The hottest Data Management Substack posts right now

And their main takeaways
Category
Top Technology Topics

A Song of Junk and Value

davidj.substack • 95 implied HN points • 03 Jan 24
🕹 Technology Data Management
  1. Data dashboards can become like old, unused bookmarks, cluttering up space.
  2. Having standard data models and a semantic layer could lead to a more efficient data analysis experience.
  3. It's important to focus on creating value in data analysis by asking complex questions and optimizing processes.

Zero ELT could be the death of the Modern Data Stack

The Orchestra Data Leadership Newsletter • 19 implied HN points • 13 Nov 23
🕹 Technology Data Management
  1. Zero ELT aims to streamline data processing by eliminating traditional extraction, loading, and transformation tools.
  2. Zero ELT tools are evolving to focus more on use-case specialization rather than functional grounds, leading to a trade-off between stack complexity and having the best tool for the job.
  3. Zero ELT tools, while promising in simplifying processes, may create data silos, lack interoperability with other tools, and bring about stack complexity issues.

Food Fraud Incidents 2025 (Searchable List)

The Rotten Apple • 31 implied HN points • 04 Jan 25
🍲 Food & Drink Data Management
  1. There is a searchable list of recent food fraud incidents from 2025. This can help people easily find information on specific cases.
  2. Incidents before September 2022 are stored in a database on Trello for reference. It's good to have a place to look for older information too.
  3. New insights about food vulnerabilities are still being added to this database, showing that the issue of food fraud is ongoing. Keeping up with this information is important for everyone's safety.

This once hot data trend from a few months ago got resuscitated by our industry’s data sweetheart

The Orchestra Data Leadership Newsletter • 19 implied HN points • 27 Oct 23
🕹 Technology Data Management
  1. Data Mesh is a decentralized approach to enterprise data management, focusing on distributed datasets and data ownership within domains.
  2. DBT Mesh is a set of features that allow multiple teams to work on dbt projects with less friction, enabling separate repositories and orchestration capabilities.
  3. Having separate dbt jobs run across projects on a schedule is limited, requiring external workflow orchestration tools for more flexibility.

#100 - Playing Offense

davidj.substack • 95 implied HN points • 15 Nov 23
💼 Business Data Management
  1. Data quality starts with the Product Requirements Document and Analytics Requirements Document.
  2. For product changes, defining data requirements through a Data Design Document is crucial.
  3. Being part of the product development process improves efficiency, speed, and collaboration in data management.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

GroupBy #6: Meta developer tool, trillions of data points at Discord and Uber's data cycle management

VuTrinh. • 19 implied HN points • 24 Oct 23
🕹 Technology Data Management
  1. Meta has introduced developer tools that help manage large-scale projects efficiently. These tools assist engineers in solving problems and improving systems.
  2. Big companies like Discord and Uber are using massive data points to create valuable insights. This helps them to effectively manage their data and understand trends better.
  3. Data engineering continues to evolve, with tools like BigQuery and dbt Mesh enhancing data practices. Staying updated with these tools can improve data analysis and management.

Semantic Superiority - Part 1

davidj.substack • 143 implied HN points • 22 Mar 23
🕹 Technology Data Management
  1. A semantic layer simplifies accessing and organizing business data by using common business terms.
  2. Without a semantic layer, organizations risk confusion, poor decision-making, and inconsistency in data usage.
  3. Having a well-maintained semantic layer facilitates quick decision-making, consensus building, and effective risk management.

I fought a DDoS and lived to tell the tale

FunkByteTech • 3 HN points • 03 Jun 24
🕹 Technology Data Management
  1. Prepare for unexpected challenges like DDoS attacks by having suitable defenses like Web Application Firewalls (WAF) in place.
  2. Stay vigilant and adaptive during a DDoS attack, making use of tools like Load Balancer access logs and being ready to block traffic from unwanted sources.
  3. After facing a DDoS attack, reflect on the experience to learn and improve, reinforcing your defense mechanisms for potential future attacks.

Why You’re Missing The Point Of Analytics

Three Data Point Thursday • 19 implied HN points • 05 Oct 23
🕹 Technology Data Management
  1. Analytics and Business Intelligence are about turning data into actionable insights, not just analyzing historical data.
  2. Separating data into 'hot' and 'cold' categories can lead to cost savings and less complexity in data management.
  3. Be cautious of the term 'data product' as it can have different meanings to different people, and ensure clarity in hiring, marketing, and tool usage.

What Suboptimal Public Transit and Your Data Pipelines Have in Common

Bytes, Data, Action! • 19 implied HN points • 05 Sep 23
🕹 Technology Data Management
  1. Public transit and data pipelines both aim to move things from point A to point B smoothly and quickly.
  2. Issues like delays, lack of visibility, and missed connections can disrupt the experiences of both public transit and data pipelines.
  3. Efficient, transparent, and reliable practices are key to ensuring a smooth journey for both public transit users and data pipelines.

