SlideShare une entreprise Scribd logo
1  sur  2
Télécharger pour lire hors ligne
| |JULY 2014
140CIOReview
CIOREVIEW.COMJULY 19, 2016BIG DATA SPECIAL
100 Most Promising Big Data Solution Providers 2016
Company:
Treselle Systems
Description:
Provides Big Data strategy, architecture,
product development, and project
execution services to assist customers
gain strategic business insights by
capturing, supporting, managing, and
seamlessly accessing variety of data
across multiple platforms
Key Person:
Sudharsan Madabusi,
President and CEO
Website:
treselle.com
Treselle Systems
recognized by magazine as
An annual listing of 100 companies that are at the forefront of providing
bigdata solutions and impacting the marketplace
CIOReviewT h e N a v i g a t o r f o r E n t e r p r i s e S o l u t i o n s
‘B
ig Data’ is no more a buzzword. Now that
organizations have already put their wide
arms around Big Data, the next impediment
lies in refining the data to bring out insightful
and meaningful results. With every bit of ‘0’ and ‘1’ being
harnessed as meaningful “collections,” enterprises are sure
to achieve complete utilization of their concrete information,
and attain significant outcomes. Another trend that has
gained notable traction is capitalization of cloud for storing
invaluable sets of data. While majority of enterprises
consider it as a risky venture owing to the concerns of
security, others embark upon it for the sake of business
agility. With myriad of such transformations, enterprises are
confident to embrace innovative ways to hold together the
regulations of corporate world, and ensure their participation
in the realm of Big Data. In order to uphold a fine balance, it
has become critical for the CIOs to choose proper technology
and select best vendors that are at the forefront of effectively
tacking the impediments across the Big Data realm. To
help them accomplish their objective, CIO Review presents
“100 Most Promising Big Data Solution Providers 2016.” A
distinguished panel comprising of CEOs, CIOs, VCs, and
analysts including CIO Review’s editorial board has decided
the top Big Data Solution Providers from over thousand
companies. The companies featured in this list provide a
look into how their products work in the real world, so that
you can gain a comprehensive understanding of the solutions
available and how they stand against competition. We present
to you CIO Review’s 100 Most Promising Big Data Solution
Providers 2016.
| |JULY 2014
141CIOReview| |July 2016
192CIOReview
Treselle Systems
Transforming Data into Business Insights
We enable our clients
to efficiently ingest,
transform, aggregate,
and gain better insights
from variety of
data sources
W
ith the rapid data explo-
sion, today, the complex-
ity of data is changing
from structured to un-
structured—from one-dimensional trans-
actional data flow to multi-dimensional
interaction data flow. Additionally, the
variety of data types that are managed and
analyzed is changing at a rapid rate. In
such a scenario, understanding where big
data can drive competitive advantage and
realizing its value can be challenging for
data managers. Defining how businesses
can and should utilize big data, Treselle
Systems provides big data strategy & ar-
chitecture service that assists businesses
to capture, support, manage, and seam-
lessly access all the data from multiple
data platforms.
The company’s big data strategy,
entity information management, and
governance services generate business
insights from the variety of data with
proper master data management and data
governance strategies. “We enable our
clients to efficiently ingest and aggregate
data from various sources using Hadoop
& Spark ecosystem and other modern
techniques—Talend and Camel for the
ETL, mediation, and routing,” says
Sudharsan Madabusi, President and CEO,
Treselle Systems. Treselle has expertise
in data visualization technologies and can
perform time-series analysis, geo-spatial
analysis, forecasting, classification,
clustering, graph-based visualization and
back-testing analysis. The company also
has extensive experience with multiple
NoSQL databases, Big Data SQL Engine,
Big Data Cloud computing, Statistical &
Quantitative analysis, Text Search & NLP,
and Big Data Quality Assurance.
Treselle’s Big Data R&D team con-
stantly explores technologies that solve
interesting use cases for its clients. For
example, Treselle implemented OrientDB
as a Polyglot persistence mechanism, for
one of their clients, due to its multi-model
capabilities that stores data in document
database but still has relationship between
documents to provide graphing capabili-
ties. Furthermore, Treselle recommended
Apache Drill, a flexible query execution
framework that has self-describing data
exploration behavior across different data
stores to avoid too much data movement
& syncing issues causing staleness across
MongoDB, MySQL, S3, and flat files by
keeping data at source.
Inoneinstance,aclientfromhealthcare
sector, processing more than 4000 data
sources was struggling with ineffective
entity identification, disambiguation,
and linkage, since same information
about healthcare practitioners came in
various formats. The client’s existing data
processing technique was too tedious,
slow and error-prone to processing large
data sets. The client required a system,
which can effectively process their data
and integrate with their data management
platform, identifying and linking the
entities within their massive 40 million
nodes and relationships managed in Neo4j.
Treselle’s Big Data engineering team
utilized various advanced technologies
and integration points to perform data
manipulation, munging, cleansing, and
transformation. The team used Hadoop
ecosystem with Pig and other user defined
functions to do the data transformation
in batch mode, R’s text engineering
capabilities to perform cleansing, entity
identification and linking, and integrated
these backend systems with OpenRefine
GUI with custom GREL macro
expressions to provide excel-like features
on the web for the client’s data science
team. This reduced their data scientist’s
time from days to hours to perform
various data munging capabilities
and enriched the data with client’s
internal APIs.
The average organization today
collects more data than ever before, and
the variety of data types that are stored,
managed, and analyzed has increased
exponentially. Engineering talent with
different data skills is needed to ingest,
transform, aggregate, model, analyze
and create insights. “We help businesses
by providing the talent to build strong
data teams that include data engineers,
modelers, scientists, and BI analysts,”
concludes Madabusi.
Sudharsan Madabusi

