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Where can I find free tech stack data for prospect lists?
Use open-source repositories and public datasets to enrich your sales lists with current technology infrastructure details without paying for enterprise databases.
Spotlight
PAGE: https://alison.com/course/introduction-to-data-visualization
PROMISE: Map your 403 tech stack technologies into a clear visual dashboard for your team.
WHO: Analysts and team leads who need to visualize open-source technology data for non-technical stakeholders
WHYNOW: The team is currently holding a list of 403 technologies that requires a visual layer for clarity
DESC: In this free online data visualization course with Google Data Studio, you will learn to visualize raw data and translate it into actionable insights.
BEFORE: Tech stack data sits in a static spreadsheet without visual context
BEFORE: Categorizing 403 technologies requires manual and error-prone sorting
BEFORE: The team cannot easily answer questions about technology distribution trends
AFTER: Tech stack data is displayed in an interactive Google Data Studio dashboard
AFTER: Categorizing 403 technologies happens automatically using defined logic rules
AFTER: The team visualizes technology distribution trends with time-series charts
GAIN: Ability to translate raw technology lists into actionable visual insights
GAIN: Skill in using CASE and IF statements to clean and categorize dataset labels
GAIN: Knowledge of selecting appropriate chart types for different data structures
STEP: The raw list of 403 technologies feels unstructured and hard to interpret for stakeholders. || Translate raw data into impactful data visualizations and uncover meaningful insights || The team views a visual summary of the tech stack rather than a flat list of names.
STEP: Technologies are grouped incorrectly, making it hard to distinguish functional categories. || Categorize and re-label data with CASE and IF statements, and regular expressions || Data points are automatically grouped into clean categories based on logic rules.
STEP: The team struggles to choose the right chart type to show the distribution of tools. || Select the most suitable chart types of your data visualizations (e.g. Tables, time-series, geo maps and more) || The dashboard uses appropriate visual formats that match the nature of the data.
STEP: Stakeholders ask for comparisons of technology adoption over time, which the flat list cannot show. || Compare performance across different date ranges in time-series charts || The team tracks changes in the technology stack over specific periods visually.
NOTFOR: Engineers who need to build custom software integrations or complex ETL pipelines
NOTFOR: Teams requiring immediate automation scripts rather than learning visualization concepts
FACT: Average duration: 3-4 Hours (Contains Video)
FACT: CPD-accredited certificate available
FACT: Beginner level
COVERS: After completing this course, you will be able to:
COVERS: Describe the key principles of data visualization and how Google Data Studio works
COVERS: Translate raw data into impactful data visualizations and uncover meaningful insights
COVERS: Categorize and re-label data with CASE and IF statements, and regular expressions
COVERS: Select the most suitable chart types of your data visualizations (e.g. Tables, time-series, geo maps and more)
COVERS: Compare performance across different date ranges in time-series charts
COVERS: Explain the various data blending and joining techniques available in Google Data Studio
COVERS: Distinguish between single colour and colour grading types of conditional formatting
COVERS: Discuss the options available for creating custom email schedules for your reports
COVERS: Recognize different aggregation types within the data schema
COVERS: Solve data visualization problems that stakeholders might have
COVERS: Google Analytics
MODULE: Data Sources, Functions and Charts || Welcome to the Course! | Creating your Google Data Studio Account | Exploring Data Sources, Tables and Filters | Creating Calculated Fields and Custom Dimensions | Creating a Time Series and Comparing Date Formats
MODULE: Data Blending, Formatting and Collaboration || What is Data Blending and the Concept of JOINs | How to Use Conditional Formatting | Access Permissions and Data Credentials
What you are probably seeing
Your current spreadsheets rely on self-reported forms or outdated manual research, leaving gaps when prospects change their infrastructure between sales cycles.
Sales teams waste hours verifying whether a company actually runs a specific CRM or cloud provider because the list lacks real-time verification signals.
Your conversion rates dip when discovery calls reveal the prospect uses a different tech stack than what your targeting criteria specified.
Why it happens
Static lists decouple from reality because companies frequently migrate between vendors or adopt new tools without updating public profiles or your CRM records.
Enterprise tech intelligence platforms charge premium fees for this data, creating a barrier that prevents smaller teams from maintaining comprehensive coverage.
Open-source initiatives and public crawling projects have democratized access to bulk technology data, allowing teams to self-serve information previously locked behind paywalls.
What changed recently
2026-10-07 · prospect research and data analyst
Open-source repositories now offer free samples for that gap:
• Crawler indexed 51.3M+ companies and their tech stacks
• Sample datasets offer 500 companies per technology
Source: autocomplete
Step by step
1. Search GitHub and GitLab for public datasets or crawler projects that index company technology stacks and download the relevant sample files.
2. Filter the downloaded data to isolate companies matching your ideal customer profile by industry, company size, or specific technology usage.
3. Cross-reference the sampled companies against your existing customer list to identify new leads that currently lack this technology signal.
4. Validate a small batch of the new leads by checking their live websites or public job postings to confirm they still use the identified technologies.
5. Update your CRM fields with the verified technology tags so sales reps can personalize outreach with relevant infrastructure examples.
Ways to go further
Start here: Introduction to Data Visualization For when you want to map the 403 technologies into a visual dashboard for your team. Open the free course on Alison ↗
Better fit: Fundamentals of Open-Source Intelligence (OSINT) For when you want to find which public data sources actually verify a company’s tech stack. Open the free course on Alison ↗
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