The Oracle Effect

Sector 6 | The Newsletter of AIM • 19 implied HN points • 02 Oct 23
🕹 Technology Data Management
  1. Oracle wants to make the cloud more accessible and open for everyone. They believe it's important for all companies to have equal access to cloud technology.
  2. They are pushing to enhance the use of generative AI in business applications and are working on new tools for industries like healthcare.
  3. Oracle has set an ambitious target to grow their company by $15 billion in three years. They want to stand out among big cloud providers like AWS and Google Cloud.

We don’t need data contracts

davidj.substack • 71 implied HN points • 16 Feb 24
🕹 Technology Data Management
  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.

AirBnB sends employees Home

Technology Made Simple • 59 implied HN points • 30 Apr 22
🕹 Technology Data Management
  1. Remote work is becoming more common and offers numerous benefits, so mastering skills like Cyber Security can be advantageous.
  2. Efficient data compression and transmission can save companies money in the era of remote work, making it a valuable skill to develop.
  3. As more interactions shift to digital platforms, learning to create interactive content or platforms for remote communication can present lucrative opportunities.

Getting to 4,000 Cybersecurity Vendors

The Security Industry • 26 implied HN points • 10 Dec 24
🕹 Technology Data Management
  1. The number of cybersecurity vendors has increased significantly, from around 467 in 2003 to over 4,000 today. This shows how important cybersecurity has become over the years.
  2. Many early cybersecurity companies have disappeared, each with its own story, which highlights the changing landscape in the industry.
  3. There is a new wave of AI-focused security companies emerging, indicating trends and advancements in cybersecurity solutions.

What's a data migration?

Technically • 29 implied HN points • 12 Nov 24
🕹 Technology Data Management
  1. Data migration is the process of moving information from one place to another, like relocating files when changing devices. It involves transferring various types of data, such as documents and databases, to ensure everything is in the right spot.
  2. Migrations can be complex and risky, often causing errors or service disruptions if not done carefully. This makes it crucial for companies to have good planning and oversight to avoid losing important data or negatively affecting users.
  3. There are many reasons to migrate data, such as upgrading technology or meeting new security regulations. Companies often need to adapt to growth or changes in the market, which can lead to costly and lengthy migration projects.

Launching a Cyber Marketplace

The Security Industry • 10 implied HN points • 16 Jun 25
🕹 Technology Data Management
  1. A new Cyber Marketplace is being launched to help users easily find and research over 11,400 cybersecurity products. It will provide helpful reports and features for making informed decisions.
  2. The marketplace is designed for various users, including security professionals, consultants, and IT teams. It aims to simplify product evaluations to save time and improve clarity in the cybersecurity field.
  3. With AI tools evolving quickly, this marketplace hopes to stay ahead of competition by offering accurate and structured data. It wants to ensure that users can access reliable information quickly without the usual sales pitches.

Under the Hood

Sarah's Newsletter • 59 implied HN points • 29 Mar 22
🕹 Technology Data Management
  1. Python's popularity is due to its ease of use and readability, making it one of the top 5 most popular languages.
  2. Abstractions like AWS Lambda can be efficient but may become harmful if not managed properly, leading to issues like security and cost concerns.
  3. Using SQL GUI tools for data aggregation can speed up the process but may lead to inaccurate results and wrong decisions due to lack of testing and QA processes.

Data Quality

Data Thoughts • 39 implied HN points • 21 Jan 23
🕹 Technology Data Management
  1. Data quality is all about how useful the data is for the specific task at hand. What is considered high quality in one situation might not be in another.
  2. There are several key aspects of data quality, including accuracy, completeness, consistency, and uniqueness. Each of these factors helps to determine how reliable the data is.
  3. Improving data quality involves preventing errors, detecting them when they occur, and repairing them. It's about making sure the data is accurate and useful over time.

(1/3) “Relational Database Management: A Status Report” [Chris Date, 1983]

Minimal Modeling • 101 implied HN points • 10 May 23
🕹 Technology Data Management
  1. The video discusses the historical background of relational databases, starting in 1983.
  2. Key points include the slow process of database system installation and the importance of primary keys in database design.
  3. Discussion on relational operations like join and divide, emphasizing the significance of these operations in practical database management.

Semantic Superiority - Part 2

davidj.substack • 107 implied HN points • 29 Mar 23
🕹 Technology Data Management
  1. Semantic layers reduce repetitive code by providing a consistent framework for queries.
  2. Semantic layers enhance data security by controlling access and reducing accidental exposure of sensitive data.
  3. A semantic layer defines entities and structures, while a metrics layer is a subset that focuses mainly on defining data models.

Viewing Microsoft Sentinel Rules with MITRE Tactics Directly in Excel

Rod’s Blog • 19 implied HN points • 09 Jan 23
🕹 Technology Data Management
  1. Known options for viewing Microsoft Sentinel rules with MITRE tactics include the MITRE ATT&CK Workbook, the MITRE ATT&CK Blade, Threat Analysis & Response Solution, and the Sentinel REST API.
  2. A lesser-known trick is to view the list directly in Excel by accessing a .csv file on the Microsoft Sentinel GitHub repository and importing it into Excel.
  3. By following simple steps, you can leverage Microsoft Excel to analyze and manipulate the Microsoft Sentinel rules and MITRE tactics data.

