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Web scraping is useful in many industries, including marketing,  real estate, travel, finance, and many others, since it offers automated data collection from online sources. Some websites, on the other hand, want to prevent their data from being scraped. In order to prevent and limit web scraping activities to their content, websites employ numerous anti-scraping techniques. Aside from anti-scraping challenges, there are other barriers that limit and disrupt web scraping activities, including CAPTCHAs, dynamic content, honeypot traps, etc.  

To help you overcome such challenges, this article highlights the top 7 web scraping best practices.

1. Continously parse & verify extracted data

Parsed data needs to be continuously verified to ensure that crawling is working correctly.

Data parsing is the process of converting data from one format to another, such as from HTML into JSON, CSV, or any other desired format. You need to parse data after extracting it from web sources. This makes it easier for data scientists and developers to analyze and work with the collected data. 

Once you collect data from multiple websites, the data will likely be in different formats, such as semi-structured or unstructured, which is impossible to read and understand. A data parsing tool crawls text sources and builds a data structure using predefined rules. Parsing scraped data is a necessary step for further analysis in order to extract value from it. 

Data parsing can be left to the end of the crawl process but then users may fail to identify issues early on. We recommend automatically and at regular intervals manually verifying parsed data to ensure that the crawler and parser are working correctly. It would be disastrous to identify that you have scraped thousands of pages but the data is garbage. These problems take place when the source websites identify scraping bot traffic as unwanted traffic and serve misleading data to the bot.

2. Choose the right tool for your web scraping project

You can build your own web scraper or use a pre-built web scraping tool to extract data from web sources.

Building a custom web scraper

Python is one of the popular programming languages for building a web scraping bot. It is a good choice for beginners because it has a large and growing community, making it easier to solve problems. Python has a large number of web scraping libraries, including Selenium, Beautifulsoup, Scrapy, and others; you need to pick the most appropriate web scraping library for your project. The following are the basic five steps for creating your own web scraper in Python:

Decide the website from which you want to extract data.

Inspect the webpage source code to view the page elements and search for the data you want to extract.

Write the code.

Run the code to make a connection request to the target website.

Store the extracted data in the desired format for further analysis.

You can customize your own web scraper based on your particular needs. Building a web scraper, on the other hand, takes time because it requires labor. 

Recommendation: If you will extract data from well-protected websites or scrape multiple web pages, you must use a proxy server with your web scraper. Residential and ISP proxies would be ideal solutions to ensure web scraping security and circumvent IP ban issues.

IP addresses of residential and ISP proxies are provided by ISPs (Internet Service Providers) that belong to real people. They provide a higher level of anonymity compared to datacenter proxies.

To help you make an informed decision, we analyzed the top 10 residential proxy providers of 2023 in terms of performance, pricing, and features.

Using a pre-built web scraper

There are numerous open-source and low/no-code pre-built web scrapers available. You can extract data from multiple websites without writing a single line of code. These web scrapers can be integrated as browser extensions to make web scraping tasks easier. If you have limited coding skills, low/no-code web scrapers could be extremely useful for your tasks.

Recommendation: If security is your primary concern in your web scraping activities, you can use a VPN solution in your data extraction process to protect your real IP address and sensitive data. Both proxies and VPNs hide clients’ real IP addresses and assign a new IP address. VPNs, as opposed to proxy servers, encrypt all network traffic between clients and web servers.

3. Check out the website to see if it supports an API

APIs establish a data pipeline between clients and target websites in order to provide access to the content of the target website. You don’t have to worry about being blocked by the website since APIs provide authorized access to data. They are provided by the website you will extract data from. Therefore, you must first check out if an API is provided by the website.

There are free and paid web scraping APIs you can utilize to access and get data from websites. Google Maps API, for example, adjusts pricing based on requester usage and volume of requests. Collecting data from websites via APIs is legal as long as the scraper follows the website’s API guidelines. 


Bright Data’s Web Unlocker helps businesses and individuals overcome any website blocks that may exist while scraping data from websites. Web Unlocker assigns clients a new IP address from a datacenter or residential proxy IP pool.

It sets intervals between requests to make the crawling slower. Otherwise, if you make requests faster than humans, the website will describe you as a bot and block your IP address.

4. Use rotating IPs & proxy servers to avoid request throttling

Websites use different anti-scraping techniques to manage web crawler traffic to their websites and protect themselves from malicious bot activity. Based on visitor activities and behaviors such as the number of pageviews, session duration, etc., web servers can easily distinguish bot traffic from human activities. For example, if you make multiple connection requests to the same website in a short period of time without changing your IP address, the website will label your activities as “non-human traffic” and block your IP address. 

Proxy servers hide clients’ real IP addresses to prevent websites from revealing their identities. Based on their IP rotation, proxy servers are classified into two types: static and rotating. Rotating proxies, as opposed to static proxies such as datacenter and ISP proxies, constantly change clients’ IP addresses for each new request to the target website. Bot traffic originating from a single IP address is more likely to be detected and blocked by websites.

We recommend using rotating proxies, such as backconnect and residential proxies, in your web scraping projects to avoid being blocked by websites.

5. Respect the ‘robots.txt’ file 

A chúng tôi file is a set of restrictions that websites use to tell web crawlers which content on their site is accessible. Websites use chúng tôi files to manage crawler traffic to their websites and keep their web servers from becoming overloaded with connection requests. 

Websites, for example, may add a chúng tôi file to their web server to prevent visual content such as videos and images from appearing in Google search results. The source page can still be crawled by the Google bot, but the visual content is removed from search results. By specifying the type of bot as the user agent, you can provide specific instructions for specific bots. 

Figure 1: The ‘robots.txt’ file for Amazon

6. Use a headless browser

A headless browser is a web browser without a user interface. All elements of a website, such as scripts, images, and videos, are rendered by regular web browsers. Headless browsers are not required to disable visual content and render all elements on the webpage.

