dates force trade off decisions to be made
Data teams struggle to not “boil the ocean” when doing data work.
Use milestones as a pattern to help the data team to focus on what really needs to be built and manage the trade-off decisions for what doesn’t.
Your data team are mercenaries, define your ways of working based on this
Modern data teams are transient, often staying less than 5 years, unlike past decades of long-term loyalty.
Companies should adapt by defining robust Ways of Working (WoW) that endure beyond individual tenures.
Balancing in-house teams with reliable data vendors for continuity and efficiency may also be a useful pattern as part of your WoW.
I’m getting pedantic about semantics
TD:LR Having a shared language is important to help a data team create their shared ways of working. When we talk about self-service, we should always highlight which self-service pattern we are talking about.I'm...
The Art of Data: Visualisation vs Storytelling
Data visualization is like painting with data, using charts and graphs to make trends and patterns easy to understand. It’s great for presenting data objectively.
Data storytelling weaves a narrative around data, adding context, engaging emotions, and inspiring action. It’s perfect for persuading stakeholders.
Most of your data is rotten and it’s not your fault, but it is your problem
Data quality is an expectation, not an exception.
While data quality is crucial, it’s not always directly our fault when issues arise, nevertheless, it remains our problem to solve.
Data Contracts are one pattern that can help us solve this problem.
Are you delivering drills, holes or outcomes?
TD:LR Whether you're a Data Entrepreneur or an organisation looking for actionable insights, its the business outcome these insights help you achieve that is the most important thing. Yes you need a data platform and...
Data Asset, Data Product, Data Service?
TD:LR Should we treat data as an Asset, a Product, a Service or a hybrid combination of all three? Data Asset, Data Product, Data Service? There has been a lot of discussions on LinkedIn, lots of podcasts, lots of...
Demystifying the Semantic Layer
The semantic layer is your mystical bridge between complex data and meaningful business insights. It acts as a translator, converting technical data into a language you understand. It works through metadata, simplifying queries, promoting consistency, and enabling self-service analytics. This layer fosters collaboration, empowers customization, and adapts to changes seamlessly. With the semantic layer’s power, you can decipher data mysteries, conjure insights, and make decisions with wizard-like precision. Embrace this enchanting tool and let it elevate your data sorcery to new heights.
Understanding Concepts, Details, and Events: The Fundamental Building Blocks of AgileData Design
Reducing the complexity and effort to manage data is at the core of what we do. We love bringing magical UX to the data domain as we do this.
Every time we add a new capability or feature to the AgileData App or AgileData Platform, we think how could we just remove the need for a Data Magician to do that task at all?
That magic is not always possible in the first, or even the third iteration of those features.
Our AgileData App UX Capability Maturity Model helps us to keep that “magic sorting hat” goal at the top of our mind, every time we add a new thing.
This post outlines what that maturity model is and how we apply it.