Methodology, Provenance and Dataset

Methodology and provenance for the TechEco DZ dataset: 629 published companies, 268 economic landmarks and 16 digital specialties across Algiers and Béjaïa.

Last exported: July 16, 2026

629published companies
268published economic landmarks
629assessed profiles
16controlled tech specialties

What the dataset contains

Every published record has a stable identity. Companies may include sector, subsector, address, coordinates, website, social profiles, Google observations, nearby landmarks and calculated scores. Landmarks include their type, position, economic context and nearby companies.

Sources, verification and publication

Discovery combines Google Maps business search through Serper, public company websites and OpenStreetMap for geographic landmarks. Sources remain distinct: an OSM coordinate does not become a Google rating, and an imputed average is never displayed as an observed review.

Verified records are published. Duplicates, generic listings, companies confused with landmarks and other doubtful records are quarantined: they remain archived to prevent re-import, but are excluded from public pages, statistics, structured data and sitemaps.

Popularity scores

Popularity combines 0-10 submetrics for Google review volume and rating, digital presence, economic-landmark proximity and tech-hiring potential. When reviews are absent, observed means from the same city provide a neutral calculation baseline only; no fabricated rating or review count is displayed.

Digital presence measures only observable, owned channels: up to 7 points for a declared, reachable website with useful page breadth (about, services, careers and contact), and up to 3 points for validated social-platform diversity. An address or Maps listing alone does not count. Job postings feed the separate hiring signal to avoid double-counting.

Role-level hiring potential

A structured LangChain agent assesses exactly 16 controlled specialties. Each estimate is calibrated toward a sector baseline according to evidence strength. Generic claims such as “this industry needs SEO” are not company-specific evidence. The score represents potential need, not a job vacancy.

  • Frontend & web developmentWeb interfaces and browser applications.
  • Backend & software developmentServer-side systems, APIs and general software engineering.
  • Mobile developmentNative and cross-platform mobile applications.
  • Embedded systems & IoTEmbedded software, electronics firmware and connected devices.
  • Data analytics & BIReporting, business intelligence and data analysis.
  • Data engineeringData platforms, pipelines and warehouse engineering.
  • AI & data scienceMachine learning, artificial intelligence and statistical modelling.
  • DevOps, cloud & SRECloud infrastructure, deployment automation and reliability.
  • CybersecurityInformation security, security operations and risk controls.
  • IT systems & networksIT support, systems administration and networking.
  • QA & software testingSoftware quality assurance and test automation.
  • Digital product & project managementDigital product ownership and technology project delivery.
  • UI/UX & product designUser research, interaction design and digital product interfaces.
  • Graphic & visual designBrand, marketing and visual communication design.
  • ERP/CRM implementationEnterprise software configuration, consulting and implementation.
  • Digital marketing & SEOSearch, social, performance marketing and digital acquisition.

Limitations and correct use

  • No hiring-potential score confirms an open position.
  • Public information may be incomplete or change after the export date.
  • Rankings are comparative within a city and are not commercial endorsements.
  • Pages without sufficient populations are not created or remain non-indexed.