Reifier Product Brief

© Nube Technologies

Better decisions through better data


About Myself and Nube- AI and Big data- Nube Products - Reifier, Crux and HIHO - IIT Delhi, 98.- International Speaker, Program Committee

Strata Hadoop World Singapore - Cofounder from IIT Kanpur, 97


Customer Feedback

Before Reifer we had to use a lot of manual efforts to identify potential duplicates in customer data, now the system can learn patterns and find duplicates for us

intelligently. It’s a breakthrough to a long-standing issue of our businesses.”

- Mr. Dave Chan, Regional Director Business Intelligence, UBM Asia


Reifier Coverage

http://youtube.com/v/eD3LkpPQIgM

http://youtube.com/v/RVw9GqXOq2E

http://youtube.com/v/Gq4wWa6gChU


Reifier - Coverage


Part of MapR App Gallery, Partner with Cloudera, AWS and HortonWorks

Reifier Industry Validation


Business Data is spread across many systemsDiscovering information a challenge - which are the entities

whom we need to address?Consolidating information a challenge - not sure if the data is

tied back to a single entityEnhancing data a challenge - are these new records genuine

or do they already exist?

Business Challenges


The problem - lake or swamp?According to Gartner, businesses lose upto 25% of potential revenue due to lack of multichannel view of data. 67% data scientists say cleaning, organizing and linking data is their most time consuming task, and 52.3% cite poor data quality as their biggest challenge.


50 shades of data

Name Company Telephone

Dave C UBM Asia +91-8800541717

D Chan UBM 8800541717

Dave Chan UBM A

Dave UBM Asia 880-0054-1717


Reifier advantage- Any variety of data (person name,

organization, address, telephone, mobiles, cameras..)

- Any language(english, chinese, japanese, thai..)

- Any scale(thousands to millions and billions)- Without any coding


Name Company Telephone

Dave C UBM Asia +91-8800541717

D Chan UBM 8800541717

Dave Chan UBM A

Dave UBM Asia 880-0054-1717

Reifier Output - Multiple fields of different types


Reifier Output - Word swapping with Different Cases, Leading and Trailing Spaces

Zyka's Kitchen 124 Queen Stshop 2 Cleveland

Zyka's Kitchen

Shop 2 124 Queen Street

Cleveland

CHATTHA RAJVINDER SINGH

SINGH CHATTHA RAJVINDER


Reifier Output - Differences Sony Xperia M C1905 4GB Unlocked Smartphone YellowSony Xperia M C1905 4GB (Yellow) (IMPORTED)

Sony Xperia Z2 D6503 (Black) (IMPORTED)(IMPORTED) Sony Z2 D6503 (Black)Sony Z2 D6503 Black

Panasonic DMC-3D1 Lumix 12MP 4x Optical Zoom Panasonic Lumix DMC-3D1 12.1MP 4x Optical Zoom Digital Camera


Reifier OutputSares Regis GroupSares-Regis Group

1800 Got Junk 83 Newmarket Road Lutwyche

1-800-GOT-JUNK 83 Newmarket


Reifier Output

BA ONE SILKS AHAMED SHAFEEQ

18/5 EPPERY HIGH ROAD PERIMEET

[email protected]

B A ONE SILKS AHMED SHAFIQ 18/5 YEPPERY HIGH RD, PERIMEET

[email protected]


Reifier Output - AbbreviationsAXA REIMAXA Real Estate Investment Managers

International Trade U 1 8 Ives Street

International Trade Unit 1 8 Ives Street


Match various languages - thai, english, japanese, chinese..Baby Gap เสื้อยดืแขนสัน้ ลายจุดBaby Gap เสื้อยดืแขนสัน้ ลายขวาง

aera โซฟาเบด โดรา รุน่ FF01-A01-DR aera โซฟาเบด โดรา รุน่ FF01-A01-DR แพค็คู่ (Purple/Pink)


Data volumes are highEach record has multiple dimensionsExact matches are rareComparing each record with every other is not possibleThere are many disparate systemsLanguages have unique issues

Technical Challenges for Matching


Discovering and maintaining rules for data quality is extremely tough

Custom coding and domain specific logic makes maintenance a nightmare

No one size fits all, big custom implementations needed every time even after using existing tools

Technical Challenges for Matching


Point and Shoot - Zero configLearns similarity definitions from dataNo hard coding of business rulesHighly scalable - runs on open source Apache SparkAdvanced Machine Learning algorithms pick most optimal

solutionDomain agnostic, can work with various kinds of dataUtilities to create labeled data available - just point it to the

data

Reifier Features


Handles different languages - English, Chinese, JapaneseHighly accurate resultsAvailable as a library or as a private/public cloud

deploymentREST interfaceAJAX based web front endReal time as well as batch supportSupport and Documentation through web based support

portal http://reifier.freshdesk.com

Reifier Features

http://reifier.freshdesk.com/


Case Study - UBM Asia- Deduplication of marketing data- Combination of English, Chinese, Japanese

and other languages- Upto 1 million new records per week- Temp can do only about 800 records per day- AWS Hosted, yearly license- Reference customer


Case Study - Government of India - Invited for data matching for intelligence

agencies- Reifier outperformed leading international

competition 2x on accuracy and >10x for speed

- Matched 40million records


A local search company lists millions of regional businesses. They also source business information from third parties. Reifier helps the search company compare their existing listings with potential listings from third parties, and keeps their directory up to date and free from duplicate data.

Case Study - Directory Service


A banking institution uses Reifier to run loan applications against credit listing data to ensure that they are not dealing with blacklisted individuals and corporates.

Case Study - BFSI


Case Study - BFSIA leading insurance provider uses Reifier to prevent fraudulent claims. By creating a centralized consolidated data repository, the company reduces overexposure of an individual who has multiple policies. By matching records, Reifier also helps find out average policy per individual and household.


A credit rating company utilizes Reifier to consolidate personal credit histories from different sources and provide accurate ratings to their customers.

Case Study - BFSI


A telecom company offers various products and services and wants to cross sell to existing customers. Existing information is fuzzily matched for accurate customer segmentation and marketing.

Case Study - Cross Selling


Case Study - RegulatoryRegulatory compliance of all kinds - including related to policies, taxes, privacy, anti terror, and anti money-laundering - require matching up data pulled from a variety of sources. With Reifier, organizations meet regulatory mandates with capabilities that support everything from simple deduplication of customer lists to matching data against government lists of suspected terrorists.


A services company sources organization and people data from LinkedIn and Crunchbase and uses Reifier to match existing in house entities to identify leads.

Case Study - Lead Generation


By consolidating vendor information from different geographies, source systems and channels, a retail operator gets a complete view of its supply chain and it able to garner better deals and discounts from its vendors. Reifier helps in cutting costs for the retailer.

Case Study - Retail Operations


Case Study - TelecomUsing Reifier, telecom companies can detect delinquency patterns by identifying non paying customers who evade detection by enrolling with give similar sounding names and addresses with different formatting and spellings.


Case Study - EcommerceMatching for competitive pricing and catalog enrichment


Accept or create training data with marked duplicates

Identify similarity and indexing rules through Machine Learning

Group near similar records togetherMatch and predict similar records

Reifier Technology


Reifier Architecture


Reifier Workflow

Configure data

Reifier Interactive Learner

Linked Result

Have training data?Reifier Match

Yes

No


Thanks for your time, please feel free to write to [email protected] for more details.

Thank You

mailto:[email protected]

Data & Analytics

Reifier Product Brief