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Visualise your data quality with Power BI

Don’t confuse the mSQL’s decision logic with simple counts and values of conventional ‘data profiling’ solutions. mSQL - is wildly different. mSQL not only gives you in-depth data insights into your ‘contact data’  - it performs deeper ‘qualitative’ analysis to measure the quality of your contact data and the trustworthiness of each record. 

With our Power BI integration, we bring that data to life with data analytics and rich interactive visualizations!


‘Powerful’ Contact Data Profiling 
360Science + Microsoft Power BI


360Science

mSQL

              +

             


       

In Private Beta

Matching and unifying contact data in Alteryx
Just got A LOT EASIER, FASTER and MORE ACCURATE!

Say hello to 360Science - and say no to #DataGymnastics and #RegExHell

THE CONVENTIONAL METHOD

A Flawed Approach

Matching algorithms are too limited in their ability, and It’s not reasonable to rely on extracted, transformed and standardized data. to create uniform matchkeys. It doesn't represent the realities of realities of data, it doesn't work for efficiency and it doesn’t work at scale. 

Requires significant preprocessing. Records must be parsed, standardized, correctly formatted... 

Results are binary

Common errors cause many matches to go undetected.


BUT THE FACT IS: Data isn't perfect

Example Conventional Match Code:
First Name (3) + Soundex Last Name (4) + Street Number (3) + Street Name (4) + ZIP (5)

Alteryx's "Conventional Matching" Processes

Alteryx is a fantastic platform, but let’s face it, trying to match and unify contact data in it isn’t easy - as a matter of fact it’s downright hard!

It’s a long iterative process of trial and error, playing with various algorithms and matchcodes just to figure out how to get ‘adequate’ results. What most people don’t realize is, the underlying algorithms and processes Alteryx and every other Data Quality, Data Integration and Data Analytics Platform relies on - are fundamentally flawed.






OUR APPROACH TO MATCHING 
is like nothing you've seen before

01

Data Wrangling Not Required

IMAGINE... a world where unifying customer data didn’t require a toolbox of regular expressions to extract, transform and standardize data before matching it? 

Customer Data Analytics has never been Faster,
Easier, or more Accurate!

We love Alteryx... but trying to match and unify contact data in Alteryx isn't exactly easy

  • Requires significant preprocessing. 
  • Data must be normalized, parsed, standardized, corrected, enriched and formatted... 
  • Results are binary
  • Common errors cause many matches to go undetected.

Alteryx fuzzy matching provides you a toolbox of regular expressions -what you want is answers, data, and results - and you want them fast!


CRM and customer data is unique - and if you are going to match, clean and maintain “contact data” you need a data matching engine built from the ground up for that purpose. 

Our team of engineers, data scientists and developers have created AND perfected the industry’s most accurate and effective contact data matching engine. Unlike conventional matching processes using a library of algorithms like Soundex, metaphone and Levenstein, 360Science identifies potential duplicates by taking a 3-dimensional view of the data, never relying on any single item of data being correct or consistent! 

More intelligent than conventional data matching processes - The logic identifies and strips out noise words, such as ‘of’ & ‘the’. AND it creates relationships between words like (‘cars’ & ‘motors and ‘inc’ & ‘incorporated’’).  AND the tokens account for miskeyed data. AND the tokens account for the consonant sounds, AND the vowel sounds, AND the stressed syllables in the name.

360Science logic analyzes the full contact record, not just a comparison of fields. It internally identifies, isolates and groups information into their logical parts (such as name and address elements) to identify suspect matches. Then it grades them!


Seriously - does anyone without a PhD in Applied Mathematics and Computational Science really know the difference between Jaccard Similarity, Dice's Coefficient and Levenshtein - or where to apply them on a given field of contact data?

A Matching Engine must handle data in a number of different formats, and process data that is parsed or unparsed. It must also simultaneously process data in different file systems and formats that contain a combination of parsed and unparsed content.

Unlike Alteryx’s native conventional matching processes – 360Science  doesn’t require data extraction, transformation, standardization, correction or manipulation prior to matching – and it doesn’t even require two different data sources to be normalized into a common format or a target database!

360Science is amazingly tolerant to the wide variations specific to customer data - even on large datasets from disparate sources! The 360 Matching Engine treats address lines as an object. It does not rely on corrected, standardized or normalized addresses to effectively locate matches. And it doesn’t require the same number of address lines in each record to compare the addresses.

Smarter Matching Logic

02

360Science Intelligent Matching Engine “encapsulates”  multiple algorithms, lexicons and process into one “intelligent” process to ensure that all types of difference are detected. Essentially, taking a 3-dimensional view of the data, never relying on any single item of data being correct or consistent!  

The logic identifies and strips out noise words, such as ‘of’ & ‘the’. AND it creates relationships between words like (‘cars’ & ‘motors and ‘inc’ & ‘incorporated’’).  AND the tokens account for miskeyed data. AND the tokens account for the consonant sounds, AND the vowel sounds, AND the stressed syllables in the name.

Notice these are “AND” statements. not separate procedures like Alteryx’s conventional data matching processes.








Multiple Techniques - One Intelligent Matching Engine

Intelligent Scoring Logic

03

The 360Science Matching Engine incorporates a robust pre-tuned yet highly configurable scoring engine, that is tightly connected the matching process.

It’s different and far more intelligent than conventional process that rely on match keys to match data. The 360Science engine intelligently prepares the data for matching, analyzes the database to find records with points of similarity, and then scores them to determine the amount of similarity.

You can instruct the 360 Matching Engine to identify “Automatic False-Positives” or “Automatic Positive Matches”. You can even weight individual attributes positively or negatively - creating matching and unmatching probabilities that will increase or decrease the composite score.

The 360 matching engine includes default rules for most customer data matching requirements, but the matching logic AND the scoring rules are also fully user configurable to give you control. You can identify duplicates using any data e.g. account number, Social Security Number, phone number, date of birth, blood type, eye color, shoe size – or anything else known about the customer.

"360Science's Matching Engine achieves results that are like human perception". Data Analyst | Major Media Company

ProTip for Data Scientists, Analysts, and DBA's...

The 360 Engine can identify Individual level, household level, and business level matches all in one routine - without the need to rerun analysis, create a new Matchcode or generate new match keys on the data!

Alteryx + 360Science

But is it Fast?

"With 360Science we reduced data matching process times from hours to 6 minutes!
These were big numbers... like 160 million records."         Yeah It's FAST!

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