Cases - NucleusTeq

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Travel and HospitalitySentiment Analysis of preferred customers for major US airline

The Challenge

Identify the sentiment & Change the way customers perceive the airline, both in domestic and international sectors.
Sentiments captured from Facebook, Twitter, Email Support, Call Center Support, Website, Travel Booking sites, etc.
Connect all together to derive relevance w.r.t. passenger, travel dates, times, sectors, planes, staff etc.

NucleusTeq Solution

Performed aspect-based sentiment analysis and identified potential areas of improvement
Worked on linkage with other datasets to identify the root causes of the problem and suggest system improvement changes
Provide high level recommendations based on past actions taken

Benefits Realized

More than 80% accuracy in identifying the relevant sentiments that impacted the customer’s satisfaction.
Effectively provide recommendations to provide recommended action for specific cases.

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Energy and UtilitiesDigital Transformation for one of the largest oil and Gas company in the world.

About the customer – Customer is one of the largest Oil & Gas company in the world

The Challenge

Fragmented functions lead to significant delays and less than optimal recommendations
The company did not have a unified digital strategy leading to significant delay in execution
Insights were not leading to effective actions

NucleusTeq Solution

Defined & Implemented Azure based cloud platform strategy leveraging Industry Gen 4 reference Architecture
Implemented 10+ Insights that would lead to smart decisions such as operations optimization, Real-time Monitoring etc.
IoT streaming & real-time analytics for predictive failures

Benefits Realized

15% more yield through advanced Machine Learning recommendations
10% faster time to market while leveraging the cloud based digital platform.
12-15% reduction in failures & incidents through predictive monitoring

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Communication Media & TechnologyRealtime anomaly detection & network monitoring for major telecommunications company in USA.

About the customer – Customer is one of the major telecommunications companies in USA

The Challenge

Detect router issues, tower failure & call drops in real-time
Identify and route the traffic to another (working) infrastructure.
Improve customer experience
Feedback loop to customer and link it with marketing

NucleusTeq Solution

NucleusTeq created an end-to-end pipeline where the network data is ingested, transformed and dynamically analyzed via Machine Learning Algorithms to identify anomalies and sent to appropriate channel for further action
Real-time routing and monitoring of the network.

Benefits Realized

Unsupervised algorithm dynamically updates itself and identifies anomalies. Thus, it always considers the latest dynamics of the environment
Real-time monitoring & optimization of the infrastructure
Enhanced customer experience

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Thought LeadershipEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

Customer Challenge

Teradata was the only platform that was catering to the enterprise reporting, This added to significant annual costs for the customer
Data was in silos and each BU had its own process to exchange data with other Bus, This added significant delays in developing products that required enterprise-level data.
Lack of self-service of the enterprise data leading to higher time to market, costs & redundancies.

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Maximize application/data Reusability & Globalization

Outcomes Delivered

Comprehensive Metadata Management, Security Data Quality & Governance
Single source of truth
Data integrity & quality with financial B&C
Eliminated redundancy by 47%
Reduced Attribute SORs by 72%
4 Petabyte data migrated
18 Months total delivery time
35+ M in operations savings per year

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Thought LeadershipEnd-to-End Data Lake Setup & Migration of Netezza reporting platform to Azure for a Major retailer

Customer Challenge

Lack of centralization, standardization and self-service of the enterprise data leading to higher time to market, costs & redundancies
Point to Point Integrations leading to significant cost, lack of governance, data quality & missing single version of “truth”.

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Maximize application/data Reusability & Globalization

Outcomes Delivered

Data Lake on Azure
Comprehensive Metadata Management, Security & Governance
Self Service Data Management Portal
Single source of truth
Data integrity & quality with financial B&C
Eliminated redundancy by 40%
Reduced IT Infra Cost by 52%
Reduced project cost by 45%
Expedited project delivery by 20% by leveraging Offshore
16 SORs
100 TB Data migrated
Customer & Services BUs
3+ M in operations savings
per year
50% more customer retention & repeat business expected
12-15% increase in Offers based sales

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Life Science and HealthcareReal-time insights and recommendation engine for one of the largest pharmaceuticals company in the world

About the customer – One of the largest manufactures & distributors of prescription pharmaceuticals in several therapeutic areas, including cancer, HIV/AIDS, cardiovascular disease, diabetes, hepatitis, rheumatoid arthritis and psychiatric disorders.

Customer Challenge

An unmanaged on-prem data lake running the risk of becoming a data swamp, needed to be optimized & migrated to cloud
Unusable insights & recommendations for the enterprise users
Unable to efficiently utilize the provisioned cluster
Enable An organized data lake supported by a curated semantic layer reducing redundancy and confusion.
Breakdown silos and enable a consolidated reporting platform powered by Hadoop

NucleusTeq Solution

Partnered with the customers stakeholders across IT and business to develop a comprehensive roadmap and strategy to optimize and migrate to the cloud
Defined a multi-year phased cloud migration plan for success and execution
Enabled and trained internal teams to get cloud and big data-enabled at the end-user level
Put in execution an initiative migrating EDW workloads to Hadoop on cloud
Put in execution optimization, data harmonization and migration to the cloud
Converged siloed analytics into a uniform converged platform expanding access for easy discovery and multi-faceted analysis.

