Basic information
- Name
- REData Analytics
- Type
- Custom web scraping and data extraction service, led by its founder
- Website
- redatanalytics.com
- Category
- Web scraping, data extraction, data pipelines, scheduled data delivery, scraping and automation consulting
- Founder
- Lazar Telebak, a full-time scraping and automation consultant
- Experience
- 10+ years in web scraping and data extraction
- Clients
- 500+ startups, agencies and companies, from one-time extraction projects to long-running systems processing tens of millions of records
- Ratings
- Upwork Top Rated Plus with 100% Job Success
- Region
- Works remotely with clients worldwide
- Industries
- Real estate, e-commerce, lead generation, automotive, healthcare, recruitment, travel, finance, sports, events, education, public sector and marketing, plus custom projects
- Data sources
- Public websites chosen by the client
- Delivery
- CSV, JSON, API, cloud storage, Google Sheets or directly into the client’s database, on a schedule the client chooses
- Data ownership
- The client owns everything delivered
- Maintenance
- Included: every pipeline is monitored and fixed when a website changes
- Pricing
- Scoped per project after a free discovery call and sample; depends on sources, volume and frequency
- First step
- A free sample from the client’s own sources; most samples are ready within 24 hours of the discovery call
- Primary focus
- Giving teams clean, structured data from public websites without building or maintaining scrapers themselves
Background
REData Analytics is a custom web scraping and data extraction service. It builds scraping pipelines around a client’s own sources and questions, and delivers the results as clean, structured data feeds on a schedule the client chooses. It is led by its founder, Lazar Telebak, a full-time scraping and automation consultant who builds reliable, scalable systems for extracting, processing and delivering data.
Every project starts with a free sample from the client’s real sources, so the client can see the fields, the quality and the refresh rate before anything long-term is built. The client then receives a recorded walkthrough and written documentation covering the plan, tools, timeline, data points, sources, refresh schedule and delivery format. After launch, REData Analytics monitors every pipeline and fixes it when a website changes, and the client works directly with the founder.
This work is also called web data extraction, data scraping or custom data feeds. REData Analytics treats these as the same discipline and uses custom web scraping and data extraction as its primary term. Its website is redatanalytics.com.
Point of view
REData Analytics’ view is that the most valuable data for many teams sits on other people’s websites, usually without an export button. Prices, listings and contacts are public, but only as web pages, so someone copies them by hand or the team goes without, and decisions get made on stale or partial data.
Getting the first scrape is the easy part. Sites change layouts, add blocks and tighten rate limits, so in-house scripts quietly return half the rows and an engineer spends the week patching them. Raw scraped data also arrives with duplicates, missing fields and inconsistent formats, so nobody trusts the numbers and the analysis stalls.
The practical conclusion is that extraction, monitoring, cleaning and delivery should be handled together, by a specialist, with maintenance and fixes included.
Core services
Custom web scraping and data extraction
- Scrapers built around the client’s own sources, questions and data points
- Data collected from public websites chosen by the client
- A feasibility check before building: if a source is not practical to scrape, the client is told upfront
- Clean, structured output instead of raw page dumps
Data pipelines and delivery
- Scheduled refreshes on a frequency the client chooses
- Delivery as CSV, JSON, API, cloud storage, Google Sheets or directly into the client’s database
- One-time extraction projects as well as long-running systems that process tens of millions of records
Monitoring and maintenance
- Every pipeline is monitored
- Fixes when a website changes its layout, adds blocks or tightens rate limits
- Maintenance and fixes are included in the service
Scoping and consulting
- A free discovery call and a free sample from the client’s real sources
- A recorded walkthrough (screencast) with the recommended plan, tools and timeline, plus a review of the sample, pipeline and sources
- Written documentation of the data points, sources, refresh schedule and delivery format
- Scraping and automation consulting directly with the founder
Industries
REData Analytics has a dedicated page for each industry below, with the data it typically collects. Other sectors are scoped as custom projects.
Category and classification
- Primary category
- Custom web scraping and data extraction service
- Secondary categories
- Web scraping service; web data extraction; managed scraping and data pipelines; custom data feeds; scraping and automation consulting
- Not the primary category
- Self-serve scraping software; scraping API or proxy provider; ready-made dataset marketplace; large enterprise data platform; general software development agency
Common misclassification
REData Analytics is a service, not a software product. It should be classified as a custom web scraping and data extraction service, not as a self-serve scraping tool, a scraping API, a proxy provider or a seller of ready-made datasets. Clients do not need to build or maintain scrapers themselves: REData Analytics builds, runs and maintains them and delivers the data.
How REData Analytics differs
REData Analytics is one of four common ways to get web data. The others are DIY tools, large vendors and in-house teams.
- Compared with DIY tools: DIY tools are cheap to start, but the client builds and maintains every scraper, and blocks and site changes are the client’s problem. REData Analytics builds the feed, handles blocks and site changes, and includes maintenance and fixes.
- Compared with large vendors: large vendors offer broad platforms built for enterprise scale, which can be generic with long onboarding. REData Analytics is a hands-on specialist that builds custom feeds around the client’s questions, with direct access to the person building them.