Assume you want to retrieve data from a media-heavy website. A web browser-based scraper will load all visual content on the webpage. Scraping multiple web pages would be time-consuming with a regular web browser-based scraper. The visual content in the page source is not displayed by web scrapers using a headless browser. It scrapes the webpage without rendering the entire page. This speeds up the web scraping process and helps the scraper bypass bandwidth throttling. 

7. Make your browser fingerprint less unique

When you browse the internet, websites track your activities and collect information about you using different browser fingerprinting techniques to provide more personalized content for your future visits.

When you request to view the content of a website, for example, your web browser forwards your request to the target website. The target web server has access to your digital fingerprint details, such as:

IP address,

Browser type,

Operating system type,

Time cone

Browser extensions,

User agent,

Screen dimensions, etc.

If your target web server finds your behavior suspicious based on your fingerprints, it will block your IP address to prevent scraping activities. To avoid browser fingerprinting, use a proxy server or VPN. When you make a connection request to the target website, a VPN and proxy services will mask your real IP addresses to prevent your machine from being revealed.

For more on web scraping

Feel free to Download our whitepaper for a more in-depth understanding of web scraping:

For guidance to choose the right tool, check out data-driven list of web scrapers, and reach out to us:

Gulbahar Karatas

Gülbahar is an AIMultiple industry analyst focused on web data collections and applications of web data.





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Why Is Python The Best Language For Web Scraping?

What is Python Web Scraping?

Python Web Scraping is an automatic method of collecting data from the web and its different websites, and performing further operations on the data. These may include storing the data in a database for future references, analyzing the data for business purposes, and providing a continuous stream of data from different sources in a single place.

Some common methods of web scraping

High performance

Simple syntax

Available existing frameworks

Universality of Python

Useful data representation

Let us take a detailed look.

Reason 1: High Performance

Python scripts written for web scraping are highly efficient. Web scraping is limited to just retrieving data from other sources in some languages, whereas in some others, it involves sourcing the data in an unstructured format and appending it together, followed by parsing and saving it as a dataset. Scripts written in Python do all this, as well as representing the scraped data visually with Python libraries like Matplotlib.

Syntax tree = html.fromstring(response.text) text_in_site = tree.xpath(‘IP address/text()’) for title in blog_titles: print(title)

Here we are seeing a scraping script using the lxml library of Python. This library contains a html module to work with HTML, although it needs the HTML string first which is retrieved using the Requests library. This parsed data is then stored in a tree object, and exact data items can be accessed by creating queries using the Xpath() function, from which desired components like text or body of the website can be extracted using appropriate tags.


Step 1 − Import the lxml library

Step 2 − Retrieve the HTML string using Requests library

Step 3 − Parse the scraped data from target website

Step 4 − Obtain individual data elements by using queries

Step 5 − Printing the required data, or using it for further purposes

Example # After response = requests.get() from lxml import html tree = html.fromstring(response.text) blog_titles=tree.xpath('//h2[@class="blog-card__content-title"]/text()') for title in blog_titles: print(title)

This script only runs in dedicated Python IDEs such as Jupyter Notebook/terminals.

Output Blog title 1 Blog title 2 Blog title 3 Reason 2: Simple Syntax

The Python language has one of the easiest and most simple syntaxes of the programming world. This is what makes it one of the easiest languages to learn for beginners. Thus, web scraping scripts written in Python are very small and simple, compared to other languages like C# and C++. This is what makes web scraping using Python so easy to write and execute.

Syntax pip install requests import requests print(response.text)

Here we use the Requests library to perform web scraping, which has one of the easiest and shortest code scripts to execute. The library sends a HTTP request using the GET() function, and then prints the scraped data for the user. This can be used as the basic syntax for the Requests library and can be modified as needed.


Step 1 − Install the Requests library using the console

Step 2 − Send HTTP request to the website server using the REQUESTS.GET() command

Step 3 − Print the received scraped data or use it for necessary representation purposes.

Example import requests from bs4 import BeautifulSoup print("n") soup_data = BeautifulSoup(res.text, 'html.parser') print(soup_data.title) print("n") print(soup_data.find_all('h4'))

This script only runs in dedicated Python IDEs such as Jupyter Notebook/terminals.

Output [Academic, Computer Science, Digital Marketing, Monuments, Machine Learning, Mathematics, Mobile Development, SAP, Software Quality, Big Data & Analytics, Databases, Engineering Tutorials, Mainframe Development, Microsoft Technologies, Java Technologies, XML Technologies, Python Technologies, Sports, Computer Programming, DevOps, Latest Technologies, Telecom, Exams Syllabus, UPSC IAS Exams, Web Development, Scripts, Management, Soft Skills, Selected Reading, Misc] Reason 3: Available Existing Frameworks

The Python language has an extensive collection of frameworks for a wide range of functions and use cases, which includes web scraping as well. Libraries such as Beautiful Soup, lxml, Requests and Scrapy. Using these frameworks for web scraping can be very efficient and effective, and can also support Xpath, HTML and other. These libraries also contain debugging methods, which help in smooth and secure programming.

Syntax driver = Chrome(executable_path='/path/to/driver')

Here we are using Selenium for web scraping, which supports parsing using Javascript, thereby allowing crawling on dynamic websites. Here we require a driver for the browser being used. In today’s era of the entire internet being programmed on Javascript, this library is essential for web scraping.


Step 1 − Installing the Selenium library

Step 2 − Importing the appropriate class for the browser used

Step 3 − Object of the browser is created using the driver

Step 4 − Load the required webpage using the get() method

Step 5 − Extract the neccessary elements from the website, if required

Step 6 − Close the browser object

Example from selenium import webdriver from import Options options = Options() options.headless = True options.add_argument("--window-size=1920,1200") DRIVER_PATH = '/path/to/chromedriver' driver = webdriver.Chrome(options=options, executable_path=DRIVER_PATH) print(driver.page_source) driver.quit()

This script only runs in dedicated Python IDEs such as Jupyter Notebook/terminals.

