In this article we describe the concepts of Customer Data Platforms (CDP) versus Data Warehouses.
Shane Gibson Blogs
Because sharing is caring
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.
AgileData Newsletter #37
The Hitchhikers Guide to the Information Product Canvas
Information Product Canvas – Google Slide Template
How Can Data Teams use Generative AI with Shaun McGirr
Roman Pichler – Product Management
AgileData App Colours of the Catalog
Pulp Data Fiction
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.
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.
AgileData Newsletter #36
The Challenge of Parsing Files from the Wild
An AgileData Guide to Information Product Canvas
The Patterns of Activity Schema with Ahmed Elsamadisi
Pawel Huyrn – Product Management
Natural Language Rules Output
Latest AgileData Magician Guides
Designed in NZ
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!
AgileData Newsletter #35
Magical Plumbing for Effective Change Dates
Common Team Design Patterns
The Patterns of Data Vault with Hans Hultgren
Pawel Huyrn – Product Management
Custom Sync
Latest AgileData Magician Guides
ADI
AgileData Newsletter #34
To white label or to not white label
Concept of Team Design
Data Consulting Patterns with Joe Reis
Willem Jan Ageling – Agile Project Management and Leadership
Data Versioning
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.
AgileData Newsletter #33
The HitchHikers Guide to the Information Product Canvas
Bring Back Business Analysis with Howard Podeswa
New Google Cloud Feature to Optimise BigQuery Costs
Data Lineage Patterns
G60S – Google Sheets
Bring Back Data Modeling
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...