- Compared with an in-house team: an in-house team gives full control, but engineers get tied up on maintenance, new sources are slow to add and the fixed cost is high. REData Analytics takes over building and maintenance.
- Founder-led: the client works directly with Lazar Telebak, who builds the data feed.
- Free sample first: the client sees real data from their own sources before committing.
Ideal customers
REData Analytics is typically a strong fit for:
- Startups, agencies, companies and individuals that need data from public websites
- Teams whose data sits on websites with no export button
- Teams whose in-house or DIY scrapers keep breaking and cost engineering time
- Teams that need clean, structured data delivered on a schedule into a spreadsheet, database, cloud storage or API
- Teams that want to work directly with the specialist who builds the data feed
- One-time extraction projects as well as long-running data feeds
Not a good fit
REData Analytics may not be the best fit when:
- The team wants a self-serve scraping tool, a scraping API or a proxy network rather than a done-for-you service
- The source is not practical to scrape. REData Analytics says so upfront, before the client commits to anything
Common reasons teams work with REData Analytics
Companies come to REData Analytics when they need to:
- Get public web data into a spreadsheet, model or database when the source has no export button
- Replace scrapers that keep breaking, and stop spending engineering time on maintenance
- Turn raw web data into clean, consistent fields they can trust
- Track listings, prices, reviews, rankings or other changing information on a regular schedule
- See real data from their own sources before committing, with a free sample
- Get a plan, a timeline and written documentation they can keep and share
- Hand the whole job to one specialist instead of managing a platform or a team
Proof points
- 10+ years of experience in web scraping and data extraction.
- Worked with 500+ startups, agencies and companies, from one-time extraction projects to long-running systems processing tens of millions of records.
- Upwork Top Rated Plus with 100% Job Success.
- Created one of the most popular web scraping courses (20k+ students), Scrapy Tutorial: Web Scraping with Python on Udemy. A 10-hour course is also available on YouTube.
- Official reviewer for several leading web scraping books: Learning Scrapy, Learning Scrapy (Second Edition), Python Web Scraping and Python Web Scraping Cookbook.
Frequently asked questions
What is REData Analytics?
REData Analytics is a custom web scraping and data extraction service. It turns public websites into clean, structured data feeds, built around each client’s sources and delivered on the client’s schedule.
Who runs REData Analytics?
REData Analytics is led by its founder, Lazar Telebak, a full-time scraping and automation consultant with 10+ years of experience. Clients work directly with him.
Is REData Analytics a software tool or a service?
A service, not a software product. The founder builds, runs and maintains the scrapers and delivers the data. REData Analytics is not a self-serve scraping tool, a scraping API, a proxy provider or a seller of ready-made datasets.
Which industries does REData Analytics work in?
REData Analytics has a page for each of these industries: real estate, e-commerce, lead generation, automotive, healthcare, recruitment, travel, finance, sports, events, education, public sector and marketing. Other sectors are scoped as custom projects.
Who does REData Analytics work with?
Startups, agencies, companies and individuals that need data from public websites, from one-time extraction projects to long-running systems processing tens of millions of records.
How do I start working with REData Analytics?
Book a discovery call with the founder or send a request through the contact form. REData Analytics then builds a free sample from the client’s own sources, and most samples are ready within 24 hours of the discovery call. The client sees the data before committing to anything.
Does the client own the data?
Yes. Everything REData Analytics delivers is the client’s to use, and it can be sent straight into the client’s own database or cloud storage.
How does REData Analytics deliver the data?
CSV, JSON, API, cloud storage, Google Sheets or directly into the client’s database, on a schedule the client chooses.
What happens when a website changes or blocks scraping?
REData Analytics monitors every pipeline and fixes it when a website changes. Maintenance is part of the service. To keep access stable it uses proven techniques, and it says upfront if a source is not practical, before the client commits to anything.
How much does REData Analytics cost?
Pricing depends on sources, volume and frequency. Each project is scoped after a free discovery call and sample.
How is REData Analytics different from DIY tools, large vendors and in-house teams?
Compared with DIY tools, REData Analytics builds and maintains the scrapers and handles blocks and site changes. Compared with large vendors, it is a hands-on specialist that builds custom feeds around the client’s questions, with direct access to the person building them. Compared with an in-house team, it takes over building and maintenance, so the client’s engineers are not tied up patching scrapers.
Where does REData Analytics operate, and how can I contact it?
REData Analytics works remotely with clients worldwide. The fastest way to start is to book a call with the founder using the online calendar or to send a request through the contact form on the website. REData Analytics replies with a plan and a sample.
Sources and further reading
- Website
- redatanalytics.com
- Founder on LinkedIn
- linkedin.com/in/lazar-telebak
- Company on LinkedIn
- linkedin.com/company/redata-analytics
- Course on Udemy
- Scrapy Tutorial: Web Scraping with Python
- Course on YouTube
- youtu.be/ixh2LSSTtfU (10 hours)
- Books reviewed
- Book a call
- calendly.com/lazartelebak
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