The hottest Data Management Substack posts right now

And their main takeaways
Category
Top Technology Topics

Tech the Heck? - CloudTruth

Cloud Irregular • 2069 implied HN points • 19 Feb 24
🕹 Technology Tech news Software Data Management Product Marketing Startups
  1. Explaining complex tech products in simple language is important for understanding and adoption.
  2. Developers may value different aspects of a tech product compared to business decision-makers, causing a mismatch in communication.
  3. CloudTruth focuses on managing crucial configuration data, highlighting the importance of precision in language and clear communication.

My Definition of Data Modeling (for today)

Joe Reis • 530 implied HN points • 20 Jan 24
🕹 Technology Data Modeling AI Venture Capital Data Management
  1. Data modeling has various definitions by different experts and serves to improve communication, provide utility, and solve problems.
  2. A data model is a structured representation that organizes data for both humans and machines to inform decision-making and facilitate actions.
  3. Data modeling is evolving to consider the needs of machines, different use cases, and a wider range of modeling approaches for various situations.
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Databricks Unity Catalog: Enabling Data Democratization

Data Plumbers • 19 implied HN points • 08 Apr 24
🕹 Technology Data Management Data Governance
  1. Data democratization is vital for modern data strategies, making data more accessible and understandable within an organization for informed decision-making and better customer experiences.
  2. Databricks Unity Catalog supports data democratization by providing a centralized governance layer, simplifying access management, enabling unified data management, and fostering data discovery, collaboration, and sharing.
  3. Implementing data democratization requires robust data governance and security measures to mitigate risks of privacy violations and data leaks.

The Trade Desk

Business Breakdowns • 334 implied HN points • 09 Jan 24
💼 Business Advertising Technology Data Management Market Dynamics Company growth
  1. The Trade Desk helps ad agencies spend their budgets more effectively by providing a platform for optimizing programmatic advertising.
  2. The company focuses on building strong, recurring relationships with buy-side agencies, leading to a high customer retention rate.
  3. The Trade Desk functions as a data management platform, enabling efficient real-time bidding and liquidity in the digital advertising market.

Long-Chain Marketing: How Data Engineering & Data Management Create Value For The Business

High ROI Data Science • 294 implied HN points • 10 Jan 24
💼 Business Data Engineering Data Management Value Creation Marketing
  1. Understanding the long-chain in marketing is crucial for connecting business outcomes with data and metrics.
  2. Data engineering and knowledge management are essential for transforming data into valuable assets that can be monetized by the business.
  3. Long-chain marketing involves seeing marketing efforts as part of a longer sequence of actions that lead to business outcomes, rather than standalone events.

Sentinel-free schemas: a thought experiment

Minimal Modeling • 393 implied HN points • 20 Dec 23
🕹 Technology Data Management Database Design Data Integrity Data processing
  1. NULL values in databases create compatibility issues and add complexity to conditional operations
  2. Sentinel values, like empty strings or placeholders, are similar to NULL values and can lead to incorrect results
  3. Creating sentinel-free schemas involves separating attributes into individual tables and explicitly defining reasons for missing data

ChinAI #252: The Top 10 Events of Internet Governance in China from 2023

ChinAI Newsletter • 157 implied HN points • 29 Jan 24
🕹 Technology Cybersecurity Data Management
  1. National Data Administration in China started coordinating data infrastructure construction in 2023.
  2. China took significant actions in internet governance, such as fines on financial platforms and AI-generated content regulations.
  3. Important events included new regulations on cyberviolence management and the first AI text-to-image infringement case in China.

Microsoft builds the bomb

benn.substack • 1500 implied HN points • 26 May 23
🕹 Technology Data Management Cloud Computing Software Development Artificial Intelligence
  1. The modern data stack aimed to revolutionize how technology is built and sold, focusing on modularity and specialized tools.
  2. Microsoft introduced Fabric as an all-in-one data and analytics platform to address the issue of fragmentation in the modern data stack.
  3. Fabric from Microsoft presents a unified solution but may risk limiting choice and innovation in the data industry.

Analytics Team: Strategic Partner or Service Org?

Elena's Growth Scoop • 1139 implied HN points • 30 Jun 23
💼 Business Data Management Company Culture Decision-making
  1. Having a data-driven culture is important for making informed decisions and connecting actions to business outcomes.
  2. In many companies, data is not well managed and can lead to frustration when trying to implement a data-driven culture too soon.
  3. Striking a balance and ensuring data accuracy is crucial before pushing for a data-driven culture.

