Data is no longer treated as a byproduct of business operations and has become one of the most valuable organizational assets. Every interaction on a banking application, e-commerce platform, hospital system, logistics network or social media service generates data continuously. As organizations increasingly adopt digital workflows, cloud platforms, machine learning systems and real-time applicati
In modern data-driven organizations, managing and analyzing data efficiently is critical. OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) are both integral parts of data management, but they have different functionalities. Understanding how they differ, and how they complement each other is essential for anyone working with data systems. Online Transaction Processing (
SQL is widely known for data querying and manipulation but systems do grow; data becomes larger; processes become repetitive and operations become sensitive. SQL has some features which enables it to be considered a fully fledged programming language. Some of the features which I discuss in this article are procedures, functions and transactions. Each of these concepts serve distinct purposes. Sto
It started at midnight I had 24 hours, a free Replit subscription, and an idea: what if I could build something like Miro — but actually understand every line of code in it? The core problem I had to solve first Multiplayer sync sounds simple until you actually build it. The hard part isn't sending a canvas update — it's figuring out what to send. canvas.on('object:modified', (e) => { socket.emi
FutureMe has 15 million letters in its database. They've been there since 2002. Some of them will be there in 2050. Evengood will have zero. This week I shipped The Quiet Letter — a feature where you write to your future self today, we email it on a date you pick, and we hard-delete the row from our database within 24 hours of sending it. The email is the only artifact. We don't keep a copy. Every
It was around 1am and I had three feeds open. X on my phone, Reddit on one monitor, Hacker News on the other. I was reading about a plane crash, a new AI model, and a meme war about whether oat milk counts as milk. And I realised I had no idea what the internet was actually feeling about any of it. The feeds told me what was happening. They didn't tell me how it felt. That's when the idea hit me.
選定理由 Paper: https://arxiv.org/abs/2512.01020 【社会課題】 【データの設計と従来技術の限界】 Issue Tree（法的論点ツリー）に変換し、葉ノードに対しルーブリック基準を適用可能にした。原告・被告・裁判所の主張をツリー構造で整理した約24,000インスタンスのデータセットを構築。評価軸は「論点カバレッジ」と「正確さ」の2次元。以下がサンプルである： 【原告の主張】被告は540万円を支払え └─【原告】保険金の支払い義務がある ├─【原告】死亡は突発的・偶発的な事故だった │ └─【原告】餅を食べて窒息死＝外因による傷害 │ └─【被告】死因は既往症の可能性が高い └─【裁判所の結論】突発的事故と認定 ただし窒息死は証明不十分 この
I write a lot of READMEs. I ship faster than I document. I work with AI agents that write code in seconds and READMEs in minutes, and somewhere between the first commit and the third refactor, the README I wrote on Tuesday stops matching the code I wrote on Friday. The install command says npm start. The package.json defines start:prod. Anyone copying that command would have failed instantly. I'd