The hottest Data Management Substack posts right now

And their main takeaways
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Top Technology Topics

What are the barriers to sensible public health data?

Joshua Gans' Newsletter • 0 implied HN points • 14 Apr 21
🏥 Health Politics Data Management
  1. Having comprehensive public health data is crucial for running an effective health system and monitoring trends.
  2. Political leaders need to prioritize and commit to improving public health data systems for better outcomes.
  3. Implementing a balanced growth strategy instead of a 'big bang' approach can lead to more sustainable progress in developing national public health data systems.

Contact tracing works!

Joshua Gans' Newsletter • 0 implied HN points • 30 Nov 20
🏥 Health Politics Data Management
  1. Contact tracing is an effective method to reduce infections by identifying and isolating those exposed to a virus proactively.
  2. Randomized experiments in scientific inquiries can provide valuable insights, but ethical concerns often prevent conducting them.
  3. The UK Excel spreadsheet error provided inadvertent data for economists to study the impact of contact tracing, revealing its value in reducing infections and deaths.

Loaded on Slurpees

Links I Would Gchat You If We Were Friends • 0 implied HN points • 30 May 14
🕹 Technology Data Management
  1. We're all dealing with surveillant anxiety due to the constant fear of our personal data being too revealing of ourselves.
  2. In the manosphere, not everyone is a creep - some tried to talk sense to troubled individuals like Elliot Rodger.
  3. To make digital memories feel more permanent, you can print them out using an industry that turns your online interactions into keepsake books.

Why wealth managers shouldn't maintain CRM?

Recontact • 0 implied HN points • 24 Feb 24
💼 Business Data Management
  1. Wealth managers can deepen client relationships by using CRM systems that go beyond just financial data to include personal details like milestones and events.
  2. Specialized CRMs designed for wealth management can help firms scale personal connections and enhance client engagement.
  3. Leveraging AI within CRM systems can transform data entry into a strategic advantage, providing wealth managers with personalized insights to strengthen client relationships.

How do Politicians remember everyone?

Recontact • 0 implied HN points • 16 Feb 24
🇺🇸 U.S. Politics Data Management
  1. Politicians need strong interpersonal skills to build public trust, understand constituent needs, and communicate effectively.
  2. CRM systems are essential for politicians to manage data, personalize communication, improve campaign efficiency, and track engagement.
  3. Politicians use CRMs uniquely by segmenting voters, integrating with social media, ensuring compliance, and managing large-scale operations.
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APIs eat Travel 🔌 Our investment in Impala 🏩

Venture Prose • 0 implied HN points • 02 Oct 19
💼 Business Data Management
  1. Impala's mission is to improve data management in the travel industry, providing a single access point for various hotel systems.
  2. Venture capital involves finding unexpected yet perfect matches between opportunities and talented teams.
  3. Impala's approach focuses on solving data management challenges in travel, offering a secure and structured layer for information exchange.

How Does Throttling Work?

Tributary Data • 0 implied HN points • 10 Jan 24
🕹 Technology Data Management
  1. Throttling controls data flow to prevent overwhelming systems, especially in streaming scenarios
  2. Throttling is different from rate limiting and involves managing resource usage
  3. Understanding how throttling works is crucial for optimizing system performance

Operational Use case Patterns for Apache Kafka and Flink — Part 1

Tributary Data • 0 implied HN points • 03 Jan 23
🕹 Technology Data Management
  1. Operational use cases with Kafka and Flink are crucial for business operations due to their message ordering, low latency, and exactly-once delivery guarantees.
  2. Using polyglot persistency with different data stores for read and write purposes can help solve the mismatch between write and read paths in microservices data management.
  3. Implementing a backend rate limiter using Flink as a Kafka consumer can help prevent exhausting an external system (e.g., a database) due to high message arrival rates from Kafka.

Artificial Intelligence is a Compost Heap (Ideally)

Cybernetic Forests • 0 implied HN points • 19 Dec 21
🕹 Technology Data Management
  1. Artificial Intelligence can be thought of as a living system like a compost heap, breaking down and reorganizing to produce something new.
  2. Metaphors play a crucial role in how we perceive and design AI, shifting from brain-centric models to organic and dynamic models like compost intelligence.
  3. Compost intelligence could offer benefits like data decomposition freeing up energy, designing for self-regulation, and emphasizing emergence and nurturing in creating richer outcomes.