Reason 4: Universality of Python

Python is one of the most universally used programming languages in today’s world, and is also widely accepted in different aspects. The biggest data collectors and companies in the world use Python, and scripts written in Python can be used with programs written in other languages as well.

Syntax pip import requests import requests print(response.text)

Here we use a web scraping script using the Requests library, which can be used in sync with scripts written in other languages and programming environments as well, thereby making Python scripts universal.


Step 1 − Install the Requests library using the console

Step 2 − Send HTTP request to the website server using the REQUESTS.GET() command

Step 3 − Print the received scraped data or use it for necessary representation purposes.

Example pip import requests import requests print(response.text)

This script only runs in dedicated Python IDEs such as Jupyter Notebook/terminals.

Output Reason 5: Useful Data Representation

The web scraping libraries used in Python can perform not just web crawling and data parsing, they can execute useful representation of data for purposes like business analysis, research and market analysis, and understanding customer feedback. Beautiful Soup is the best for scraping data which can be then displayed via Matplotlib, Plotly and similar libraries.

Syntax response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser')

This is the syntax for a script in Beautiful Soup, where we first get the target url using the Requests library, as shown in earlier examples. Then we search and find the required element from the website in the second line. This received data can be then represented using the appropriate libraries.


Step 1 − Install the Beautiful Soup library

Step 2 − Receive the website url by sending request

Step 3 − Extract the element required from the website

Step 4 − Perform necessary operations with the data like printing/storing etc.

Step 5 − Pass the data to Matplotlib for representation purposes

Example import requests response = requests.get(url) from bs4 import BeautifulSoup soup = BeautifulSoup(response.text, 'html.parser') print(soup.title) blog_titles ='') for title in blog_titles: print(title.text)

This script only runs in dedicated Python IDEs such as Jupyter Notebook/terminals.

Output Conclusion

Thus here we see how web scraping is done using various methods in Python, and also the way in which these methods make Python the best for web scraping. There are several other smaller reasons why Python is great for web scraping, but here we have only mentioned a few. To get a detailed lesson on each of the methods, you can visit their individual learning pages respectively. Python is thus arguably one of the best languages to perform web scraping.

Top 7 Product Data Management (Pdm) Best Practices In 2023

Product data management, or PDM, is an essential part of any business since it enables: 

Data integration 

Smoother supply chain operations 

Efficient product development 


And an overall higher customer satisfaction level. 

However, achieving effective product data management is easier said than done. You can implement a PDM tool, but just throwing money at expensive software will not make all your troubles go away. Effective product data management can be achieved by combining sophisticated software and strategic best practices.

This article explores the top 7 PDM best practices that business leaders must consider to ensure an effective product data management process in their supply chains.

1. Conduct product data transcription 2. Understand the business processes that need to be supported

You must understand how your product data is used across the organization if you wish to streamline the flow and management of that data. Understanding company procedures like marketing, sales, customer support, and operations that rely on product data is necessary to do this.

Once you know which business processes need to be supported by the PDM solution, you can determine the product data requirements for each process. This can help you filter out the unnecessary data fields and prioritize the essential ones.

3. Define your master data management strategy and structure

Your data model serves as an outline for the structure of the product data. How you will govern your product data moving forward is determined by your master data management plan. This covers details like who will have access to modify the data, how changes will be recorded and audited, and how versioning of the data will be managed. 

You can choose from the following data models:

Hierarchical model: In this model, the data has a parent-child-like relationship in which the data is arranged into a tree-like structure. For instance, a sales order has multiple sales items (Child entity) but can only be linked to one sales order (Parent entity).

Relational model: This model involves storing all related data in a single location. For instance, a supplier’s details are stored in one table, with its name, location, contact person, etc.

Entity-relationship (ER) model: This model breaks down your data into different categories to make it more organized. The categories are:

Entities: a product or a customer are separate entities

Relationships: The connections between the entities

Attributes: Something which describes the entity, for instance, product or customer name

Dimensional model: It enables teams to share information across many departments for efficient decision-making and cooperation. This model is mainly used by data warehouses. 

4. Identify which systems and data need to be integrated 4.1. Data integration

You need to also identify which data will be shared across different systems. After that, you need to automate the data-sharing process by using tools such as RPA to make sure the latest data is available throughout the organization.

4.2. System integration

System integration is one of the most important reasons for implementing a PDM tool. You can ensure that your product data is always correct and up-to-date and that all relevant departments have access to it by integrating your PDM system with ERP, PLM, CRM, and eCommerce.

5. Create a process for maintaining product data governance

In the current business environment, products and services are frequently changing. These changes are also reflected in their data. Having a proper product data governance mechanism in place can help you efficiently manage these changes. A governance strategy can contain the following systems:

Key roles, including users who are/are not authorized to make changes

How will the changes be made

A process for approving or rejecting changes

A system for tracking and auditing changes.

A good PDM system can help you streamline your product data management process. Most of the software on the market offer system integrations and automated processes to help simplify your product data management process. 

Considering these best practices will ensure that your PDM tool and business processes are aligned and work in synergy. 

It can also be beneficial to dedicate a team that can regularly update and change the PDM system as the business requirements change.

7. Leverage dashboards and reports to track KPIs

Finally, it is important to track the performance of your projects, and product data is an essential element in measuring that. By using dashboards and reports that monitor KPIs on a regular basis, you can identify problems early and take action before they escalate. You can look for a solution that offers built-in dashboards. Some important KPIs for PDM are:

Data accuracy

Data timeliness

Data completeness

Errors in the data

Further reading References

Shehmir Javaid

Shehmir Javaid is an industry analyst at AIMultiple. He has a background in logistics and supply chain management research and loves learning about innovative technology and sustainability. He completed his MSc in logistics and operations management from Cardiff University UK and Bachelor’s in international business administration From Cardiff Metropolitan University UK.