Outcomes Delivered

Business users are able to perform wider analysis across multiple channels unhindered by silos
A flexible and elastic data platform in the cloud capable of catering to the diverse and dynamic needs of the enterprise for a significantly smaller budget footprint
Cost savings and effort reduction enabled by dynamic AWS native apps
One stop metrics repository for senior management review and chargebacks

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InsuranceCreate new liability insurance models based on IOT sensor data for a leading business Insurer.

About the customer – Customer is one of the top 3 B2B broker in the world

Customer Challenge

Create a unified risk-based model for real-time underwriting & presentment of Insurance to a Business customer
Lack of centralization, standardization and self-service of the enterprise data leading to higher time to market, costs & redundancies
Point to Point Integrations leading to significant cost, lack of governance, data quality & missing single version of “truth”.

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Created a data model that accounted for various parameters such as IOT sensor data of the field worker, probability of injury, pattern analysis etc.

Outcomes Delivered

Data Lake on Azure for unified data management & single source of truth
Data integrity & quality with financial B&C
Real-time (100 TPS) system for Insurance underwriting & premium processing
Eliminated system redundancy by 40%

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Banking and Financial ServicesEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

About the customer – Customer is one of the top 3 largest credit card & payments companies in the world.

Customer Challenge

Teradata was the only platform that was catering to the enterprise reporting, This added to significant annual costs for the customer
Data was in silos and each BU had their own process to exchange data with other Bus, This added significant delays in developing products that required enterprise level data.
Lack of self-service of the enterprise data leading to higher time to market, costs & redundancies.

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Maximize application/data Reusability & Globalization

Outcomes Delivered

Comprehensive Metadata Management, Security Data Quality & Governance
Single source of truth
Data integrity & quality with financial B&C
Eliminated redundancy by 47%
Reduced Attribute SORs by 72%
8 Petabyte data migrated
18 Months total delivery time
35+ M in operations savings per year

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Banking and Financial ServicesDetection of Intent to Fraud using NLP for one of world’s largest banks

About the customer – Customer is one of the top 10 largest banks in the world.

Customer Challenge

Bank lost billions of dollars in penalties and trading losses
Challenge posed was to detect the intent to commit fraud proactively by monitoring communications in order to avoid penalties and damage to reputation
Large team of ~30 people were dedicated to ensure compliance using keyword search but face too many false positives

NucleusTeq Solution Approach

Delivered a semi-supervised learning-based NLP solution to aid in detecting fraudulent activity
Coordinated multiple rounds of reviews to improve solution accuracy across 10 categories
Attained expected precision in SLA within 2 months
Implemented solution on Stanford NLP, Spark and Tachyon

Outcomes Delivered

Delivered expected accuracy to detect email messages with scores for fraud categories
Elimination of a large part of the data via identification of non-relevant messages using learning algorithms
Defined templates unique to each type of fraud based on presence of different entities (persons, places etc)
Created an approach to profile all the users in the data by means of graph analytics algorithms

Enterprise AutomationAutomation of Insurance – Sales, Underwriting & Services process for Leading Insurance company with $135 B in assets

Customer Challenge

Mandate to Increase revenues & customer retention
Reduce customer support costs
Mandate to Improve customer experience

NucleusTeq Solution Approach

Use Cases fully automated:

Billing Inquiry Analysis
Insurance Quote Lookup
Knowledge Push
Automated Documentation
Agent Groups: Customer Service, Sales, Underwriting, Processing

Outcomes Delivered

72% Manual Effort Automated
6 million in annual savings
2 weeks CSR training time reduction
20% AHT reduction
6 months implementation

Enterprise AutomationBack Office RPA Solution for American Multinational investment

Back Office RPA Solution for American Multinational investment bank and financial services company, also Big 4 Bank with around 10.73% of American bank deposits

Customer Challenge

Higher waiting time for Mortgage Processing
Mandate to reduce errors and paper work in the process
Highly manual process, with redundant and repetitive steps
Mandate to Improve Customer Satisfaction Rating

NucleusTeq Solution Approach

Through RPA, the manual & repetitive entries in application processing were automated
The paper work was digitized through OCR, easier online application & verification, faster underwriting and escalation processing; and reduced process time to a competitive 1 minute from 2 hours approvals
Process Transformation through Digitization and Process Improvement efforts led to reduced errors

Outcomes Delivered

AHT improved by a record 35%
Errors reduced to 0.005%
Increased loan origination revenue by $12 Million
AHT reductions and over 25% increased online applications in 2018
Strongest consumer score in the bank’s history

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Cloud ServicesBig-Data Lake setup on Azure Cloud for top 3 Pet Retailers in the world

About the customer – Customer is one of the top 3 pet retailers in the world

Customer Challenge

Lack of centralization, standardization and self-service of the enterprise data leading to higher time to market, costs & redundancies
Projects based development as opposed to “Platform / Products” thinking leading to significant cost & redundancy.