How I re-categories 14K products using plang

Ingig • 0 implied HN points • 06 Mar 24
🕹 Technology Data Management
  1. Re-categorizing 14K products using plang saved time and money by automating the process for about $20 and an hour of developer work.
  2. The strategy included exporting product data to CSV, using OpenAI Playground to construct system commands, and then running Plang code to update the database with mapped product categories.
  3. By creating an efficient process using Plang, the task of categorizing 14K products was completed with minimal cost and a low error rate.

10/28 Tech Buzz China Insider Digest

Tech Buzz China Insider • 0 implied HN points • 29 Oct 21
🕹 Technology Data Management
  1. Douyin is posing strong competition to Alibaba's Tmall in certain product categories like bags & accessories, and clothing, with high GMV
  2. Top live streamers like Austin and Viya in China generated an impressive $3Bn in GMV within a short period, highlighting the massive impact of live shopping in the market
  3. PingCAP, a $3Bn open-source database unicorn, is prominent for its TiDB product, which serves as a distributed SQL database for elastic scale and real-time analytics

The Rise of the Data Product Manager

The Orchestra Data Leadership Newsletter • 0 implied HN points • 17 Nov 23
🕹 Technology Data Management
  1. The role of Data Product Manager is gaining importance in the data industry, with a focus on delivering value and advocating for data to drive business outcomes.
  2. Tools like Fivetran, dbt, Snowflake, and platforms like Orchestra are simplifying data team setups and enabling Product Managers with less technical skills to handle data initiatives effectively.
  3. Federated teams, marketplace functionalities by Databricks and Snowflake, and the evolving concept of data quality and productization are shaping the field of data management towards a more product-led approach.

Data Leadership #2 Understanding Data Lake Architecture

The Orchestra Data Leadership Newsletter • 0 implied HN points • 08 Oct 23
🕹 Technology Data Management
  1. Understanding the architectural structure of data lakes is crucial for data leaders to make informed decisions on data storage.
  2. File formats play a significant role in data storage efficiency, querying capabilities, and overall costs in a data lake architecture.
  3. Choosing between data lake providers or data warehouses can be complex due to the influence of underlying technologies, like object stores and file formats.

Data Leadership #1 Why being a Head of Data isn't what you think it is

The Orchestra Data Leadership Newsletter • 0 implied HN points • 04 Oct 23
🕹 Technology Data Management
  1. Being a Head of Data involves more than just solving problems, it requires aligning stakeholders, data cleanliness, and resources.
  2. Responsibilities as a Head of Data may shift towards evangelizing data tools, advocating for data strategy, and applying domain knowledge to solve business problems.
  3. Data leadership in a less mature data environment should focus on hitting crucial data use cases, getting leadership buy-in, and marketing the value of data within the organization.

Why Power Platform admins need to be SharePoint admins too.

Power Platform News • 0 implied HN points • 25 May 24
🕹 Technology Data Management
  1. SharePoint lists are widely used due to their ease of use and 'free' licensing, making them a popular choice for building apps.
  2. Dataverse may not always live up to its promise in practical use, and many organizations continue to prefer SharePoint lists for their applications.
  3. Microsoft sees value in maintaining both SharePoint lists and Dataverse to cater to different needs and competition in the market, leading to a need for Power Platform admins to also have SharePoint admin skills.

Automation Centre in the Power Platform

Power Platform News • 0 implied HN points • 21 May 24
🕹 Technology Data Management
  1. The Automation Centre in Power Automate is a new feature that will assist makers in monitoring flows in their environment more efficiently.
  2. It provides data almost within an hour, which is an improvement from the traditional CoE kit that had a one-day delay.
  3. Premium licensing is required for the Automation Centre and it is not available for the default environment.

Gradient Flow #43: Graph Databases; Language Understanding; Program Synthesis

Gradient Flow • 0 implied HN points • 09 Sep 21
🕹 Technology Data Management
  1. Graph databases and graph analytics are growing in interest, with use cases and applications expanding.
  2. The NLP Summit offers insights from leading organizations and researchers in the field of Natural Language Processing.
  3. Tools like Darts for time series forecasting and River for online machine learning are open-source libraries enabling easier adoption of advanced machine learning techniques.

Gradient Flow #17: RL for Recommenders, AI Assurance, Traffic Prediction

Gradient Flow • 0 implied HN points • 10 Sep 20
🕹 Technology Data Management
  1. AI Assurance focuses on building tools to scale AI operations, bringing together various organizational stakeholders.
  2. Machine learning tools are evolving with a rise in natural language interfaces to databases and advancements in differential privacy techniques.
  3. Graph Neural Networks are showing promise in traffic prediction, potentially improving real-time ETA accuracy by up to 50%.

