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5 core Data Collection Patterns

At AgileData, delivering our Fractional Data Service has revealed the diverse challenges of integrating data from varied organisations, industries, and systems. To scale effectively, we’ve adopted five core data collection patterns based on our “Define it Once, Reuse it Often” (DORO) principle:

1. Push
2. Pull
3. Stream
4. Share
5. File Drop

These patterns are supported by a toolkit of tested technologies like Dataddo, Meltano, and Google services, allowing us to solve new data challenges quickly. Our approach ensures flexibility and scalability, always starting with the question: Push, Pull, Stream, Share, or File Drop?

Transforming to the Product Model with Chris Jones
Transforming to the Product Model with Chris Jones

Join Murray Robinson and Shane Gibson as they chat with Chris Jones from the Silicon Valley Product Group about the product operating model, emphasising the importance of cross-functional agile product teams.

He shares insights on transitioning to a product model. The value of rapid experimentation, product leadership and common pitfalls. And he discusses successful examples of product transformations at Adobe Cloud and Train Line in Europe.

NZ Scaleup AgileData achieves Google Cloud Ready – BigQuery Designation
NZ Scaleup AgileData achieves Google Cloud Ready – BigQuery Designation

AgileData has achieved Google Cloud Ready – BigQuery designation, streamlining data management for customers and partners. This certification confirms the integration’s functionality and reliability, reducing complexity through a low-code interface. By leveraging Google Cloud’s infrastructure and BigQuery, AgileData empowers business leaders to rapidly gain insights and make informed decisions efficiently.

The last (for now) of our #AgileDataDiscover summaries!
The last (for now) of our #AgileDataDiscover summaries!

Shane Gibson and Nigel Vining completed a 30-day public experiment using a Large Language Model for legacy data warehouse discovery. They confirmed it was feasible, viable, and valuable, securing their first paying customer. They’re showcasing their progress at Big Data London in September under their new product, AgileData Disco.

#AgileDataDiscover weekly wrap No.5
#AgileDataDiscover weekly wrap No.5

We are in the final phase of building a new product, AgileData Disco, aimed at efficiently discovering and documenting data platforms. We are exploring various Go-to-Market strategies like SLG and PLG. Pricing strategies include options like pay per output or subscription models. We are building in public to gather feedback and refine their approach.

#AgileDataDiscover weekly wrap No.4
#AgileDataDiscover weekly wrap No.4

We review feedback, highlight emerging use cases like legacy data understanding, data governance, and automated data migration. New patterns are needed for moving from prototype to MVP. Challenges include managing tokens, logging responses, and secure data handling. The GTM strategy focuses on Partner/Channel Led Growth.

Mob Programming and Software Teaming with Woody Zuill
Mob Programming and Software Teaming with Woody Zuill

Join Murray Robinson and Shane Gibson as they chat with with Woody Zuill about mob programming.

Woody explains the concept of mob programming where a cross-functional software development team focuses on completing one feature at a time. Woody describes how mobbing has increased the effectiveness of development teams he’s worked with by 10 times while rapidly increasing team learning, capability and skills. Tune in to learn about the practical implementation of mobbing techniques to improve your product development.

#AgileDataDiscover weekly wrap No.3
#AgileDataDiscover weekly wrap No.3

We focus on developing features such as secure sign-in, file upload, data security, and access to Google’s LLM. Challenges include improving the menu system and separating outputs into distinct screens for clarity. Feedback drives their iterative improvements.

#AgileDataDiscover weekly wrap No.2
#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.

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.

Ways of Working with Scott Ambler
Ways of Working with Scott Ambler

Join Shane Gibson on the Agile Data Podcast for an enlightening conversation with Scott Ambler, an IT and Agile expert. Delve into Scott’s journey from pioneering programmer to data architecture and Agile methodologies. Discover the evolution of Agile data, the importance of adapting ways of working, and the pitfalls of best practices. Learn valuable insights into continuous improvement, team dynamics, and the complexities of data quality in today’s fast-paced IT landscape. Don’t miss this episode for an in-depth exploration of Agile data and its impact on IT projects and processes.

Demystifying the Semantic Layer
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.

Attribution Model Patterns with Yorgos Moschovis
Attribution Model Patterns with Yorgos Moschovis

Explore the intricacies of marketing attribution with Yorgos Moschovis on the Agile Data Podcast. Dive into the complexities of tracking customer behavior across various channels and the challenges of connecting online and offline data. Learn about Yorgos’s journey from the Office of the Auditor General to a leader in data analytics, navigating through companies like Spark New Zealand and Silicon Graphics. Understand the evolution of attribution modeling, from basic first and last touch to sophisticated, multi-touch approaches. Discover the impact of third-party cookie demise on tracking and the emergence of identity management solutions. Gain insights into how different industries, like retail and insurance, approach customer journey mapping and the significance of continuous touches versus deeper histories. Hear Yorgos’s perspective on the diminishing role of static demographics in favor of digital behavior analysis. The conversation also delves into operational improvements through actionable insights, emphasising real-world applications and AB testing over theoretical model complexities.

Understanding Concepts, Details, and Events: The Fundamental Building Blocks of AgileData Design
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.

