In this article we describe the concepts of Customer Data Platforms (CDP) versus Data Warehouses.
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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.
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
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.
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.
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.
To whitelabel or not to whitelabel
Are you wrestling with the concept of whitelabelling your product? We at AgileData have been there. We discuss our journey through the decision-making process, where we grappled with the thought of our painstakingly crafted product being rebranded by another company.
Metadata-Driven Data Pipelines: The Secret Behind Data Magicians’ Greatest Tricks
Metadata-driven data pipelines are the secret behind seamless data flows, empowering data magicians to create adaptable, scalable, and evolving data management systems. Leveraging metadata, these pipelines are dynamic, flexible, and automated, allowing for easy handling of changing data sources, formats, and requirements without manual intervention.
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.
Shane Gibson – Making Data Modeling Accessible
TD:LR Early in 2023 I was lucky enough to talk to Joe Reis on the Joe Reis Show to discuss how to make data modeling more accessible, why the world's moved past traditional data modeling and more. Listen to the episode...
AgileData Cost Comparison
AgileData reduces the cost of your data team and your data platform.
In this article we provide examples of those costs savings.
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.





