A Digital Debt Crisis?

The Digital Anthropologist • 0 implied HN points • 29 Jan 24
🕹 Technology Data Management
  1. A Digital Debt Crisis could lead to better technologies and innovations that benefit everyone.
  2. Technology debt in organizations may impact the market, lead to complex IT systems, and cause declines in digital technology usage.
  3. A Digital Debt Crisis may result in fewer investments in new technology but could drive improvements in software quality and better data management.

Workplace Culture & AI: It Gets Complicated Fast

The Digital Anthropologist • 0 implied HN points • 02 Jan 24
🕹 Technology Data Management
  1. Introducing AI agents in the workplace can lead to complex cultural impacts and challenges that traditional AI tools don't pose.
  2. AI agents, with agency and social interactions, can become social actors and adopt traits of their workplace environment, which includes toxic or empowering cultures.
  3. The use of AI agents in the workplace brings forth unique complications such as knowledge management risks, governance challenges, and the need to redefine productivity metrics beyond traditional approaches.

What do we mean by ‘High Availability’ in the Cloud?

realkinetic • 0 implied HN points • 25 May 23
🕹 Technology Data Management
  1. Availability is expressed as a percentage of uptime; higher percentages require substantial investment and multi-team efforts
  2. Achieving high availability in the cloud involves significant costs and considerations like multi-master databases, multi-zonal deployments, and failover testing
  3. Five nines (99.999%) availability is considered the gold standard, but it requires extensive resources, multi-region support, and rigorous infrastructure and data replication

Clash of Tech Civilisations

Sector 6 | The Newsletter of AIM • 0 implied HN points • 05 Jan 23
🕹 Technology Data Management
  1. Cloud database providers like Redis and MongoDB are facing major challenges from big companies like AWS, Microsoft, and Google.
  2. These cloud giants have recently grabbed a larger share of the database market, taking 6% from traditional leaders like IBM and Oracle.
  3. In the past, the top companies controlled almost all of the market, but now their dominance is slipping due to the rise of cloud solutions.

LangGraph Introduced SubGraphs

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 30 Jul 24
🕹 Technology Data Management
  1. LangGraph allows users to create and manage states using graphs. This helps in making complex conversation flows simpler and more organized.
  2. Sub-graphs can perform specific tasks like summarizing logs separately while still connecting back to a main graph. This lets each section work independently but share important information.
  3. LangGraph is flexible and lets users visualize and modify conversation flows easily. It works with regular Python functions, making it adaptable for various applications.

LangChain Just Launched LangGraph Cloud

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 01 Jul 24
🕹 Technology Data Management
  1. LangGraph Cloud is a new service that helps users build and host their LangGraph applications easily. It's like having a managed platform to run your projects without worrying about servers.
  2. Agents are becoming more common and can handle complicated user questions automatically. They break tasks into smaller steps, making it easier to manage them.
  3. LangGraph Studio lets users visualize how data flows in their applications. This tool helps with debugging and understanding processes, even though you can't change the code directly in it.

LLamaIndex Agentic RAG Demo

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 01 Feb 24
🕹 Technology Data Management
  1. Agentic RAG uses a system of smaller agents to answer questions across multiple documents. Each smaller agent focuses on its own document, which helps organize the information better.
  2. This setup allows for comparing different documents and summarizing specific ones easily. It's a flexible way to dig into complex topics.
  3. The architecture is designed to scale by adding more agents as needed. This means it can grow and adapt to handle more information over time.

Prompt-RAG: Vector Embedding Free Retrieval-Augmented Generation

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 26 Jan 24
🕹 Technology Data Management
  1. Prompt-RAG is a simpler way to use language models without needing complex data setups like vector embeddings. This makes it easier to apply for specific tasks.
  2. It uses a Table of Contents to find the right information quickly, which helps generate more accurate responses to user questions.
  3. While it's great for small projects, it may face challenges with larger data or technical scaling as needs grow.

LLM Drift, Prompt Drift, Chaining & Cascading

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 27 Sep 23
🕹 Technology Data Management
  1. LLM Drift refers to the changes in the responses of language models over time, where their accuracy can significantly decline.
  2. Prompt Drift happens when the same prompt gives different responses because of changes in the model or data, even if the prompt itself hasn't changed.
  3. Cascading occurs when errors from one part of a process affect subsequent parts, making issues worse as they go along.

