AgileData reduces the cost of your data team and your data platform.
In this article we provide examples of those costs savings.
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AgileData reduces the cost of your data team and your data platform.
In this article we provide examples of those costs savings.
Join Murray Robinson and Shane Gibson as they chat with Stefan Wolpers about scrum anti-patterns. Explore common anti-patterns, such as scrum masters assigning tasks to disempowered teams, and discover the solutions...
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.
The key components of a successful data warehouse technology capability include data sources, data integration, data storage, metadata, data marts, data query and reporting tools, data warehouse management, and data security.
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.
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.
A graphical overview of the components required for a Data Product
Join Murray Robinson and Shane Gibson as they converse with Brendan Marsh about his experience working at Spotify. Understand how Spotify's agile methodologies aim to achieve speed to market and learning, which their...
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.
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.
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...
Join Murray Robinson and Shane Gibson as they delve into the fundamentals of product management with Roman Pichler, renowned author of 'Agile Product Management with Scrum'. Topics we'll explore in this conversation...
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 |...
Join Murray Robinson and Shane Gibson as they take a critical look at the current state of the agile industry with guests Michael Kusters and Brett Maytom. In this episode, we address: 🔸 The degradation of the agile...
Join Murray Robinson and Shane Gibson as they dive into the world of agile business analysis with guest Howard Podeswa. In this episode, we'll uncover: 🔸 The role and value of a business analyst 🔸 Why big requirements...
Join Shane and Nigel as they discuss how and why we define a conceptual model of Concepts, Details and Events in AgileData and how we map these to a physical Data Vault model.
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.
Join Murray Robinson and Shane Gibson as they talk with veteran developer, Jonathan Crossland about Ammerse, a value based decision making guide for products and teams. Ammerse is a mnemonic for agile, minimal,...
Join Murray Robinson and Shane Gibson as they talk with Rich Mironov about the problem with sales led development. It's easy for B2B enterprise companies to fall into a sales lead development model where the majority...
Join Murray Robinson and Shane Gibson as they talk with Donna Spencer from Maker X about user experience design in empowered product teams. We discuss user research, information architecture, and visual design. And the...
Join hosts Murray Robinson and Shane Gibson in a conversation with Al Shalloway, the founder of Amplio, as they discuss the re-emergence of pattern libraries in the realm of knowledge work. In this episode: Al...