Content we think will help you get more value out of AgileData
AgileData has achieved Google Cloud Ready – BigQuery designation, streamlining data management for customers and partners. This certification confirms the integration’s functionality and reliability, reducing complexity through a low-code interface. By leveraging Google Cloud’s infrastructure and BigQuery, AgileData empowers business leaders to rapidly gain insights and make informed decisions efficiently.
Having AI embedded in your product have become table stakes it seems.
I have been thinking about our approach to AI in our product for a while and landed on 3 patterns that I use as a reference.
Ask AI
Assisted AI
Automated AI
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...
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.
TD:LR In mid 2023 I was lucky enough to present at The Knowledge Gap on the Information Product Canvas. Shane Gibson - AgileData.io Watch The Information Product Canvas, is an innovative pattern designed to capture...
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.
AgileData reduces the cost of your data team and your data platform.
In this article we provide examples of those costs savings.
As Data Consultants your customers are buying and outcome based on one of these patterns – effort, expertise, experience or efficiency.
We outline what each of these are, how they are different to each other and how to charge for delivering them.
TD:LR Data Architecture as a Service (DAaaS), is it Buzzwashing or not? As is often the case, it depends on your point of view. Our point of view? Nope its a real thing.
TD:LR Cloud Data Platforms promise you the magic of storing your data and unlimited elastic compute for cents. Is it too good to be true? Yes AND No. You can run a cloud platform for a low low cost, but its will take...
TD:LR When we dreamed up AgileData and started white-boarding ideas around architecture, one of the patterns we were adamant that we would leverage, would be Serverless. This posts explains why we were adamant and what...
TD:LR AgileData's mission is to reduce the complexity of managing data. A large part of modern data complexity is selecting, implementing and maintaining a raft of different technologies to provide your "Modern Data...
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