Foundation Conversational AI Technologies

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 10 Feb 23
🕹 Technology Data Management
  1. Conversational AI (CAI) technologies are grouped by their areas, but sometimes it's tricky to fit them into just one category. Many technologies overlap.
  2. The focus is mainly on foundational technologies instead of specific products or solutions, which are too numerous to cover in detail.
  3. Feedback and suggestions for improvement are encouraged to make future versions better.

The Cobus Quadrant™ Of NLU Design

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 09 Feb 23
🕹 Technology Data Management
  1. Understanding customer intent is key to making chatbots work well. Starting with what customers want helps create better and more trusted AI experiences.
  2. NLU Design is about turning messy data into clear information for chatbots. It involves organizing unstructured data and using both human input and machine help to label and manage it.
  3. Improving chatbots requires ongoing evaluation and fine-tuning. Regularly checking their performance and making adjustments helps keep them responsive to users' needs.

Stop using UUIDs: The Modern ID Spec

Getting Traction • 0 implied HN points • 12 May 24
🕹 Technology Data Management
  1. UUIDs are not always the best choice for identifiers because they're long and hard to read. A new approach suggests using shorter, more human-friendly IDs that are easier to copy and work with.
  2. The modern ID format uses a prefix for the table and a suffix for uniqueness, allowing for better organization and user experience. This means URLs can be cleaner and easier to understand.
  3. Different tables can have different suffix lengths based on their volume and sensitivity, making it flexible. It also makes it easier to manage potential ID conflicts as your database grows.

LLM and GenAI future from a business perspective

Thoughts from the trenches in FAANG + Indie • 0 implied HN points • 17 Aug 24
💼 Business Data Management
  1. LLM and GenAI are helpful tools that boost human productivity, even though they can't think creatively on their own.
  2. The cost of using these models is decreasing, making it easier for businesses to choose vendors based on price and convenience.
  3. To get the most value from LLM, companies must control and organize their data properly, which may create new job opportunities in data management and security.

The simple button that makes data easier to use

CommandBlogue • 0 implied HN points • 28 May 24
🕹 Technology Data Management
  1. Adding a reset button in dashboards helps users easily undo multiple customizations with one click. It saves time and makes exploring data more efficient.
  2. This feature allows users to quickly return to the default view, which is helpful when working with multiple users in an app.
  3. Just like pressing delete to start over, users prefer easy solutions that let them change their paths without wasting time.

GroupBy #9: FDAP stack, Iceberg and Hudi ACID Guarantees, Data Driven Management

VuTrinh. • 0 implied HN points • 14 Nov 23
🕹 Technology Data Management
  1. The FDAP stack is important in building reliable data systems. It helps to manage data more efficiently by using advanced technologies.
  2. Learning about data quality is crucial. It ensures that the information used for decision-making is accurate and trustworthy.
  3. Data-driven management is all about making decisions based on solid data insights. It helps businesses understand what works and what doesn't.

GroupBy #3

VuTrinh. • 0 implied HN points • 22 Sep 23
🕹 Technology Data Management
  1. Docker commands can be simplified with a cheat sheet, making it easier for developers to use container technologies effectively.
  2. Apache Spark was created at UC Berkeley to improve cluster computing, focusing on faster interactive computations than previous systems like Hadoop.
  3. There are key differences between HDFS and S3, especially in how they handle data, and many people confuse them even though they serve different purposes.

Master Dynamic Queries in Spring JPA

Curious Devs Corner • 0 implied HN points • 13 Jul 24
🕹 Technology Data Management
  1. You can create fully dynamic queries in Spring JPA based on user input. This allows users to choose which columns to select and how to group them.
  2. When using 'group by', all non-aggregated columns from the select statement must be included in the group clause. Otherwise, you'll get an error.
  3. Using the Java Persistence Criteria API can help effectively manage these dynamic queries and avoid common issues.

HN blogs -24/10/24

HackerNews blogs newsletter • 0 implied HN points • 24 Oct 24
🕹 Technology Data Management
  1. Migrating from I3 to Sway on Wayland can improve your user experience. It's a process worth exploring for better desktop management.
  2. Using PostgreSQL recursive CTEs can help in effectively retrieving data from graph structures. This technique can be a game changer for handling complex data queries.
  3. Thinking carefully about framework choices in software development is important. Relying too much on convenient tools can stifle innovation and creativity.