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Big Data & Analytics Stack
Stream
AATLAccredited
Benefits
eservices@emudhra.com
One of the world’s largest digital mar-
keting agency uses emStream for
sentiment monitoring across 25 retail
brands
Large public sector bank uses
emStream for risk monitoring across
corporate borrowers
Stream
A sophisticated stack designed to cater
to your unified data analytics
requirements
Abundant data sources, easy set-up,
distributed processing, advanced
NLP, Predictive Analytics and more...
Interactions today are becoming increasingly
multi-channel and real-time in a speed that is
difficult, yet important to keep up with. Consequent-
ly, so are the risks associated with inadequate brand
management that are not on par with today’s market
demands.
Interestingly, we have noticed that this pattern does
not simply apply to brand management but also
applies in general to various elements of risk and
fraud across Banking and other industries. Globaliza-
tion and selective disclosure that facilitate consumer
level fraud have wreaked havoc on many financial
institutions.
Built upon a Big Data Layer, emStream is eMudhra’s
Analytics stack which can be used to address
bespoke requirements in Sentiment, Fraud, and Risk
analytics.
Run data pipelines and ETL
emStream can significantly optimize the data pipeline
setup and maintenance, and enable operational
reporting in real-time. In addition, enterprises can
build a maintainable replication mechanism for
enabling deeper analytics later, and also have both
transactional and analytical data available to further
scale up and out.
Distributed computing using Apache Spark
With support for data ingestion across a range of data
sources, emStream’s core engine runs on an advanced,
in-memory Apache Spark computing engine that delivers
100x the performance of Apache Hadoop for your
workloads. This enables it to seamlessly run Natural
Language Processing and Predictive Analytics tasks on
unstructured, semi-structured and structured data, and
deliver business intelligence with lightning speed.
Run Machine Learning with no coding
emStream allows businesses to run Machine Learning
models by choosing the appropriate algorithms without
writing a single line of code. Companies can also carry
out data preparation and feature engineering at ease
just by configuring a set of rules.
Leverages open source with significantly
lower TCO
Quick deployment on-prem or on cloud
Uses latest technologies in NLP and ML
Ability to support with data scientists,
ML programmers for building use cases
Customer Success Stories
NLP built on deep learning frameworks
Over a decade of work has gone into our NLP engine
which is fully proprietary. A combination of domain
ontology on top of data helps us establish sentiment
to specific attributes with high accuracy. Apart from a
plethora of features that our NLP enables us to
provide, we even offer contextual NLP where we
expand graph theory to resolve entities against
known databases.
Our NLP driven analytics engine can be used for:Powerful data aggregation
emStream has ready feeds from popular social
media platforms. However, it is capable of data
ingestion from excel, email servers, SMS servers,
websites, blogs, RSS feeds, video/image input, and
even relational databases within your organization.
You define what you want, and emStream gets the
data (keeping in mind data privacy regulations of
course!).
• Sentiment, Problem & Intent Analysis
• Topic Identification
• Theme Extraction
• Auto Summarization of Text
• Verb Argument Extraction
• Extraction of Events
eservices@emudhra.com
Technical Details
Service Issues
Customer Loyalty
Lifetime value
Room
Restaurant
Brand Affinity
Demographics
Discounts
Redefined
Loyalty Scores
Superior
Customer
Intelligence
Product
Recommendations
eMails
Structured
Data
“I love restaurant Food but found dirty floors”
“I called Customer Support but no one answered”
Representative Attitude
Product Planning
Strong Customer
Insights
Brand
Intelligence
Marketing Strategy
emSTREAM
Uses Apache Spark's ETL capabilities
for analyzing
Stream
Database Layer
Distributed In-memory Analytics
• mongoDB
• elastic
• Classification
• Clustering
• Association
• Predictive Analysis
• Anomaly Detection
Sample flow - Predictive Analytics for Customer Churn
Use Cases
Government
Media Monitoring across multiple sources of
news and media focusing on risk analytics,
sentiment analytics, and influencer analysis
Financial Services
• Fraud analytics aimed at loan fraud mitigation
• Consumer analytics focused on credit card churn
• Omnichannel customer support analytics
• Behavioral analytics
Manufacturing
• Risk management
• Fault prediction and preventive maintenance
• Demand forecasting and inventory analysis
Healthcare
• Creating risk scores for diabetes, cancer, etc.
• Sending real-time alert about patient condition
eCommerce
• Individual targeted offers for retail/eCommerce
companies
• Brand monitoring
• Chat/email analytics
IoT Analytics
• Consumer product usage analysis
• Video analytics for surveillance and safety
• Predictive maintenance and reliability analysis
• Anomaly detection & diagnosis
• Named Entities
• Sentiments
• Topics
Data Aggregators
• Local Data Adapter for Structured and Semi-structured
• Social Adapters for Social Media Data Sources
• Forums Adapter and URL Crawler for Unstructured
Data Sources
Semi Structured – CSV, JSON, XML, HDFS, Excel
Structured – Databases like Oracle, MySQL, etc
TW, FB, LinkedIn, Youtube, Instagram
Blogs, Boards, News
Data Sources
US
Much like the name, which is an embodiment of the seal of
authenticity in the electronic or digital world, eMudhra is a cyber
security solutions company and a trust service provider that is
focused on accelerating the world’s transition to a secure integrated
digital society. With presence in 5 continents and a global delivery
center in Bengaluru, India, eMudhra is empowering secure digital
transformation of over 45 global banks, several Fortune 100
customers and thousands of SMEs.
