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Data Contracts with Andrew Jones

Join Shane Gibson as he chats with Andrew Jones on the pattern of Data Contracts

The Heart of Agile with Mike Leber
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.

The state of product management with Jason Knight
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.

There are 3 strategic / macro data use cases
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.

Building the Data Plane while flying it
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.

Dysfunction Mapping with Michael Lloyd
Dysfunction Mapping with Michael Lloyd

Join Murray Robinson and Shane Gibson as they chat with Michael Lloyd about dysfunction mapping.

Whether you are new to the agile world or a seasoned professional, you’ll find valuable insights as we delve into understanding team dynamics, honing the coaching process. And the essential principle of iterative hypothesis testing. Join us as we learned the power of mapping dysfunctions to unveil powerful solutions in agile environments.

2024 the year of the Intelligent Data Platform
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.

Developing digital products in China with Bianca Grizhar
Developing digital products in China with Bianca Grizhar

In this episode, we talk to Bianca Grizhar about developing digital products in China. We discuss the cultural differences between Germany and China, and how Scrum improved team collaboration. We talk about the benefits of working directly with people offshore in cross functional, cross organisational teams. Whether you’re a product manager or a developer, this episode is packed with practical advice that will help you work more successfully with your offshore teams.

AgileData App

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Network

Learn about consulting practises and good patterns for data focused consultancies

DataOps

Learn from our DataOps expertise, covering essential concepts, patterns, and tools

Data and Analytics

Unlock the power of data and analytics with expert guidance

Google Cloud

Imparting knowledge on Google Cloud's capabilities and its role in data-driven workflows

Journey

Explore real-life stories of our challenges, and lessons learned

Product Management

Enrich your product management skills with practical patterns

What Is

Describing data and analytics concepts, terms, and technologies to enable better understanding

Resources

Valuable resources to support your growth in the agile, and data and analytics domains

AgileData Podcast

Discussing combining agile, product and data patterns.

No Nonsense Agile Podcast

Discussing agile and product ways of working.

App Videos

Explore videos to better understand the AgileData App's features and capabilities.

Observability, Tick
Observability, Tick

TD:LR Data observability is not something new, its a set of features every data platform should have to get the data jobs done. Observability is crucial as you scale Observability is very on trend right now. It feels...

DataOps: The Magic Wand for Data Magicians
DataOps: The Magic Wand for Data Magicians

DataOps is a magical approach to data management, combining Agile, DevOps, and Lean Manufacturing principles. It fosters collaboration, agility, automation, continuous integration and delivery, and quality control. This empowers data magicians like you to work more efficiently, adapt to changing business requirements, and deliver high-quality, data-driven insights with confidence.

Information Product Canvas

Join Shane and Tammy Leahy as they discuss the Information Product Canvas, what each area of the canvas holds and why you would want to collect this information.

This is the second in a series of podcast episodes that deep dives into the Information Product pattern.

ELT without persisted watermarks ? not a problem
ELT without persisted watermarks ? not a problem

We no longer need to manually track the state of a table, when it was created, when it was updated, which data pipeline last touched it …. all these data points are available by doing a simple call to the logging and bigquery api. Under the covers the google cloud platform is already tracking everything we need … every insert, update, delete, create, load, drop, alter is being captured