We don’t need data contracts

davidj.substack • 71 implied HN points • 16 Feb 24
🕹 Technology Data Management Data Contracts Data Transformation
  1. Data teams face challenges when separated from product engineering, leading to loss of metadata and concerns about data quality. Data contracts can help address these issues by defining the nature, completeness, and format of shared data.
  2. Integrating data professionals within product teams can enhance understanding and usage of data, reducing the need for separate contracts. This approach allows for direct-to-consumer, organic data processes.
  3. Centralized data platform teams can establish common standards and infrastructure, enabling embedded data personnel in product teams to work efficiently. This collaborative model streamlines data transformation and enhances data accessibility.

How Artificial Intelligence Will Change the Chemical Industry

The Polymerist • 116 implied HN points • 16 Jan 24
🕹 Technology AI Software Data Management R&D
  1. Companies in the chemical industry can benefit from AI tools to improve efficiency and profitability.
  2. AI tools are becoming more accessible for functions like customer relationship management, inventory management, and data organization.
  3. While AI won't replace R&D functions, it can significantly enhance productivity and help companies stay competitive in specialized chemical sectors.

StackAware and Mithril Security: making private AI a reality

Deploy Securely • 117 implied HN points • 12 Jan 24
🕹 Technology AI Cybersecurity Privacy Data Management Artificial Intelligence
  1. Mithril Security offers tools for securing sensitive AI deployments.
  2. StackAware assists companies in managing risks related to cybersecurity, compliance, and privacy in AI deployments.
  3. Partnership between StackAware and Mithril Security combines expertise in AI threats and confidential AI for secure deployments.

Overview of the AI landscape

Software Engineering Tidbits • 98 implied HN points • 22 Jan 24
🕹 Technology AI Machine Learning Data Management Tooling
  1. Large Language Models (LLMs) are key in AI applications like OpenAI's ChatGPT and Anthropic's Claude.
  2. Vector databases and embeddings help understand word associations, with tools like Pinecone and the Embedding Projector by TensorFlow.
  3. Tooling in AI is advancing, with Vellum for versioning prompts and Not Diamond for routing prompts for optimal model response.

3 steps to value focused data product management

Datent • 58 implied HN points • 09 Feb 24
💼 Business Data Management Product Development Project management Innovation
  1. Transitioning from a BI role to a data product team requires defining a Value Gateway to ensure projects deliver tangible benefits.
  2. To manage the progress and accountability of data work, reporting on value at key points is crucial, showcasing the value realized and areas needing support.
  3. Establishing a process around failing fast and doubling down on successful projects, supported by agile project management, is essential for efficient data product management.

How to Deploy Microsoft Sentinel Effectively

Rod’s Blog • 59 implied HN points • 01 Feb 24
🕹 Technology Security Cloud Computing Data Management AI Automation
  1. To get the most out of Microsoft Sentinel, organizations should carefully plan and prepare their deployment by assessing security needs and goals.
  2. Choosing the right subscription and pricing model is crucial for optimizing the benefits of Microsoft Sentinel, based on data requirements, user protection, and features needed.
  3. Effective management of Microsoft Sentinel involves monitoring data ingestion, leveraging AI and ML capabilities, automating workflows, and learning from security incidents and feedback.

Python Lists: A closer look, part 11

Mostly Python • 628 implied HN points • 30 Mar 23
🕹 Technology Programming Data Management Development Python Classes
  1. Copying a list in Python can lead to unexpected behavior if the items in the list are mutable objects.
  2. To create a true copy of a list with mutable objects, use the deepcopy() function from the copy module.
  3. When working with Python lists, consider the nature of the items in the list to decide between using list[:], list.copy(), or deepcopy().

Microsoft Sentinel SOC 101: How to Detect and Mitigate Multiple Microsoft Teams Deleted by a Single User with Microsoft Sentinel

Rod’s Blog • 39 implied HN points • 07 Feb 24
🕹 Technology Security Software Data Management Incident Response Cloud Computing
  1. Use Microsoft Sentinel to detect and respond to multiple Teams deletion events in your organization.
  2. Collect Teams activity logs in Microsoft Sentinel to monitor data and detect security risks.
  3. Write custom analytics rules in Microsoft Sentinel to generate alerts for suspicious activities, such as multiple Teams deletion by a single user.

