Aketch  Rachel

Aketch Rachel


How Can I Scrape The Data From A Website I Don't Own?

Why Do You Need To Scrape Data From Websites?

There are lots of different reasons why you need to scrape

data from websites as a business. You can use the data you collect for market research, to make more informed decisions, to answer questions more credibly, and to produce more high-quality content, products, or services that better serve your customers.

As for being an agency, the biggest reason why you’d scrape data would be to help your team come up with creative solutions that solve your clients’ unique challenges.

But collecting data can be very time-consuming. What are the

best strategies for scraping data that make it easy?

Here’s a list of the top five best data extraction tools we recommend that can scrape data from websites by name, zip code, and URL. These data mining tools not only automatically collect data for you, but can also save this data in a useful and readable format like CSV, Excel, or Text files. Some are better for mass data collection while others are better suited for collecting client data like email and phone numbers.

Top 5 Data Scraping Tools To Scrape Data From Websites

Choosing the ideal Web Scraping Tool that perfectly meets your business needs can be a challenging task, especially when there’s a large variety of Web Harvesting Tools available on the internet. To simplify your search, here is a comprehensive list of 5 Best Web Scraping Tools that you can choose from:

1. Anysite Scraper

Anysite Scraper is an incredibly powerful and elegant tool that allows you to build web scrapers without having to write a single line of code. You can build your own web scrapers for multiple websites like Facebook, Twitter, Amazon, eBay, Etsy, Walmart, Yellow Pages, etc.

Anysite Web Data Extractor is targeted at pretty much anyone that wishes to play around with data. This could be anyone from analysts, freelancers, marketers, and data scientists to journalists. If you have a list of website URLs, you can scrape data from these URLs with Anysite Web Crawler. But, If you don’t have the list of URLs, you can find your prospect’s details by name and zip code.

2. Google Map Extractor

If you’re looking for a business scraping tool that can scrape data from Google Maps, Google Maps Data Extractor is the way to go. The Google Maps Scraper helps you quickly find and scrape multiple business listing data from Google Maps.

The Google Maps Data Grabber has the ability to scrape data by business listing URL, business name, and area code. You can store your data in CSV, Excel, or Text file formats. Unfortunately, Google Maps Crawler isn’t free but the subscription plans are affordable.

3. Cute Web Phone Number Extractor

Cute Web Phone Number Scraper is one of the best data collection tools out there for businesses that depend on gathering phone numbers of customers and businesses. The Phone Number Scraper collects the phone numbers database in real-time and analyzes it instantly to help users complete tasks right then and there. The Mobile Number Extractor has the ability to find and scrape phone numbers by person/business name, country code, mobile company code, or website URL.

4. Cute Web Email Extractor

It is a very high-end email scraping tool that provides millions of emails for email marketing. Email Scraper Software is built for both programmers and non-programmers.

You can scrape emails from website URLs and you can find emails by name also. You can find and collect personal email databases, professional email databases, an employee’s email database, business email database by using this email grabber. The email hunter is extremely easy to use because it requires zero coding to use it.

5. Top Lead Extractor

Top Lead Extractor offers two different kinds of web scrapers. You can use it as an email scraper and a phone number scraper. It is the best email and phone number finder software for those who want to collect data from email marketing, SMS marketing, mobile marketing, and telemarketing campaigns. Like all other tools, it requires no coding to use it and provides you data in CSV, Excel, or Text file formats.

#web-scraping-software #data-collection-tools #data-extraction-tools #data-mining-tools #web-scraping-tools

What is GEEK

Buddha Community

How Can I Scrape The Data From A Website I Don't Own?
 iOS App Dev

iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink


Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.


As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Cyrus  Kreiger

Cyrus Kreiger


How Has COVID-19 Impacted Data Science?

The COVID-19 pandemic disrupted supply chains and brought economies around the world to a standstill. In turn, businesses need access to accurate, timely data more than ever before. As a result, the demand for data analytics is skyrocketing as businesses try to navigate an uncertain future. However, the sudden surge in demand comes with its own set of challenges.

Here is how the COVID-19 pandemic is affecting the data industry and how enterprises can prepare for the data challenges to come in 2021 and beyond.

#big data #data #data analysis #data security #data integration #etl #data warehouse #data breach #elt

Macey  Kling

Macey Kling


Applications Of Data Science On 3D Imagery Data

CVDC 2020, the Computer Vision conference of the year, is scheduled for 13th and 14th of August to bring together the leading experts on Computer Vision from around the world. Organised by the Association of Data Scientists (ADaSCi), the premier global professional body of data science and machine learning professionals, it is a first-of-its-kind virtual conference on Computer Vision.

The second day of the conference started with quite an informative talk on the current pandemic situation. Speaking of talks, the second session “Application of Data Science Algorithms on 3D Imagery Data” was presented by Ramana M, who is the Principal Data Scientist in Analytics at Cyient Ltd.

Ramana talked about one of the most important assets of organisations, data and how the digital world is moving from using 2D data to 3D data for highly accurate information along with realistic user experiences.

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment, 3D data for object detection and two general case studies, which are-

  • Industrial metrology for quality assurance.
  • 3d object detection and its volumetric analysis.

This talk discussed the recent advances in 3D data processing, feature extraction methods, object type detection, object segmentation, and object measurements in different body cross-sections. It also covered the 3D imagery concepts, the various algorithms for faster data processing on the GPU environment, and the application of deep learning techniques for object detection and segmentation.

#developers corner #3d data #3d data alignment #applications of data science on 3d imagery data #computer vision #cvdc 2020 #deep learning techniques for 3d data #mesh data #point cloud data #uav data

Uriah  Dietrich

Uriah Dietrich


What Is ETLT? Merging the Best of ETL and ELT Into a Single ETLT Data Integration Strategy

Data integration solutions typically advocate that one approach – either ETL or ELT – is better than the other. In reality, both ETL (extract, transform, load) and ELT (extract, load, transform) serve indispensable roles in the data integration space:

  • ETL is valuable when it comes to data quality, data security, and data compliance. It can also save money on data warehousing costs. However, ETL is slow when ingesting unstructured data, and it can lack flexibility.
  • ELT is fast when ingesting large amounts of raw, unstructured data. It also brings flexibility to your data integration and data analytics strategies. However, ELT sacrifices data quality, security, and compliance in many cases.

Because ETL and ELT present different strengths and weaknesses, many organizations are using a hybrid “ETLT” approach to get the best of both worlds. In this guide, we’ll help you understand the “why, what, and how” of ETLT, so you can determine if it’s right for your use-case.

#data science #data #data security #data integration #etl #data warehouse #data breach #elt #bid data