25+ Best Iphone Apps You Must Have In 2023

It’s been years since Apple revolutionized the tech world with the tagline, “there’s an app for that.” And today, this rings more accurate with the ever-expanding capabilities of apps. If you want a comprehensive overview of which app is worth getting, here are our suggestions for the best iPhone apps.

1. PicMerger Edit Pics & Collages – Editor’s choice

For social media freaks like me, photo editing apps are essential. I heavily rely on PicMerger app on daily basis as it fulfills all my need for picture editing. You can collate photos using 200+ built-in templates and frames, add custom font texts and watermarks, apply textured borders, decorate them with 100 custom stickers, etc.

Though the built-in layouts are good. Additionally, you may merge your photos or screenshots side by side without making a collage. Besides, it allows you to edit your images, crop them to specific dimensions, and export in high quality.


A vast pool of exercises to choose from.

Exercises are simple to understand and follow

Progress tracking is available


Could include more lessons for kids

Price: Free (In-app purchases start from $2.99)


2. VSCO – Manual camera app

VSCO is one of the most popular manual camera apps of all time. The elegant user interface and customization options set it apart from the competition by a huge margin. Besides, in the app’s free version, you can access the photo editor with 10 free presets to stylize your image.

Moreover, the app’s membership provides over 200 options for editing your photos and making them look the way you want. Advanced editing tools such as Split Tones add more depth to image processing. Additionally, there’s a huge VSCO community with helpful members who provide easy tips to subtly improve your photo and video editing skills.

For more options, you can also upload or download custom presets made by creators on the VSCO community. But my only issue with the app is that the free version is highly limited in terms of its features. Membership is the only way to truly experience the VSCO app.


Advanced editing tools

A huge number of presets

Helpful community


The free version is too limited

Price: Free (In-app purchases start from $7.99)


3. Spotify – Music streaming

The world’s most popular music streaming app is a must-have for anyone who enjoys songs and podcasts. It lets you quickly search for and listen to any track, artist, or album. Then, you can create and share playlists to build a personal music collection accessible anytime.

There are tons of premade playlists too, which are ever-expanding, so there’s always more to discover. Of course, you’ll need the premium membership to unlock the full features. Additionally, once you upgrade to the app’s premium version, you can download your favorite songs and enjoy ad-free music.


Premium podcast shows

Create playlists with friends

Support for Apple Watch


Price: Free (In-app purchases start from $3.99)


4. Wallpapers & Widgets: MyScreen – Customize your iPhone

iOS 16 has opened a new world of customization. You can jazz up your Home and Lock screens with this wallpaper app that offers many gorgeous images. MyScreen app offers attractive wallpapers, contemporary themes, new icons, useful widgets, keyboard themes, and top screen packs. 

Also, MyScreen’s Depth Effect Wallpapers are amazing. Besides, the wallpaper shuffle collections let you enjoy new wallpaper every day. I liked its animations for charging. You can choose 3-in-1 themes from an extensive catalog and library.


3-in-1 themes

Charging animation

Custom lock screen and depth wallpapers


Can only make one background in the free version

Price: Free (In-app purchases start from $4.99)


5. iPhone Live Wallpapers for Me – 4K backgrounds

This live wallpaper app can further enhance the look of your screen with beautiful moving pictures. New animations and dynamic themes are added weekly to ensure a constant flow of options. The app’s strong suit is its impressive, well-categorized library of live wallpapers.

You get to choose from so much – time-lapse sceneries, cute pets, mesmerizing patterns, cosmic explosions, and more. Further, you can even create a personal collection of your favorite wallpapers for quick access. But a 5-sec ad after almost every second swipe is quite off-putting.


An amazing collection that gets updated regularly

Convert your videos into live wallpapers

Unlocks secret wallpaper after a 30-sec ad


Drains battery fast

Price: Free (In-app purchases start from $0.99)


6. JustFit: Lazy Workout – Stay fit

So, it’s ideal whether you want to target trouble areas, reduce weight, or develop muscle weight. The fitness app will closely monitor your daily progress. Also, it examines your profile preferences and lifestyle to assist you in achieving your objective more quickly. You may integrate it with Apple Health to measure calories burnt by steps.


Easy to commit with no equipment

Personalized plan

Track daily progress


Subscription billing is buggy

Price: Free (In-app purchases start from $19.99)


If you’re looking for the best yoga app, here’s one that will give you a new yoga practice each time you go to your mat. It offers over 60 thousand configurations and counting, so you never have to repeat a routine.

Moreover, you can choose styles such as Vinyasa, Hatha, Gentle, Restorative, Yin, Ashtanga, Chair, and more. Six different teacher voices and dynamic music offer further personalization. Lastly, it also integrates with the iOS Health app.


Multiple practice styles

Dynamic changing music

Several guide voices


No significant cons

Price: Free (In-app purchases start from $2.99)


8. Calm – Meditation app

Mental peace is as vital as physical health, and a meditation app can make a world of difference. Calm has been repeatedly recognized as one of the best iPhone apps to practice mindfulness, calm anxiety, and cultivate a state of joy. The app offers a new 10-minute program each day to soothe your mind and charge your energy.

There’s a plethora of guided meditations and soothing music to choose from. Even if you’re new to the practice, this app can ease you in and offer varied programs you can follow. So, when you want to reduce stress, expertly crafted music can work magic in cooling your mind.


Masterclasses by experts

Relaxing music

Lots of sleep stories


Pricey subscription

Limited free content

Price: Free (In-app purchases start from $14.99)


9. BetterSleep: Relax and Sleep

The BetterSleep app, previously known as Relax Melodies, improves your sleep with over 300 calming sounds. You can find categories like a crackling fire, wind, ocean, rain, birdsong, etc., natural noises, and white noise for sleeping, such as hairdryers, aircraft, vacuum cleaners, and fan noises. 