Introduction To Event-Based Analytics - Issue 142

Data Analysis Journal • 569 implied HN points • 03 May 23
🕹 Technology Data Analytics Product Analytics Data Management
  1. Event-based analytics is crucial for understanding user behavior and product performance.
  2. Session-based analytics focus on website traffic while event-based analytics track user interactions like clicks and actions.
  3. Implementing and maintaining event-based analytics can be challenging due to issues with data integration and interpretation.

Time Scales of UX: From 0.1 Seconds to 100 Years

Jakob Nielsen on UX • 50 implied HN points • 24 Jan 24
🕹 Technology User Experience Web Design AI Organizational Change Data Management
  1. User experience is not a place or thing, but it unfolds over time.
  2. The time scales in UX range from 0.1 seconds to 100 years, with a huge variability.
  3. Design decisions in UX can impact events that last from a fraction of a second to a century, requiring a broad perspective and high IQ to navigate effectively.

A Gentle Introduction to Kafka API

Tributary Data • 1 HN point • 16 Apr 24
🕹 Technology Programming Data Management Distributed Systems
  1. Kafka started at LinkedIn and later evolved into Apache Kafka, maintaining its core functionalities. Various vendors offer their versions of Kafka but ensure the Kafka API remains consistent for compatibility.
  2. Apache Kafka acts as a distributed commit log storing messages in fault-tolerant ways, while the Kafka API is the interface used to interact with Kafka for reading, writing, and administrative operations.
  3. Kafka's structure involves brokers forming clusters, messages with keys and values, topics grouping messages, partitions dividing topics, and replication for fault tolerance. Understanding these architectural components is vital for working effectively with Kafka.

Get a Microsoft 365 Copilot security teardown without hours of documentation review

Deploy Securely • 39 implied HN points • 24 Jan 24
🕹 Technology Security Privacy Data Governance AI Governance Data Management
  1. Microsoft 365 Copilot provides detailed data residency and retention controls favored by enterprises in the Microsoft 365 ecosystem.
  2. Be cautious of insider threats with Copilot as it allows access to considerable organizational data, potentially leading to inadvertent policy violations.
  3. Consider the complexities of Copilot's retention policies, especially in relation to existing settings and the use of Bing for web searches.

LabKey

Axial • 7 implied HN points • 15 Mar 24
💼 Business Startups Data Management Software Development Revenue Models Partnerships
  1. LabKey provides data management solutions tailored to researchers, clinicians, and biotech companies.
  2. LabKey's evolution from a project at Fred Hutchinson Cancer Research Center to a successful software company is inspiring for startups.
  3. LabKey's strategic shift to a tiered subscription service model helped in sustaining revenue and investing in new product development.

Data classification mastery: 5 simple categories for handling sensitive information

Deploy Securely • 19 implied HN points • 07 Feb 24
🕹 Technology Data Management Cybersecurity Data Privacy Regulations AI Governance
  1. Effective AI governance requires clear data classification policies and procedures.
  2. Avoid unnecessarily complex ascending levels of data sensitivity for easier management.
  3. Utilize practical categories like Public, Confidential-Internal, and Confidential-External for better data handling.

Securing Data in an AI-First World with Microsoft Purview

Rod’s Blog • 19 implied HN points • 06 Feb 24
🕹 Technology Data security AI Microsoft Data Management Compliance
  1. Microsoft Purview is a top industry solution for managing data estates, offering governance, protection, and management.
  2. The latest enhancements to Microsoft Purview and Microsoft Defender focus on securing data in the context of generative AI, providing visibility, protection, and compliance controls.
  3. Organizations can leverage Microsoft Purview and Microsoft Defender to securely adopt AI, ensuring data protection while harnessing AI's full potential.

How to Know When Data Retention Values Have Changed for Microsoft Sentinel

Rod’s Blog • 138 implied HN points • 03 Aug 23
🕹 Technology Data Management Cybersecurity
  1. Customers can use a quick KQL query to track changes in Log Analytics workspace data retention values for Microsoft Sentinel.
  2. The provided KQL query can be utilized in various ways such as in a Workbook, a Hunting query, or as an Analytics Rule for notifications.
  3. For ongoing access to the latest version of the query and further discussion, references to the author's resources and accounts are provided.

Eventual Business Consistency

Software Design: Tidy First? • 134 HN points • 04 Aug 23
🕹 Technology Business Data Management Programming Systems Database
  1. The goal is to achieve eventual business consistency by closely matching what's in the system with real-world events.
  2. Different data storage methods like storing dated data or double-dated data come with trade-offs in complexity and accuracy.
  3. Bi-temporal systems use two dates to track when data changes occurred in reality and when they were recorded in the system for better business operations.