NucleusTeq Solution Approach

Defined & Created core platform components on the Azure environment to support Scheduling, Ingestion, Metadata Management, Data quality etc.
Created end-to-end monitoring & operations management platform to ensure optimal use of the platform
Created Continuous Integration, Continuous Deployment, Automated testing capabilities for all federated applications. Extensive use of enterprise Jenkins.
Created data consumption layer through microservices architecture using Azure Kubernetes Services.

Outcomes Delivered

Unified single version of truth data lake for the enterprise
5X faster time to market for new reports & data capabilities
40% reduction in operating expenses through cloud adoption & management.

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Cloud ServicesModernization of Enterprise reporting (Netezza) to AWS for a major housing finance company

About the customer – Customer is one of the top federal housing finance company

Customer Challenge

Enterprise Data Warehouse (EDW) on Netezza to be migrated to AWS Cloud.
Design and deliver a comprehensive solution implementing best practice recommendations in line with the enterprise data lake goals.
Replicate the current Netezza snapshotting process in the EDW environment into the AWS environment
Provide best practice recommendations in the areas of metadata capture, lineage & audit

NucleusTeq Solution Approach

Migrated the snapshotting process from Netezza to AWS based environment
Migrated base tables in 3NF from IDS (Integrated Data Store) to S3 and update them on an ongoing basis with incremental updates
Implemented identified data migration patterns in a way that it can be reused for tables conforming to similar patterns
Identified and migrated major percentage of the EDW users and their associated queries that qualify as long-running workloads to S3
Comprehensive architecture on AWS addressing the enterprise data lake goals with best practice recommendations in the areas of metadata capture, lineage, storage & audit

Outcomes Delivered

Offload of the major percentage of Netezza based EDW (data and workloads) to AWS based environment
Free the EDW from snapshotting process by migrating the process to AWS
Use of cloud offering elasticity to the process for future scaling

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Big Data Advisory and EngineeringEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

Customer Challenge

Teradata was the only platform that was catering to the enterprise reporting, This added to significant annual costs for the customer
Data was in silos and each BU had their own process to exchange data with other Bus, This added significant delays in developing products that required enterprise-level data.
Lack of self-service of the enterprise data leading to higher time to market, costs & redundancies.

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Maximize application/data Reusability & Globalization

Solution Architecture

Outcomes Delivered

Comprehensive Metadata Management, Security Data Quality & Governance
Single source of truth
Data integrity & quality with financial B&C
Eliminated redundancy by 47%
Reduced Attribute SORs by 72%
8 Petabyte data migrated
18 Months total delivery time
35+ M in operations savings per year

Big Data Advisory and EngineeringEnd-to-End Data Lake Setup & Migration of Netezza reporting platform to Azure for a Major retailer

Customer Challenge

Lack of centralization, standardization and self-service of the enterprise data leading to higher time to market, costs & redundancies
Point to Point Integrations leading to significant cost, lack of governance, data quality & missing single version of “truth”

NucleusTeq Solution Approach

Centralized, Standardized & Certified Data for Consistency
Democratize Data through self-service API’s while eliminating redundancy
Ensuring compliance to Enterprise data security guidelines
Maximize application/data Reusability & Globalization

Solution Architecture

Outcomes Delivered

Data Lake on Azure
Comprehensive Metadata Management , Security & Governance
Self Service Data Management Portal
Single source of truth
Data integrity & quality with financial B&C
Eliminated redundancy by 40%
Reduced IT Infra Cost by 52%
Reduced project cost by 45%
Expedited project delivery by 20% by leveraging Offshore
16 SORs
100 TB Data migrated
Customer & Services BUs
3+ M in operations savings per year
50% more customer retention & repeat business expected
12-15% increase in Offers based sales

Older Posts

SUCCESS STORIES

Travel and HospitalitySentiment Analysis of preferred customers for major US airline

Energy and UtilitiesDigital Transformation for one of the largest oil and Gas company in the world.

Communication Media & TechnologyRealtime anomaly detection & network monitoring for major telecommunications company in USA.

Thought LeadershipEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

Thought LeadershipEnd-to-End Data Lake Setup & Migration of Netezza reporting platform to Azure for a Major retailer

Life Science and HealthcareReal-time insights and recommendation engine for one of the largest pharmaceuticals company in the world

InsuranceCreate new liability insurance models based on IOT sensor data for a leading business Insurer.

Banking and Financial ServicesEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

Banking and Financial ServicesDetection of Intent to Fraud using NLP for one of world’s largest banks

Enterprise AutomationAutomation of Insurance – Sales, Underwriting & Services process for Leading Insurance company with $135 B in assets

Enterprise AutomationBack Office RPA Solution for American Multinational investment

Cloud ServicesBig-Data Lake setup on Azure Cloud for top 3 Pet Retailers in the world

Cloud ServicesModernization of Enterprise reporting (Netezza) to AWS for a major housing finance company

Big Data Advisory and EngineeringEnterprise Data modernization of one of world’s largest credit card company from Teradata to On-Premise Big-Data Lake

Big Data Advisory and EngineeringEnd-to-End Data Lake Setup & Migration of Netezza reporting platform to Azure for a Major retailer

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