Sedona Bulk Fuzzy Text Search Tool

Main Text Source Repository

Android is a mobile operating system based on a modified version of the Linux kernel and other open-source software, designed primarily for touchscreen mobile devices such as smartphones and tablets. Android has historically been developed by a consortium of developers known as the Open Handset Alliance, but its most widely used version is primarily developed by Google. It was unveiled in November 2007, with the first commercial Android device, the HTC Dream, being launched in September 2008. At its core, the operating system is known as the Android Open Source Project (AOSP) and is free and open-source software (FOSS) primarily licensed under the Apache License. However, most devices run on the proprietary Android version developed by Google, which ships with additional proprietary closed-source software pre-installed, most notably Google Mobile Services (GMS) which includes core apps such as Google Chrome, the digital distribution platform Google Play, and the associated Google Play Services development platform. Firebase Cloud Messaging is used for push notifications. While AOSP is free, the Android name and logo are trademarks of Google, which imposes standards to restrict the use of Android branding by 'uncertified' devices outside their ecosystem. Over 70 percent of smartphones based on the Android Open Source Project run Google's ecosystem (which is known simply as Android), some with vendor-customized user interfaces and software suites, such as TouchWiz and later One UI by Samsung and HTC Sense. Competing ecosystems and forks of AOSP include Fire OS (developed by Amazon), ColorOS by Oppo, OriginOS by Vivo, MagicUI by Honor, and custom ROMs such as LineageOS; and Meta Horizon OS for VR headsets.

List of Search Terms

digital camera HTC Dream foldable phones Android 10 Huawei watchOS IntelliJ IDEA IDE Developer Conference microkernel micro kernel micro-kernel Septamber Kalifornia Linax kernel Android Open Sorce Project

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Plan comparison chart

Feature	Free	Pro 1 Day	Pro Monthly
Max. characters processed per file	10000	100000	100000
Max. no. of file uploads processed	20	200	200
Trusted User Benefits (Bypass reCAPTCHA)	No	Yes	Yes

Use Sedona Bulk Fuzzy Text Search Tool to search for approximate strings that are slightly similar, helping to catch typos like “Septamber” in batch or bulk.

 

Example file upload sample template

01. Android OS.docx

02. HarmonyOS.docx

03. iOS.docx

 

 

 

 

 

 

-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)

Related helpful articles around the web for reference

Match, VLOOKUP, and Combine Names and Texts Based on Similarity Scores

The Fuzzy Match add-on for Excel and Google Sheets facilitates the comparison and merging of textual data. It helps in identifying approximate duplicates within a single table or merging similar rows between two tables by using fuzzy matching techniques.

Advanced fuzzy data matching allows for the alignment of non-exact data records. If you’re still relying on spreadsheets for manual data matching, consider upgrading to WinPure’s fuzzy data match tool. It offers enhanced features for comparing multiple data sources, setting match thresholds, and creating custom matching rules.

Fuzzy Diagram NEW 12

WinPure’s fuzzy matching tool uses a proprietary algorithm to streamline customer data by eliminating duplicates across various sources like marketing lists, databases, spreadsheets, and CRMs. With a 97% accuracy rate, it effectively matches names, phone numbers, emails, and physical addresses, ensuring you communicate with the correct individuals.

Clean & Match Fuzzy Matching (1)

Key Features of WinPure’s Fuzzy Data Match:

• Connects with popular databases, CRMs, and file formats.
• Accesses diverse sources, including Text/CSV, Excel, XML, SQL Server, Oracle, MySQL, MS Access, MS Azure, Salesforce, and Zoho.
• Custom match logic and thresholds to suit specific data requirements.
• Custom Word Manager to manage synonyms and business-specific terms, reducing errors and inconsistencies.

SS Matching 3

WinPure offers user-friendly visualizations and detailed match scores, providing clear metrics on match rates, potential duplicates, and confidence levels. This helps in managing data quality and supports data-driven decision-making.

How Customers Utilize Our

 

Fuzzy Match

 

Tool

• Resolves complex duplicates that spreadsheets and CRMs struggle with, achieving up to 80% reduction in duplicate data.
• Facilitates cross-platform matching for deeper insights.
• Matches a variety of data types, including emails, phone numbers, and addresses.
• Enhances GDPR compliance through improved address data matching.

Serving Clients Worldwide

WinPure has assisted businesses and government entities across 50+ countries, serving over 4,000 SMEs with an 89% data matching accuracy and an 87% customer retention rate.

Consolidate Customer Records

WinPure aids marketing teams in consolidating customer data from various sources to achieve complete and accurate customer records.

Recommended by Industry Leaders

Eric Branson, Founder of Highr, and Alexander Goldenberg, Director of IT and Operations, endorse WinPure for its intuitive fuzzy matching and effective data handling capabilities.

Online Tools

• Fuzzy Wuzzy Algorithm

  : A tool for comparing text strings using the Fuzzy Wuzzy algorithm, which improves upon the Levenshtein distance method to offer better accuracy in string matching.

• Fuzzy Matching Algorithm Tools

  : Tools to unlock value from messy and inconsistent data using fuzzy matching to handle spelling errors and variations.

• Find

   

  Fuzzy Matches

   

  Add-on

  : A free tool for Google Sheets to correct fuzzy matches and remove duplicates, offering easy comparison and export options.

• 
  

  Flookup

   

  : A Google Sheets add-on with functions like FLOOKUP, QLOOKUP, and MLOOKUP for fuzzy lookups based on similarity percentages.

• FuzzyWuzzy

  : A Python library for string matching, useful in data cleaning and text mining, though it may be slow with large datasets.

• Microsoft Excel Fuzzy Lookup Add-In

  : Enhances Excel’s data matching capabilities to identify similar but non-identical values, and it’s free to use.

• MatchKraft

  : An online tool for matching company names with advanced algorithms, offering a free plan for exporting up to 100 rows.

Conclusion

Fuzzy matching is crucial for cleaning and unifying data. Tools like Find Fuzzy Matches, Flookup, FuzzyWuzzy, Microsoft Excel Fuzzy Lookup Add-In, and MatchKraft offer various features to improve data accuracy and analysis. They allow users to handle data inconsistencies effectively, making them valuable for efficient data management and decision-making.

Feel free to adjust any specifics if needed!