Besides, it offers sleep stories, guided meditations, breathing exercises, and a section for people’s favorite mixes. I liked the customization choices in designing soundscapes. With its user-friendly bedtime reminders, sleep tracker, sleep recorder, and quality sleep sounds, you can understand and improve your sleep. 91% of app users report improved sleep after only one week.


Integrated sound mixer

Sleep recorder and tracker

Brainwaves feature  

Regular app content updates 


Only 2 sleep stories and 4 meditations are free

Too many notifications

Price: Free (In-app purchases start from $9.99)


10. Scanner App – Scan documents

In an increasingly digital age, document scanner apps can be incredibly handy. The Scanner App – PDF Editor, is one of the most effective portable document scanners for iPhones. It can convert your device into a quick, portable scanner with automatic text recognition (OCR). Additionally, it allows you to merge multiple PDFs in quick succession.

One of this app’s most salient features is the ability to scan your signature on books, paper notes, invoices, and contracts. Moreover, the scans can be saved as PDF or JPG files also. Last but not least, the Scanner App has the easiest-to-use PDF editor, enabling you to edit your document before sharing it.


Automatic text recognition

Scan your signature

Easy-to-use PDF editor


Can’t zoom in to read a scanned document

Price: Free (In-app purchases start from $2.99)


11. Dashlane – Password manager

Security is essential, and password manager apps make it easier. Therefore, Dashlane is one of the best iOS apps to have on your iPhone because it lets you create and store unlimited secure passwords. Also, it syncs all your sensitive data securely so that you can access them across devices.

It will then autofill the right username and password on every app and website you use, minimizing effort. Besides, you can quickly log in with a look or tap using Face ID or Touch ID. Moreover, the app does not collect your data, ensuring ultimate privacy.


Get instant alerts of unknown logins

Beautiful dark mode

Automatically syncs data across devices


iOS password generation is glitchy

Price: Free (In-app purchases start from $3.49)


12. TapeACall – Call recording

Your iPhone doesn’t have native call recording functionality, but TapeACall is an excellent call recorder app that does the job. Also, it’s among the best paid iPhone apps. You can record incoming and outgoing calls without limit on the duration or number of recordings.

Further, you can upload recordings to cloud services such as DropBox, Evernote, and Google Drive or even email them to yourself in MP3 format. If the list is long, you can save time by giving a unique name to the recordings. The app has a beautiful, easy-to-use interface and is reliable.


Transcribe your recordings

Record scheduled calls

Supports recording Zoom meetings


The free version isn’t very useful

Price: Free (In-app purchases start from $3.99)


13. Fonts – Stylize your fonts

Express yourself better with this font app that lets you customize text and emojis to stand out on Instagram, Facebook, WhatsApp, Snapchat, and other places. It’s over 100k reviews on the App Store and is rated highly.

Further, it ranks as one of the best in the utility category, so you know it’s a must-have. New fonts are added frequently, so you never run out of things to experiment with. There are in-app purchases to unlock access to more features.


Customized keyword themes

Unique symbols and Kaomojis


No significant cons

Price: Free (In-app purchases start from $0.99)


14. TeraBox – Get more storage

I always get issues with storage in my iPhone, and cloud storage apps are a stress reliever. TeraBox is a free cloud storage service offering backing up documents, sharing files, and saving videos. The best part is you will get 1TB (1024 GB) of free cloud storage synced across all your devices.

So, you may upload any kind of file, share them with others in private, and move files to other devices. Also, it has an automatic backup feature. Besides, your uploaded images will be automatically classified into the smart categorized album. So, you can quickly search and find your files. Numerous privacy layers ensure your data is safe.


1024GB of free cloud storage

Multiple privacy protections

Intelligent classified album


Price: Free (In-app purchases start from $2.99)


15. Structured – Best productivity app

Every morning my first task is to make a to-do list and get a schedule for the whole day (even on holidays!). And my breakfast table companion is the Structured app. It boosts productivity more than ever before by ensuring every activity is in one place and waiting to be marked off. You can add Home Screen widgets to keep your chores at the tip of your fingers.

Also, it helps to eliminate distractions by sending alerts ahead of time and offers a precise overview of your activities. You may import calendar events and integrate them with the Reminders app. I loved its recurring tasks feature and VoiceOver assistance. Besides, iCloud synchronization ensures all your devices are always on the same page.


Support for the Reminders app

VoiceOver support

Sync with iCloud


Re-Occurring Subtasks feature has bugs

Price: Free (In-app purchases start from $1.49)


16. Notion – Project management app

Just get an idea? Jot down, plan, and organize all in one location with the Notion app. It’s a must-have among the best iOS apps for students and professionals. The best part is it never runs out of storage space, as your note-taking will be saved on the cloud. You simply drag and drop to create the dashboard, website, document, or tasks.


Turn any Notion page into a website

No more messy folders

Collaborate in real-time


Offline sync needs improvements

Price: Free (In-app purchases start from $4.99)


17. chúng tôi – Email Cleanup

I think most of us are annoyed with spam and subscription emails overflowing our inboxes. chúng tôi helps to clear up your inbox and unsubscribe from unwanted emails, making it easy to navigate. It displays all subscription emails in your inbox and lets you eliminate undesired emails and save the ones you like.

Besides, the roll-up feature archives emails you want to keep subscribed to but don’t want to see in your inbox. You will get a daily digest email summarizing your rolled-up subscriptions. Moreover, you may add numerous email accounts in the app and manage your subscriptions across all accounts. It supports several email apps such as Gmail, iCloud, Yahoo!, Outlook, etc.

To keep your iPhone uncluttered and smooth to navigate, get the best cleaner app.


Unsubscribe in bulk

View rich text easily

Unique Roll Up feature


Some users reported privacy issues

Price: Free


18. Audible – For book lovers

Audible is the most well-known app among book lovers. It offers premium audiobooks, exclusive podcasts, and genre-bending Audible Originals from vast categories. They update the library with new material every week.  