About eMudhra:
© eMudhra. All Rights Reserved.eservices@emudhra.com

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eMStream

  • 1. Big Data & Analytics Stack Stream AATLAccredited
  • 2. Benefits eservices@emudhra.com One of the world’s largest digital mar- keting agency uses emStream for sentiment monitoring across 25 retail brands Large public sector bank uses emStream for risk monitoring across corporate borrowers Stream A sophisticated stack designed to cater to your unified data analytics requirements Abundant data sources, easy set-up, distributed processing, advanced NLP, Predictive Analytics and more... Interactions today are becoming increasingly multi-channel and real-time in a speed that is difficult, yet important to keep up with. Consequent- ly, so are the risks associated with inadequate brand management that are not on par with today’s market demands. Interestingly, we have noticed that this pattern does not simply apply to brand management but also applies in general to various elements of risk and fraud across Banking and other industries. Globaliza- tion and selective disclosure that facilitate consumer level fraud have wreaked havoc on many financial institutions. Built upon a Big Data Layer, emStream is eMudhra’s Analytics stack which can be used to address bespoke requirements in Sentiment, Fraud, and Risk analytics. Run data pipelines and ETL emStream can significantly optimize the data pipeline setup and maintenance, and enable operational reporting in real-time. In addition, enterprises can build a maintainable replication mechanism for enabling deeper analytics later, and also have both transactional and analytical data available to further scale up and out. Distributed computing using Apache Spark With support for data ingestion across a range of data sources, emStream’s core engine runs on an advanced, in-memory Apache Spark computing engine that delivers 100x the performance of Apache Hadoop for your workloads. This enables it to seamlessly run Natural Language Processing and Predictive Analytics tasks on unstructured, semi-structured and structured data, and deliver business intelligence with lightning speed. Run Machine Learning with no coding emStream allows businesses to run Machine Learning models by choosing the appropriate algorithms without writing a single line of code. Companies can also carry out data preparation and feature engineering at ease just by configuring a set of rules. Leverages open source with significantly lower TCO Quick deployment on-prem or on cloud Uses latest technologies in NLP and ML Ability to support with data scientists, ML programmers for building use cases Customer Success Stories NLP built on deep learning frameworks Over a decade of work has gone into our NLP engine which is fully proprietary. A combination of domain ontology on top of data helps us establish sentiment to specific attributes with high accuracy. Apart from a plethora of features that our NLP enables us to provide, we even offer contextual NLP where we expand graph theory to resolve entities against known databases. Our NLP driven analytics engine can be used for:Powerful data aggregation emStream has ready feeds from popular social media platforms. However, it is capable of data ingestion from excel, email servers, SMS servers, websites, blogs, RSS feeds, video/image input, and even relational databases within your organization. You define what you want, and emStream gets the data (keeping in mind data privacy regulations of course!). • Sentiment, Problem & Intent Analysis • Topic Identification • Theme Extraction • Auto Summarization of Text • Verb Argument Extraction • Extraction of Events
  • 3. eservices@emudhra.com Technical Details Service Issues Customer Loyalty Lifetime value Room Restaurant Brand Affinity Demographics Discounts Redefined Loyalty Scores Superior Customer Intelligence Product Recommendations eMails Structured Data “I love restaurant Food but found dirty floors” “I called Customer Support but no one answered” Representative Attitude Product Planning Strong Customer Insights Brand Intelligence Marketing Strategy emSTREAM Uses Apache Spark's ETL capabilities for analyzing Stream Database Layer Distributed In-memory Analytics • mongoDB • elastic • Classification • Clustering • Association • Predictive Analysis • Anomaly Detection Sample flow - Predictive Analytics for Customer Churn Use Cases Government Media Monitoring across multiple sources of news and media focusing on risk analytics, sentiment analytics, and influencer analysis Financial Services • Fraud analytics aimed at loan fraud mitigation • Consumer analytics focused on credit card churn • Omnichannel customer support analytics • Behavioral analytics Manufacturing • Risk management • Fault prediction and preventive maintenance • Demand forecasting and inventory analysis Healthcare • Creating risk scores for diabetes, cancer, etc. • Sending real-time alert about patient condition eCommerce • Individual targeted offers for retail/eCommerce companies • Brand monitoring • Chat/email analytics IoT Analytics • Consumer product usage analysis • Video analytics for surveillance and safety • Predictive maintenance and reliability analysis • Anomaly detection & diagnosis • Named Entities • Sentiments • Topics Data Aggregators • Local Data Adapter for Structured and Semi-structured • Social Adapters for Social Media Data Sources • Forums Adapter and URL Crawler for Unstructured Data Sources Semi Structured – CSV, JSON, XML, HDFS, Excel Structured – Databases like Oracle, MySQL, etc TW, FB, LinkedIn, Youtube, Instagram Blogs, Boards, News Data Sources
  • 4. US Much like the name, which is an embodiment of the seal of authenticity in the electronic or digital world, eMudhra is a cyber security solutions company and a trust service provider that is focused on accelerating the world’s transition to a secure integrated digital society. With presence in 5 continents and a global delivery center in Bengaluru, India, eMudhra is empowering secure digital transformation of over 45 global banks, several Fortune 100 customers and thousands of SMEs. About eMudhra: © eMudhra. All Rights Reserved.eservices@emudhra.com