AgileData Blogs

Because sharing is caring

An Experiment – Top Data Trends for 2025 with Coalesce and Google NotebookLM

Join two LLM generated guests as they discuss the Top Data Trends of 2025 Whitepaper published by Coalesce.

This is a different episode.  Instead of a human guest, we have two robot guests. 

I decided to try and experiment. My experiment was, can I upload a white paper to LLM, have it generate a podcast listen to that podcast in my daily walk and see whether that summary removes the need for me to actually read the white paper.

So in this case, I have grabbed a white paper  called Top Data Trends for 2025 from Coalesce, uploaded it to the Google Notebook LLM and got it to generate a podcast with two hosts chatting about the white paper.

Have a listen, let me know what you think.

Unveiling the Definition of Data Warehouses: Looking into Bill Inmon’s Magicians Top Hat
Unveiling the Definition of Data Warehouses: Looking into Bill Inmon’s Magicians Top Hat

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.

Martech – The Technologies Behind the Marketing Analytics Stack: A Guide for Data Magicians
Martech – The Technologies Behind the Marketing Analytics Stack: A Guide for Data Magicians

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.

Unveiling the Magic of Data Clean Rooms: Your Data Privacy Magicians
Unveiling the Magic of Data Clean Rooms: Your Data Privacy Magicians

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.

Agile-tecture Information Factory
Agile-tecture Information Factory

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.

DataOps: The Magic Wand for Data Magicians
DataOps: The Magic Wand for Data Magicians

DataOps is a magical approach to data management, combining Agile, DevOps, and Lean Manufacturing principles. It fosters collaboration, agility, automation, continuous integration and delivery, and quality control. This empowers data magicians like you to work more efficiently, adapt to changing business requirements, and deliver high-quality, data-driven insights with confidence.

ELT without persisted watermarks ? not a problem
ELT without persisted watermarks ? not a problem

We no longer need to manually track the state of a table, when it was created, when it was updated, which data pipeline last touched it …. all these data points are available by doing a simple call to the logging and bigquery api. Under the covers the google cloud platform is already tracking everything we need … every insert, update, delete, create, load, drop, alter is being captured