I liked its dedicated widget to return to your last listen with convenient access from the home screen. Besides, you can use it with Apple Watch and CarPlay. So, listen to a podcast while commuting, read bestsellers at your leisure, and download and listen to material offline.

If you are more into audiobooks, check out our hand-picked best audiobook apps list.


Podcasts and audiobooks all in one

Listen offline and download shows

Apple Watch and CarPlay support


Works best with a subscription

Price: Free (In-app purchases start from $7.99)


19. Get food at your doorstep – DoorDash

Okay, so who does not use food delivery apps? They allow enjoying food from the comfort of your home. DoorDash has the largest online selection of restaurants, grocery shops, convenience stores, pet stores, and other local businesses that provide on-demand delivery or pickup. So, you can order freshly cooked meals, groceries, booze, home essentials, etc., in 4,000+ locations throughout the United States, Canada, and Australia.

The best part is you don’t have to pay any delivery charges during your first month of usage. Besides same-day on-demand delivery, you may schedule deliveries after placing an order. Also, they avail of no-contact deliveries. The real-time tracking shows when your order will be delivered. It supports Apple Pay, Venmo, Paypal, and credit cards.


Order food, alcohol, and groceries

Save $5 on average

Schedule deliveries


Has location issues

Price: Free


20. Ibotta – For great savings

Hey shopaholics, attention, please. Ibotta is the best coupon app that gives you cash back when you purchase online or in-store. You just need to check the app for offers before purchasing. Besides, you can submit a picture of your receipt to receive cashback. 

It collaborates with top brands, merchants, and shopping apps such as Uber, chúng tôi Groupon, eBay, etc., to help you save money without the fuss of conventional coupons or promo codes. The company claims Ibotta users have saved 1.6x the inflation rate on groceries.


Easy cash withdrawal

Cash back on gift cards

Bonuses on hitting shopping milestones


Price: Free


21. Waze – Best navigation app

Waze is the best navigation app for iPhone, with the biggest community-based live traffic. In this app, the local drivers update real-time traffic and route information about construction, road hazards, speed traps, etc., from time to time. So, plan your journey accordingly with dynamic routing to save time.

Besides, you can find the cheapest gas along your route to save money. But you must have the internet to access the live map and interact with other drivers. I loved its compatibility with playing music and podcast directly from the app. Besides, you can use it on your car’s display while driving with Apple CarPlay.


Real-time traffic information

Apple CarPlay compatibility

Rerouting automation


Ads on the screen create distractions

Price: Free


You just planned a family outing, and after a few hours, it started raining. Not suitable, right? That’s why you should have a weather app on your iPhone. CARROT Weather provides accurate weather data in a uniquely humorous way. You can access current, hourly, and daily predictions from Apple Weather, Dark Sky, AccuWeather, and

The app is privacy-conscious and promises not to sell your personal information, including your location data, to other parties. I loved its Augmented Reality Mode and ability to create weather report videos like a TV newscast. Besides, regular notifications of precipitation, weather warnings, and lightning strikes keep you updated.


Compatibility with iOS 16 Live Activities and Dynamic Island

Dedicated widget for Home and Lock Screen

Customization of the entire user interface

Get weather Apple Watch face


Needs a subscription to work properly

Price: Free (In-app purchases start from $4.99)


23. BeReal – New era of social media


Not time wasting

Use RealMojis as stickers in your iMessage

Regular unique challenges


Connectivity issues

Price: Free


24. Roblox – For gamers

Roblox has allowed everyone to taste the metaverse and enjoy the ultimate virtual environment where you can create, share experiences with others, and be whatever you want. They have a worldwide community. Every day, there’s something new and interesting for you, thanks to the increasing collection of experiences.


Explore the infinite metaverse

Full cross-platform support

Connect with your friends


No significant cons

Price: Free (In-app purchases start from $0.99)


25. Toddler Learning Game-EduKitty

If you’re a new parent, there are several apps for young children that can help with learning and development. EduKitty features an adorable kitten that guides kids ages 4 and up to learn through fun and games.

It will help your child learn colors, shapes, alphabets, numbers, and other basic building blocks. It’s aimed at building varied foundational skills such as listening and reasoning. The app is available in 12 languages and is an excellent guide for preschoolers.


12 different languages

3D kitten guides

Innovative rewards system


The free version is very limited

Price: Free (In-app purchases start from $6.99)


26. Mathway – Become a math expert

Math apps powered by Chegg can be a great way for children to build and improve their math skills. Mathway is for children aged 4 and older. It covers everything from basic algebra to complex calculus, physics problems, graphs, etc. That’s why it’s called the smartest app for iPhone.

Moreover, it is quick at solving any problem you throw its way. There’s an optional monthly or annual subscription to see the step-by-step solutions. Also, you can subscribe to a live tutor anytime you need extra help.


Snap and solve feature

interactive calculator with different subjects’ equations


Can’t solve word problems

Price: Free (In-app purchases start from $9.99)


27. Canva – Graphic designing

Canva is your best friend for designing anything you want. This graphic designer app gives you countless templates to create everything from social media posts to posters, wallpapers, websites, resumes, animations, and more. Also, it has the capability to edit videos, make PowerPoint slides, and much more.

You can also create custom designs from scratch using our own images, text, and many elements such as clipart, backgrounds, and more. Further, a pro membership lets you unlock more properties to use in your designs.


Thousands of templates

All-in-one photo and video editor

Make mockup for anything


The website is much better than the app

Price: Free (In-app purchases start from $0.99)


28. InShot  – Video editor for iPhone

Here’s a video editing app that makes it easy to create engaging video stories in just a few minutes. InShot not only lets you edit videos but also pictures and lets you create collages. It allows you to combine multiple videos at a time. The merging speed can be slow, though.