We need to talk about Excel

davidj.substack • 95 implied HN points • 10 May 23
🕹 Technology Data Management
  1. Excel is still widely used in the data space for its ease of use and versatility
  2. Data teams aim to reduce Excel use due to limitations such as scalability and version control issues
  3. New tools like Count and Equals are emerging to address Excel limitations and improve collaboration in data analysis

In search for ideal CDP for B2B SaaS

nonamevc • 24 implied HN points • 10 Nov 24
🕹 Technology Data Management
  1. Customer Data Platforms (CDPs) are becoming important for B2B SaaS companies by helping them unify data from different sources. This makes it easier for teams to work together and drive better marketing and sales efforts.
  2. There are two main types of CDPs: packaged and composable. Packaged CDPs are more like ready-made solutions, while composable CDPs allow for customization to better fit a company's specific needs.
  3. B2B companies might not need a standalone CDP as many existing tools are starting to include features traditionally offered by CDPs. This means businesses can often get what they need from tools they are already using.

Metricalypse Now

davidj.substack • 107 implied HN points • 15 Feb 23
🕹 Technology Data Management
  1. Two approaches to metrics layers: wide datasets without defined data models vs. defined data model for more powerful metrics.
  2. Importance of new semantic layer by dbt Labs acquiring Transform for a universal standalone analytics solution.
  3. Opportunity for data consumption vendors to integrate with new dbt semantic layer for a ubiquitous solution.

Sort is now available on the AWS Marketplace!

Database Engineering by Sort • 23 implied HN points • 28 Oct 24
💼 Business Data Management
  1. Sort is now on the AWS Marketplace, making it easier for businesses to manage data changes. This means users can quickly add Sort to their systems.
  2. Sort helps streamline data change management with a simple process for proposing and approving changes. It makes it easy for teams to fix errors or update records without hassle.
  3. Every data change is logged by Sort, creating a clear history of what changes were made and why. This feature ensures full transparency and helps maintain high data quality.

Will active metadata eat the orchestrator?

Data People Etc. • 88 implied HN points • 27 Mar 23
🕹 Technology Data Management
  1. Active metadata is a dynamic way to manage and use metadata across different parts of the data stack.
  2. Active metadata can potentially replace triggering mechanism aspect of data orchestrators, but not the optimization intelligence.
  3. The true value of active metadata lies in empowering business users by acting as a personal data assistant.

How Sort Made It to the Front Page of Product Hunt

Database Engineering by Sort • 15 implied HN points • 27 Jan 25
🕹 Technology Data Management
  1. Preparation is key for a successful launch. It helps to choose the right day and have a strong online presence ready.
  2. Engaging with your community can make a big difference. Personal messages and social media can help gather support and votes.
  3. A clear value proposition shows how your product solves real problems. Highlighting what makes your product unique is important for attracting attention.

Excelibur

davidj.substack • 71 implied HN points • 17 May 23
🕹 Technology Data Management
  1. Excel scalability can be improved by integrating technologies like DuckDB for handling larger datasets.
  2. Enhancing data cleanliness through exposing hidden issues to the user for resolution.
  3. Implementing a full semantic layer in Excel could make data pulling easier and more secure.

Clouded Judgement 6.13.25 - The Battle for Data Ownership

Clouded Judgement • 7 implied HN points • 13 Jun 25
🕹 Technology Data Management
  1. You might think you own your data, but companies can make it hard to use. For example, Slack has new rules that limit how you can access your own conversation data.
  2. If other apps like Salesforce or Workday follow Slack's lead, it could become really tough for companies to use their data in AI projects. This means you might not have as much control as you thought.
  3. The fight for data ownership is a big deal right now. As software shifts towards AI, who controls the data will be a key factor in how companies operate.

16 Cybersecurity Startups Selected for Google Growth Academy

The Security Industry • 11 implied HN points • 16 Feb 25
🕹 Technology Data Management
  1. IT-Harvest is part of Google's Growth Academy for 2025, focusing on supporting cybersecurity startups. This helps them connect with experts and gain valuable resources.
  2. The platform has evolved to meet the needs of security teams, showing strong interest in their data tools and features. Users can now map their security tools to important frameworks like NIST CSF.
  3. They are using AI to streamline data collection and analysis, which makes understanding cybersecurity products faster and easier. This change has made their tools more appealing to companies and consultants alike.

Maze: A Different Type of Security Company

Why Now • 6 implied HN points • 11 Jun 25
🕹 Technology Data Management
  1. Maze has recently raised $25 million in a Series A funding round and is already used by Fortune 500 companies, showing early success in the cybersecurity space.
  2. The number of software vulnerabilities is growing quickly, with a drop in the average time it takes for these vulnerabilities to be exploited. This means businesses need to stay ahead of the threats.
  3. Due to a lack of data on vulnerabilities, companies may need to look for new ways to access information. This situation could open up opportunities for new solutions in vulnerability management.