Building a vibrant community with Scott Hirleman
Building a vibrant community with Scott Hirleman

Explore the art of building vibrant communities with Scott Hirleman on the Agile Data Podcast. Uncover key insights into community growth, operational strategies, and sustainability. Discover how Scott transitioned from a stock market enthusiast to a community management expert, specifically in tech and data spaces. Learn about the rapid expansion of the Data Mesh Learning Community, the importance of engaging members, and the role of timely content and responses. Delve into the operational nuances of community building, including automated onboarding, managing different fluency levels, and establishing community vibes. Understand the critical need for investment, sustainability, and how to overcome founder dependence. Gain insights into ideal team structures for community management and the significance of adaptability and realism in community growth. These comprehensive strategies and experiences offer valuable lessons for anyone looking to nurture and grow a successful community in the tech and data sectors.

AgileData App UX Capability Maturity Model
AgileData App UX Capability Maturity Model

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.

Unveiling the Magic of Change Data Collection Patterns: Exploring Full Snapshot, Delta, CDC, and Event-Based Approaches
Unveiling the Magic of Change Data Collection Patterns: Exploring Full Snapshot, Delta, CDC, and Event-Based Approaches

Change data collection patterns are like magical lenses that allow you to track data changes. The full snapshot pattern captures complete data at specific intervals for historical analysis. The delta pattern records only changes between snapshots to save storage. CDC captures real-time changes for data integration and synchronization. The event-based pattern tracks data changes triggered by specific events. Each pattern has unique benefits and use cases. Choose the right approach based on your data needs and become a data magician who stays up-to-date with real-time data insights!

Layered Data Architectures with Veronika Durgin
Layered Data Architectures with Veronika Durgin

Dive into the Agile Data Podcast with Shane Gibson and Veronika Durgin as they explore the intricacies of layered data architecture, data vault modeling, and the evolution of data management. Discover key insights on balancing data democratisation with governance, the role of ETL processes, and the impact of organisational structure on data strategy.

How can data teams use Generative AI with Shaun McGirr
How can data teams use Generative AI with Shaun McGirr

Discover the transformative impact of generative AI and large language models (LMS) in the world of data and analytics. This insightful podcast episode with Shane Gibson and Shaun McGirr delves into the evolution of data handling, from manual processes to advanced AI-driven automation. Uncover the vital role of AI in enhancing decision-making, business processes, and data democratization. Learn about the delicate balance between AI automation and human insight, the risks of over-reliance on AI, and the future of AI in data analytics. As the landscape of data analytics evolves rapidly, this episode is a must-listen for professionals seeking to adapt and thrive in an AI-driven future. Stay ahead of the curve in understanding how AI is reshaping the role of data professionals and transforming business strategies.

The challenge of parsing files from the wild
The challenge of parsing files from the wild

In this instalment of the AgileData DataOps series, we’re exploring how we handle the challenges of parsing files from the wild. To ensure clean and well-structured data, each file goes through several checks and processes, similar to a water treatment plant. These steps include checking for previously seen files, looking for matching schema files, queuing the file, and parsing it. If a file fails to load, we have procedures in place to retry loading or notify errors for later resolution. This rigorous data processing ensures smooth and efficient data flow.

The Magic of Customer Segmentation: Unlocking Personalised Experiences for Customers
The Magic of Customer Segmentation: Unlocking Personalised Experiences for Customers

Customer segmentation is the magical process of dividing your customers into distinct groups based on their characteristics, preferences, and needs. By understanding these segments, you can tailor your marketing strategies, optimize resource allocation, and maximize customer lifetime value. To unleash your customer segmentation magic, define your objectives, gather and analyze relevant data, identify key criteria, create distinct segments, profile each segment, tailor your strategies, and continuously evaluate and refine. Embrace the power of customer segmentation and create personalised experiences that enchant your customers and drive business success.

Magical plumbing for effective change dates
Magical plumbing for effective change dates

We discuss how to handle change data in a hands-off filedrop process. We use the ingestion timestamp as a simple proxy for the effective date of each record, allowing us to version each day’s data. For files with multiple change records, we scan all columns to identify and rank potential effective date columns. We then pass this information to an automated rule, ensuring it gets applied as we load the data. This process enables us to efficiently handle change data, track data flow, and manage multiple changes in an automated way.

The patterns of Activity Schema with Ahmed Elsamadisi
The patterns of Activity Schema with Ahmed Elsamadisi

In an insightful episode of the AgileData Podcast, Shane Gibson hosts Ahmed Elsamadisi to delve into the evolving world of data modeling, focusing on the innovative concept of the Activity Schema. Elsamadisi, with a rich background in AI and data science, shares his journey from working on self-driving cars to spearheading data initiatives at WeWork. The discussion centers on the pivotal role of data modeling in enhancing scalability and efficiency in data systems, with Elsamadisi highlighting the limitations of traditional models like star schema and data vault in addressing complex, modern data queries.

Amplifying Your Data’s Value with Business Context
Amplifying Your Data’s Value with Business Context

The AgileData Context feature enhances data understanding, facilitates effective decision-making, and preserves corporate knowledge by adding essential business context to data. This feature streamlines communication, improves data governance, and ultimately, maximises the value of your data, making it a powerful asset for your business.