Its video editor brings many features. For instance, you can trim, cut, or split videos easily. And adding music or a voice-over to your video is easy. It also lets you add stickers to videos, and if you want to animate stickers, there’s an edit section offering various effects, including background blurring.


Make video collages

Add voice effects

Smooth slow motion and transitions


The free version leaves a watermark

Price: Free (In-app purchases start from $1.99)


In 2023, you must have these iPhone apps! ( Video )

Summing Up!

You may also like to read:

Author Profile


Ava is an enthusiastic consumer tech writer coming from a technical background. She loves to explore and research new Apple products & accessories and help readers easily decode the tech. Along with studying, her weekend plan includes binge-watching anime.

Etl Testing Best Practices In 2023

Extract, Transform, and Load (ETL) is a crucial process in data warehousing, where data is extracted from multiple sources, transformed to fit the target schema, and then loaded into a data warehouse. ETL testing is a critical step in ensuring the quality and accuracy of the data loaded into a specific location.

ETL testing is a complex and challenging task that requires a deep understanding of data and the ETL process. In this article, we will discuss some of the best practices for ETL testing that can help you improve the quality of your data and minimize errors during the ETL process. ETL testing can be helpful for sectors that handle a lot of data, frequently from different sources.

1- Automate your testing

Automation in testing is essential to ETL testing best practices. Automating your ETL testing processes helps you save time, reduce errors, and increase efficiency. You can use ETL testing tools to automate repetitive testing tasks and generate detailed reports.

2- Understand the data

To perform ETL testing effectively, it’s crucial to thoroughly understand the data being processed, including its


Format Structure,

Expected output.

This knowledge will help you identify potential issues and anomalies in the data, ensuring that the final output meets the business requirements.

3- Plan your testing strategy 

Develop a comprehensive ETL testing plan that covers all aspects of the ETL process, including data extraction, transformation, and loading. This plan should define the testing scope, methodology, expected outcomes, and tools &resources required to execute the plan.

An example of a testing strategy could be in the following order:

Data Extraction Testing: Verify that the data is being extracted from the correct source system

Data Transformation Testing: Verify that data is being transformed correctly and consistently

Data Loading Testing: Verify that the data is loaded into the correct target system

Data Reconciliation Testing: Compare the data in the source system to the data in the target system to ensure that the data has been accurately transformed and loaded

Regression Testing: Conduct regression testing to ensure that changes to the ETL process do not impact existing functionality. Verify that the ETL process works correctly after system upgrades or changes.

Performance Testing: Test the performance of the ETL process for both small and large data sets. Verify that the ETL process performs within acceptable time and resource constraints. Investigate and resolve any performance issues.

Error Handling Testing: Test error handling for different scenarios, such as invalid data, network failures, and system errors

Security Testing: Test the security of the ETL process, including data encryption, authentication, and access controls. Verify that the ETL process complies with regulatory and security requirements.

4- Use test data wisely

The quality of your test data is critical to the success of your ETL testing efforts. Use representative data sets that simulate real-world scenarios and edge cases and cover various data types and formats.

Real-world scenario data:

Patient demographic data, such as: name, age, gender, and contact information

Medical history data, such as: diagnoses, medications, procedures, and allergies

Claims data, such as: billing codes, dates of service, and insurance information

Provider data, such as: physician names, practice locations, and credentials

Edge case data:

Patients with unusual or rare medical conditions that require special handling

Patients with multiple or overlapping medical conditions that require complex data transformations

Claims with incorrect or incomplete billing codes

Invalid or missing patient and provider information

5-Verify data integrity

As part of your ETL testing efforts, you should verify the integrity of the data being processed. This includes checking for data accuracy, completeness, consistency, and conformity to data standards and rules.

Here are two ways to verify data integrity for ETL testing:

Data profiling: Profiling the data before and after the ETL process can help you identify data quality issues, such as missing or duplicate data, and validate the accuracy of the data. Data profiling tools can help you compare source data to target data, identify patterns and anomalies, and highlight discrepancies.

Data reconciliation: Comparing the data in the source system to the data in the target system is an effective way to verify data integrity. You can identify missing, duplicated, or inconsistent data by comparing the source and target systems data. You can also use data reconciliation tools to automate this process and generate reports highlighting discrepancies.

The ETL process transforms data from its source to the target format. It’s essential to validate these transformations to ensure the data is transformed correctly and consistently. You can use two crucial aspects of software testing to complement ETL testing and strengthen the ETL process:

Unit testing: This testing is typically done using mock data and test cases that cover various data scenarios. By testing each transformation individually, you can identify and fix any issues early in the ETL process.

Integration testing: Integration testing involves testing the entire ETL process to ensure that the data is transformed accurately and consistently. This testing typically uses real-world data and test cases covering various data scenarios. You can identify and fix data transformations and flow issues by testing the ETL process.

Check our article “Integration Testing vs Unit Testing” to understand the difference between the two practices

7-)Test data loading 

The final step in the ETL process is to load the data into the target system. It’s essential to test the data loading process to ensure that the data is loaded correctly and that there are no data loss or corruption issues.

If you have further questions about ETL testing, reach out to us

He received his bachelor’s degree in Political Science and Public Administration from Bilkent University and he received his master’s degree in International Politics from KU Leuven .





Why Must Text Data Be Pre

This article was published as a part of the Data Science Blogathon


these. In fact, machines can’t understand any text data at all, be it the word “blah” or the word “machine”. They only understand numbers. So, over the decades scientists have been researching how to make machines understand our language. And thus they developed all the Natural Language Processing or NLP Techniques.

What is Natural Language processing?

Natural language processing or NLP is a branch of Artificial Intelligence that deals with computer and human language interactions. NLP combines computational linguistics with statistical, machine learning, and deep learning models, allowing computers to understand languages. NLP helps computers to extract useful information from text data. Some of the real-world applications of NLP are,

Speech recognition – The task of converting voice data to text data.

