Technology Tales

Metabase offers an open-source analytics platform designed to enable users to interact with data through natural language queries, AI-assisted tools and visual interfaces, allowing teams to generate insights without requiring extensive technical expertise. It supports integration with over 20 data sources, provides features for creating and sharing dashboards and includes tools for managing permissions, securing data and embedding analytics within applications. The platform is used by many organisations and includes advanced capabilities such as model creation, SQL editing and caching to enhance performance, alongside enterprise-level compliance and security measures. Its flexibility and ease of use make it suitable for startups and larger enterprises seeking to streamline data analysis and reporting processes.

BlueSky Statistics is a data analysis tool designed for professionals in statistics, quality control, engineering and related fields, offering a user-friendly interface available in multiple languages. It integrates advanced statistical methods, machine learning and quality management features, with recent updates including an interactive graph builder that allows dynamic creation of visualisations through drag-and-drop functionality.

The software is used globally by thousands of organisations and individuals, supported by a range of collaboration tools and the ability to export analyses to common formats. Users have transitioned from other platforms due to its comprehensive feature set, ease of use and cost-effectiveness, with testimonials highlighting its suitability for applications ranging from Six Sigma to biostatistics. The company participates in industry events and provides training resources through partnerships, positioning itself as a versatile alternative to proprietary statistical software.

Top ten database attacks

Enterprise databases face numerous serious security threats, many of which stem from poor configuration, inadequate design or insufficient oversight. Misconfigured cloud databases remain a persistent problem, frequently exposing vast quantities of sensitive data due to weak authentication or failure to properly restrict public access. SQL injection continues to be a highly damaging attack vector, exploiting poorly written application code to extract or manipulate database contents, while weak authentication practices such as storing passwords in plain form or failing to implement multifactor authentication leave systems unnecessarily vulnerable.

Privilege abuse and excessive privileges both pose significant internal risks, with users potentially exploiting legitimate access rights beyond their intended scope, particularly when role changes are not properly managed. Inadequate logging and auditing undermine an organisation's ability to detect and investigate suspicious activity, and denial-of-service attacks can render systems unavailable through either network flooding or resource exhaustion. Running unpatched software dramatically increases exposure to known vulnerabilities, and insecure overall system architecture can allow an initial breach to cascade into a much broader compromise. Finally, inadequate backup practices, particularly where backups remain reachable from a compromised environment or are not encrypted, leave organisations dangerously exposed to ransomware and other destructive attacks. Addressing these threats requires a combination of strong technical controls, sound procedural practices and regular risk assessment.

Excel Formula Generator

Formula Bot is an AI-powered data analysis platform aimed primarily at marketers and data teams, enabling users to upload, connect and combine data from multiple sources and then query that data using plain language in any language. The platform can generate interactive charts and graphs, perform data transformation tasks such as cleaning, merging and reshaping datasets, and carry out text analysis functions including sentiment detection, keyword extraction and language translation.

Users can export results to Excel, create formatted reports and schedule recurring analyses to run automatically on a daily, weekly or monthly basis. Additional capabilities include a curated data explorer, embeddable analytics, web scraping, code transparency showing the underlying Python, SQL or R generated for each request, and a knowledge base for improving query accuracy. Security features include end-to-end encryption via AWS infrastructure, row-level access controls and isolated sandbox environments for each session, with a stated commitment to never using customer data for AI model training.

Six tips for better spreadsheets

Nature examines how widely used spreadsheet tools such as Microsoft Excel and Google Sheets are frequently misused, drawing on insights from data scientists and researchers. Stephanie Labou, a data-science librarian at the University of California, San Diego, highlights common pitfalls encountered in practice, including errors arising from manually entered data such as GPS coordinates. The piece offers six practical tips aimed at improving how spreadsheets are structured and used, with the broader goal of encouraging more reliable and reproducible data handling in scientific and research contexts.

Apache Superset

An open-source data exploration and visualisation platform, Apache Superset offers a range of tools for users to interact with data through intuitive interfaces, including a drag-and-drop chart builder, SQL query capabilities and pre-installed visualisations. It supports integration with numerous databases, from traditional systems to modern cloud-native solutions, and provides features such as data caching, customisable dashboards and semantic layers for complex data transformations. Designed to be lightweight and scalable, the platform enables teams to create interactive dashboards, explore datasets and perform detailed analysis using cross-filters and drill-down functionalities. Adopted by numerous organisations, it is used for self-serve analytics, allowing users to generate insights without requiring extensive technical expertise.

FOSS For Spectroscopy

A comprehensive catalogue of free and open-source software for spectroscopy has been compiled, covering techniques including NMR, IR, Raman, ESR/EPR, fluorescence, XRF, LIBS and UV-Vis, though mass spectrometry and MRI software are deliberately excluded. The catalogue currently lists 405 entries, the majority written in R or Python, and draws information directly from the respective project repositories and developer pages.

Each entry is lightly vetted to exclude incomplete or unclear projects, and a status date is provided for each to indicate the most recent repository activity, issue filing or package submission, serving as a rough indicator of whether a project is actively maintained. Related resources are also acknowledged, including a comprehensive survey of R packages suited to metabolomics, a curated collection focused on Raman spectroscopy and a task view covering chemometrics and computational physics.

9 Free Harvard Courses to Learn Data Science

8 Free MIT Courses to Learn Data Science Online

Both Harvard and MIT offer free online data science courses through their respective open learning platforms, covering a progression from beginner programming through to advanced machine learning. The Harvard pathway consists of nine courses, primarily taught in R, that move through programming basics, data visualisation, probability, statistics, data pre-processing, linear regression and machine learning, culminating in a capstone project that brings all the learnt skills together. The MIT pathway takes a similarly structured approach, beginning with an introductory Python programming course before moving into statistics, foundational mathematics including calculus and linear algebra, and finally an intermediate machine learning programme that requires prior knowledge of all the preceding subjects.

While the MIT courses are noted for their depth and relatively fast pace, the Harvard sequence is designed to cover the full data science workflow in a more applied manner, giving learners the opportunity to work with real-world data throughout. Both pathways are available to audit at no cost, though certificates of completion carry a fee, and all courses are hosted on the edX platform in the case of Harvard and MIT OpenCourseWare in the case of MIT.

The Book of OHDSI serves as a comprehensive resource detailing the Observational Health Data Sciences and Informatics collaborative, covering its community, data standards and analytical tools. Organised into five sections, it explores topics such as the common data model, standardised vocabularies, data analytics use cases, evidence quality assessment and methodologies for conducting studies within a distributed research network.

Aimed at both newcomers and experienced participants, the book provides theoretical explanations alongside practical guidance on implementing OHDSI initiatives, including cohort definition, population-level estimation and patient-level prediction. It is developed using open-source tools and maintained through continuous community contributions, with updates reflected in the online version to ensure alignment with evolving software and methodologies.

Observational Health Data Sciences and Informatics

The Observational Health Data Sciences and Informatics initiative brings together researchers, healthcare professionals and data scientists globally to enhance healthcare through large-scale analysis of observational health data. Based at Columbia University, the programme develops open-source tools and fosters collaboration across diverse stakeholders to generate real-world evidence that supports informed clinical decisions and improves patient outcomes. It hosts international events such as the 2026 Global Symposium, which aims to showcase innovations and strengthen partnerships in advancing healthcare research. The organisation also provides educational resources, software and a platform for sharing findings, with ongoing efforts to expand its network and impact through community engagement and scientific exchange.