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#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
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.
AI Data Agents with Joe Reis
Join Shane Gibson as he chats with Joe Reis on how the potential adoption of GenAI and LLM’s in the way Data teams work.
#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
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.
The Dojo with Joel Tosi and Dion Stewart
Join Murray Robinson and Shane Gibson as they chat with Joel Tosi and Dion Stewart about Dojo’s.
Dojo’s are a six week immersive learning experience where teams learn and practice new ways of working on real work with skilled coaches. We discuss the structure and implementation of Dojos, chartering, coaching dynamics, and frequent feedback loops. We emphasize the challenges and anti-patterns that can emerge, such as treating Dojos as bootcamps or lacking stakeholder support. Finally, Joel and Dion offer insights into the future of Dojos and their potential for building capability and driving organisation change.
#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.
Product Management with John Cutler
Join Murray Robinson and Shane Gibson as they discuss product management with John Cutler, famous for his newsletter The Beautiful Mess.
We dive into the purpose of product management as a driver of profitable growth. And we discuss how to use the north star framework to align your organisation around common goals. We examine how to use product roadmaps to communicate and prioritize plans and discuss how critical it is to be an open, honest, and effective leader. And finally we look at whether agile is critical or useless in product management. Join us as we uncover the insights and best practices product managers need to be more effective.
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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.
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
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
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.
Upgrading Python: A Plumbing Adventure in the Google Stack
In the ever-evolving world of AgileData DataOps, it was time to upgrade the Python version that powers the AgileData Platform.
We utilise micro-services patterns throughout the AgileData Platform and a bunch of Google Cloud Services. The upgrade could have gone well, or caused no end of problems.
Read more on our exciting plumbing journey.
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
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
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
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
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
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.
Fast Answers at Your Fingertips: Unveiling AgileData’s ‘Ask a Quick Question’ Feature
Immerse yourself in the magical world of data with AgileData’s ‘Ask a Quick Question’ capability. Perfectly designed for data analysts and business analysts who need to swiftly extract insights from data, this capability facilitates quick data queries and rapid exploratory data analysis.
The Hitchhikers guide to the Information Product Canvas
TD:LR In mid 2023 I was lucky enough to present at The Knowledge Gap on the Information Product Canvas. Watch The Information Product Canvas, is an innovative pattern designed to capture data requirements visually and...
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
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.
Unveiling the Secrets of Data Quality Metrics for Data Magicians: Ensuring Data Warehouse Excellence
Data quality metrics are crucial indicators in a data warehouse that measure the accuracy, completeness, consistency, timeliness, and uniqueness of data. These metrics help organisations ensure their data is reliable and fit for use, thus driving effective decision-making and analytics
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.
New Google Cloud feature to Optimise BigQuery Costs
This blog explores AgileData’s use of Google Cloud, specifically its BigQuery service, for cost-effective data handling. As a bootstrapped startup, AgileData incorporates data storage and compute costs into its SaaS subscription, protecting customers from unexpected bills. We constantly seek ways to minimise costs, utilising new Google tools for cost-saving recommendations. We argue that the efficiency and value of Google Cloud make it a preferable choice over other cloud analytic database options.
Data as a First-Class Citizen: Empowering Data Magicians
Data as a first-class citizen recognizes the value and importance of data in decision-making. It empowers data magicians by integrating data into the decision-making process, ensuring accessibility and availability, prioritising data quality and governance, and fostering a data-centric mindset.
The patterns of Data Vault with Hans Hultgren
In a compelling episode of the Agile Data Podcast, Shane Gibson invites Hans Hultgren to explore the intricacies of Data Vault modeling. Hans, with a substantial background in IT and data warehousing, brings his expertise to the table, discussing the evolution and benefits of Data Vault modeling in today’s complex data landscapes. Shane and Hans navigate through the foundations of Data Vault, including its core components like hubs, satellites, and links, and delve into more advanced concepts like Same-As Links (SALs) and Hierarchical Links (Hals). They highlight how Data Vault enables flexibility, agility, and incremental development in data modeling, ensuring scalability and adaptability to change.