Migo Lee’s Post

The Modern Data Products are Programmable

How much do you think access to reliable financial data shapes decision-making in the corporate world? In an age where information is power, the ability to tap into accurate public company data can be a game changer for analysts, investors, and businesses alike. The recent article on SEC's RESTful APIs shines a light on how these tools can facilitate smoother data access from resources like EDGAR. While diving into this, I reflected on the challenges many face, such as managing rate limits and transforming complex JSON into usable tables. It's compelling to see both the possibilities and the hurdles involved in leveraging this technology effectively. What are your thoughts on the potential impacts of easy access to financial data? Share your experiences and insights! https://lnkd.in/eSQb2ssf

How does running off of a messaging queue impact your data loading strategies? Read on for a deep and technical analysis of which strategies scale, perform, and stay cost effective. https://lnkd.in/gHZqcFvg

5 tricks to improve your automations process in n8n 1. Brainstorm- Before clicking that start node, think what the end goal is. You dont want to be half way only to realize you mapped the wrong system. Create a mental map of how you want your automation to run 2. Data Pinning - With large workflows, testing all the way from the start is chaotic. Detac nodes, pin data and use that as the first step in your automation. 3. Map and remap the data as much as posible - The set node is one of the most important nodes in n8n. Use this to manipulate data into new fields suitable for the next steps. You can pass data from diferent steps and use if as new fresh data 4. Loop as much as you can- Iterate your data where posible. If you are managing a huge workflow, best loop your data int chunks The advantage, you will need to do less subworkflows 5. Create reusable blocks. I like using the webhook as a trigger node for my workflows. Why? I can turn any workflow into an API call by just aligning the data to the API next node, which you guessed right - a set node For advanced user case - Use the set node to replace the code node. This can do lots of syntax such as email extraction, regex, replace, convresions among other fun stuff. In a more advanced case, you can use the code node to manipulate the data to your liking What tricks do you use? #funautomations

GraphQL is a query language for APIs and a runtime for executing those queries by providing a complete and understandable description of your data. Unlike REST, which exposes multiple endpoints, GraphQL allows clients to request only the data they need from a single endpoint. This reduces over-fetching and under-fetching issues. By using a strong type system, it enables more precise and flexible queries, and its real-time capabilities through subscriptions provide dynamic updates to clients. For efficient data retrieval and manipulation, GraphQL represents the ultimate evolution in API querying. Would you like to delve deeper into a specific feature or use case of GraphQL?

I explore the Dual Write Problem and how to solve it using Change Data Capture (CDC) and the Outbox Pattern. Would be a good read for developers tackling data consistency! https://lnkd.in/g6VugB52 Thoughts & feedback welcome as always! #DataConsistency #Microservices #Design

Distributed systems 🌐 are popular for their ability to scale ⏫ and handle large amounts of data 💾. A key challenge in these systems is keeping data consistent 🔄 across multiple nodes. Read Consistency 📖: This means any read operation will return the most recent write value ✔️ or a value that meets specific consistency rules, no matter which node handles the read request. Write Consistency ✍️: This ensures that when a write operation is performed, the new data is propagated to all relevant nodes. All replicas must be updated with the latest value before the write is considered successful ✅. Consistency Overview 📊: In a distributed system, Conflicts arise because each node can update its own copy, leading to different values when data is read from different nodes. This is where concepts like Eventual Consistency (EC) and Strong Consistency (SC) are important. Strong Consistency 💪: Strong consistency ensures that all nodes see the same data at the same time, regardless of which node is accessed. After a write operation, all subsequent reads from any node will return the most recent write value. This makes the system behave like a single, unified entity 👥. Eventual Consistency 🕰️: With eventual consistency, the system gradually becomes consistent over time. However, during this period, users accessing different nodes may see different versions of the data. The system guarantees that updates will eventually propagate to all nodes, leading to a consistent state, but temporary for few seconds or minutes discrepancies can occur. #DistributedSystems #DataConsistency #ReadConsistency #WriteConsistency #StrongConsistency #EventualConsistency #Scalability #DataHandling #TechInsights #SoftwareEngineering #SystemDesign #TechTips

One of the major challange is ensuring consistency in the database. Problem : The dual write problem in databases occurs when updates need to be made to two or more data stores simultaneously, often leading to inconsistencies. When: This typically happens in scenarios involving microservices or systems that need to maintain data in both a primary database and a secondary one, such as a cache or search index. Solution : 1) distributed transactions 2) eventual consistency models 3) event-driven architectures The following article contains the detailed information #systemdesign #scale

Zero Trust In Data Contracts? I never fully trust the data contracts of a REST API. They’re a guide, not a guarantee. Just because a contract says a field is an INT doesn’t mean it actually is. My go-to? Ingest JSON as text and handle casting in the silver layer. It’s the only way to avoid nasty surprises downstream. How do you handle unreliable data contracts? #dataengineering

Thriving in business is like a symphony; each component must harmonize to create a masterpiece. Our latest article delves into the intricate world of RESTful APIs and their pivotal role in financial operations. Explore how these digital conduits orchestrate seamless data exchanges for enhanced business efficiency. #FinancialInnovation #DigitalTransformation https://lnkd.in/eSQb2ssf