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NZ Scaleup AgileData achieves Google Cloud Ready – BigQuery Designation

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.

Unmanaged with Jack Skeels
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.

Defining self-service 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.

OKR’s with Adrian Howard
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.

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.

AgileData App

Explore AgileData features, updates, and tips

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.

Data Consulting Patterns with Joe Reis
Data Consulting Patterns with Joe Reis

Dive into the world of data consulting with Shane Gibson and Joe Reis on the Agile Data Podcast. Explore their journey from traditional employment to successful data consulting, covering client acquisition, business models, financial management, reputation, sales strategies, employee management, and work-life balance.

The Enchanting World of Data Modeling: Conceptual, Logical, and Physical Spells Unraveled
The Enchanting World of Data Modeling: Conceptual, Logical, and Physical Spells Unraveled

Data modeling is a crucial process that involves creating shared understanding of data and its relationships. The three primary data model patterns are conceptual, logical, and physical. The conceptual data model provides a high-level overview of the data landscape, the logical data model delves deeper into data structures and relationships, and the physical data model translates the logical model into a database-specific schema. Understanding and effectively using these data models is essential for business analysts and data analysts, create efficient, well-organised data ecosystems.

Cloud Analytics Databases: The Magical Realm for Data
Cloud Analytics Databases: The Magical Realm for Data

Cloud Analytics Databases provide flexible, high-performance, cost-effective, and secure solution for storing and analysing large amounts of data. These databases promote collaboration and offer various choices, such as Snowflake, Google BigQuery, Amazon Redshift, and Azure Synapse Analytics, each with its unique features and ecosystem integrations.

Unveiling the Definition of Data Warehouses: Looking into Bill Inmon’s Magicians Top Hat
Unveiling the Definition of Data Warehouses: Looking into Bill Inmon’s Magicians Top Hat

In a nutshell, a data warehouse, as defined by Bill Inmon, is a subject-oriented, integrated, time-variant, and non-volatile collection of data that supports decision-making processes. It helps data magicians, like business and data analysts, make better-informed decisions, save time, enhance collaboration, and improve business intelligence. To choose the right data warehouse technology, consider your data needs, budget, compatibility with existing tools, scalability, and real-world user experiences.

Martech – The Technologies Behind the Marketing Analytics Stack: A Guide for Data Magicians
Martech – The Technologies Behind the Marketing Analytics Stack: A Guide for Data Magicians

Explore the MarTech stack based on two different patterns: marketing application and data platform. The marketing application pattern focuses on tools for content management, email marketing, CRM, social media, and more, while the data platform pattern emphasises data collection, integration, storage, analytics, and advanced technologies. By understanding both perspectives, you can build a comprehensive martech stack that efficiently integrates marketing efforts and harnesses the power of data to drive better results.

Unveiling the Magic of Data Clean Rooms: Your Data Privacy Magicians
Unveiling the Magic of Data Clean Rooms: Your Data Privacy Magicians

Data clean rooms are secure environments that enable organisations to process, analyse, and share sensitive data while maintaining privacy and security. They use data anonymization, access control, data usage policies, security measures, and auditing to ensure compliance with privacy regulations, making them indispensable for industries like healthcare, finance, and marketing.

Data Lineage Patterns with Tomas Kratky

In this episode of the AgileData Podcast, Shane Gibson has an insightful discussion with Tomas Kratky on the evolution and importance of data lineage, especially in large enterprises. Tomas Kratky, a traditional software engineer turned data enthusiast, shared his journey to founding Manta, a company focused on data lineage. The conversation highlighted the significance of data lineage, not just as an end in itself, but as a powerful tool for unlocking potential in large enterprises, enhancing visibility, and fostering agility.

Free Google Analytics 4 (GA4) online courses
Free Google Analytics 4 (GA4) online courses

TD:LR There is some great free course content to help you upskill in Google Analytics 4 (GA4) Here are the ones we recomend.Discover the Next Generation of Google Analytics Find out how the latest generation of Google...

Observability – Raj Joseph

Join Shane Gibson as he chats with Raj Joseph on his experience in defining data observability patterns.Guests Raj JosephShane GibsonResourcesSubscribe | Apple Podcast | Spotify | Google Podcast  | Amazon Audible |...

5E’s
5E’s

As Data Consultants your customers are buying and outcome based on one of these patterns – effort, expertise, experience or efficiency.

We outline what each of these are, how they are different to each other and how to charge for delivering them.

Agile-tecture Information Factory
Agile-tecture Information Factory

Defining a Data Architecture is a key pattern when working in the data domain.

Its always tempting to boil the ocean when defining yours, don’t!

And once you have defined your data architecture, find a way to articulate and share it with simplicity.

Here is how we articulate the AgileData Data Agile-tecture.

Agile and Product – Justin Bauer

Join Shane Gibson as he chats with Justin Bauer on his experience combining the worlds of agile and product in a data driven company.Guests Justin BauerShane GibsonResourcesSubscribe | Apple Podcast | Spotify | Google...