Sentiment analysis- The task of extracting qualities like attitudes, emotions, etc. The most basic task in sentiment analysis is to classify the polarity of a sentence that is positive, negative, or neutral.

Natural language generation – The task of producing text data from some structured data.

Part-of-speech (POS) tagging – The task of tagging the Part of Speech of a particular word in a sentence based on its definition and context.

process text data are Count Vectorization, Tf-Idf Vectorization, etc. These techniques help to convert our text sentences into numeric vectors. Now, the question arises, ‘Aren’t we processing the data using these techniques? So why do we need to pre-process it?’ This article gives an explanation for that doubt of yours. Instances of python code are also provided.

Need for Pre-Processing

Raw text data might contain unwanted or unimportant text due to which our results might not give efficient accuracy, and might make it hard to understand and analyze. So, proper pre-processing must be done on raw data.

Consider that you scraped some tweets from Twitter. For example,

” I am wayyyy too lazyyy!!! Never got out of bed for the whole 2 days. #lazy_days “

The sentences “I am wayyyy too lazyyy!!!” and “I am way too lazy”, both have the same semantic meaning, but gives us a totally different vibe, right. Depending on how these data get pre-processed, the results also differ. Pre-processing is therefore the most important task in NLP. It helps us remove all the unimportant things from our data and make our data ready for further processing.

Some Python libraries for text pre-processing Natural Language ToolKit (NLTK) :

NLTK is a wonderful open-source Python library that provides modules for classification, tokenization, stemming, tagging, etc.


Gensim is also an open-source Python library that mainly focuses on statistical semantics— estimation of the meanings of words using statistical methods, by looking at patterns of words in huge collections of texts. gensim.parsing.preprocessing module provides different methods for parsing and preprocessing strings.

Sci-kit Learn:

Some modules in sci-kit learn also provide some text preprocessing tools.  sklearn.feature_extraction.text provides a module for count vectorization, CountVectorizer() that includes text preprocessing, tokenizing, and filtering of stop words.  CountVectorizer() module contains preprocessor (it strip_accents and lowercase letters), tokenizer, stop_words as attributes. If set, this module does these for you along with count vectorizing- converting the text documents to a matrix of token counts.

Each data and task requires different pre-processing. For example, consider the sentence, “I am wayyy too lazyyy!!!”. If your task is to extract the emotion of the sentence, the exclamation marks, and how the words “wayyy” and “lazyyy” are written, all these become important. But if your task is just to classify the polarity of the sentence, these do not become important. So you can remove the exclamation marks and stem the words “wayyy” to way and “lazyyy” too lazy, to make further processing easier. Depending on the task you want to achieve, the steps for pre-processing must also be carefully chosen.

Some simple steps to pre-process the given example tweet for the basic sentiment analysis task of classifying the polarity are given below. Here I have used the gensim library.

The first step of data pre-processing is,

encoding in the proper format

. utils.to_unicode module in the gensim library can be used for this. It converts a string (bytestring in encoding or Unicode), to unicode.

import gensim from gensim import utils s=" I am wayyyy too lazyyy!!! Never got out of bed for the whole 2 days. #lazy_days " s = utils.to_unicode(s) print(s)


I am wayyyy too lazyyy!!! Never got out of bed for the whole 2 days. #lazy_days

Then convert all the uppercase letters to lowercase. “Never” and “never” are the same word, but the computer processes both as different words.

s = s.lower()  print(s)


i am wayyyy too lazyyy!!! never got out of bed for the whole 2 days. #lazy_days

Remove the tags and punctuations. They behave like noise in the text data since they have no semantic meaning.

import gensim.parsing.preprocessing as gp s=gp.strip_punctuation(s) s=gp.strip_tags(s) print(s)


i am wayyyy too lazyyy never got out of bed for the whole 2 days lazy days

Remove all the numbers, because we are preparing the data for basic sentiment analysis (positive, negative, or neutral classification), where numbers are not important.

s=gp.strip_numeric(s) print(s)


i am wayyyy too lazyyy never got out of bed for the whole days lazy days

Also, get rid of the multiple white spaces.

s=gp.strip_multiple_whitespaces(s) print(s)


i am wayyyy too lazyyy never got out of bed for the whole days lazy days

language. ‘Is’, ‘and’, ‘the’, etc are some stop words in English. It can improve accuracy a lot.

s=gp.remove_stopwords(s) print(s)


wayyyy lazyyy got bed days lazy days

Stemming is also a very important step. Stemming is the process of reducing the words to their roots. For example, ‘stemming’ to ‘stem’. The stem_text() function returns porter stemmed version of the string. Porter stemmer is known for its speed and simplicity.


These output strings can be used for further processing to convert into numeric vectors using techniques like Count Vectorization.

For our task of basic sentiment analysis, we have seen how to pre-process a single tweet till now. Hope you have understood each step clearly. The above processes can be done to a  dataset of tweets.

import pandas as pd import gensim from gensim import utils import gensim.parsing.preprocessing as gp df = pd.read_csv(folderpath) #consider that df['tweets'] column contains tweets. def preprocess_text(s): s = utils.to_unicode(s) s = s.lower() s=gp.strip_punctuation(s) s=gp.strip_tags(s) s=gp.strip_numeric(s) s=gp.strip_multiple_whitespaces(s) s=gp.remove_stopwords(s) s=gp.stem_text(s) return s df['tweets']=df['tweets'].apply(str) #to convert each row of tweets column to string type df['tweets']=df['tweets'].apply(preprocess_text) #pass each row of tweets column to preprocess_text()

Thus, we have preprocessed our dataset of tweets.


Preprocessing text data is one of the most difficult tasks in Natural Language processing because there are no specific statistical guidelines available. It is also extremely important at the same time. Follow the steps that you feel are necessary to process the data depending on the task that you want to achieve.

Hope you enjoyed this article and learned something new. Thank you for reading. Feel free to share with your study buddies, if you liked this article.

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