Contenu connexe

Tendances

Liberating data with Talend Data Catalog
Liberating data with Talend Data CatalogLiberating data with Talend Data Catalog
Liberating data with Talend Data CatalogJean-Michel Franco
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analyticsThe Marketing Distillery
 
Big agendas for big data analytics projects
Big agendas for big data analytics projectsBig agendas for big data analytics projects
Big agendas for big data analytics projectsThe Marketing Distillery
 
sas_overview_annual_report
sas_overview_annual_reportsas_overview_annual_report
sas_overview_annual_reportKanhu Badtia
 
Business Analytics & Big Data Trends and Predictions 2014 - 2015
Business Analytics & Big Data Trends and Predictions 2014 - 2015Business Analytics & Big Data Trends and Predictions 2014 - 2015
Business Analytics & Big Data Trends and Predictions 2014 - 2015Brad Culbert
 
Unlocking value in your (big) data
Unlocking value in your (big) dataUnlocking value in your (big) data
Unlocking value in your (big) dataOscar Renalias
 
Tangenz big data
Tangenz big dataTangenz big data
Tangenz big dataemmajones88
 
Making Sense of NoSQL and Big Data Amidst High Expectations
Making Sense of NoSQL and Big Data Amidst High ExpectationsMaking Sense of NoSQL and Big Data Amidst High Expectations
Making Sense of NoSQL and Big Data Amidst High ExpectationsRackspace
 
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانی
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانیBusiness Data Alignment-همراستاییِ داده‌ها با اهداف سازمانی
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانیHosseinieh Ershad Public Library
 
Delivering data you can trust with Talend 2019
Delivering data you can trust with Talend 2019 Delivering data you can trust with Talend 2019
Delivering data you can trust with Talend 2019 Jean-Michel Franco
 
The New Enterprise Blueprint featuring the Gartner Magic Quadrant
The New Enterprise Blueprint featuring the Gartner Magic QuadrantThe New Enterprise Blueprint featuring the Gartner Magic Quadrant
The New Enterprise Blueprint featuring the Gartner Magic QuadrantLindaWatson19
 
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...DATAVERSITY
 
Data Catalog as a Business Enabler
Data Catalog as a Business EnablerData Catalog as a Business Enabler
Data Catalog as a Business EnablerSrinivasan Sankar
 

Tendances (14)

Liberating data with Talend Data Catalog
Liberating data with Talend Data CatalogLiberating data with Talend Data Catalog
Liberating data with Talend Data Catalog
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analytics
 
Big agendas for big data analytics projects
Big agendas for big data analytics projectsBig agendas for big data analytics projects
Big agendas for big data analytics projects
 
sas_overview_annual_report
sas_overview_annual_reportsas_overview_annual_report
sas_overview_annual_report
 
Business Analytics & Big Data Trends and Predictions 2014 - 2015
Business Analytics & Big Data Trends and Predictions 2014 - 2015Business Analytics & Big Data Trends and Predictions 2014 - 2015
Business Analytics & Big Data Trends and Predictions 2014 - 2015
 
Unlocking value in your (big) data
Unlocking value in your (big) dataUnlocking value in your (big) data
Unlocking value in your (big) data
 
Tangenz big data
Tangenz big dataTangenz big data
Tangenz big data
 
Making Sense of NoSQL and Big Data Amidst High Expectations
Making Sense of NoSQL and Big Data Amidst High ExpectationsMaking Sense of NoSQL and Big Data Amidst High Expectations
Making Sense of NoSQL and Big Data Amidst High Expectations
 
Big Data SurVey - IOUG - 2013 - 594292
Big Data SurVey - IOUG - 2013 - 594292Big Data SurVey - IOUG - 2013 - 594292
Big Data SurVey - IOUG - 2013 - 594292
 
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانی
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانیBusiness Data Alignment-همراستاییِ داده‌ها با اهداف سازمانی
Business Data Alignment-همراستاییِ داده‌ها با اهداف سازمانی
 
Delivering data you can trust with Talend 2019
Delivering data you can trust with Talend 2019 Delivering data you can trust with Talend 2019
Delivering data you can trust with Talend 2019
 
The New Enterprise Blueprint featuring the Gartner Magic Quadrant
The New Enterprise Blueprint featuring the Gartner Magic QuadrantThe New Enterprise Blueprint featuring the Gartner Magic Quadrant
The New Enterprise Blueprint featuring the Gartner Magic Quadrant
 
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...
 
Data Catalog as a Business Enabler
Data Catalog as a Business EnablerData Catalog as a Business Enabler
Data Catalog as a Business Enabler
 

Similaire à Treselle Systems_CIO article

2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor BriefingsDigital Enterprise Journal
 
Data as a Service (DaaS): The What, Why, How, Who, and When
Data as a Service (DaaS): The What, Why, How, Who, and WhenData as a Service (DaaS): The What, Why, How, Who, and When
Data as a Service (DaaS): The What, Why, How, Who, and WhenRocketSource
 
Keyrus US Information
Keyrus US InformationKeyrus US Information
Keyrus US InformationJulian Tong
 
Big Data Trends and Challenges Report - Whitepaper
Big Data Trends and Challenges Report - WhitepaperBig Data Trends and Challenges Report - Whitepaper
Big Data Trends and Challenges Report - WhitepaperVasu S
 
Idiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics
 
Tips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsTips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsAbhishek Sood
 
TDWI checklist - Evolving to Modern DW
TDWI checklist - Evolving to Modern DWTDWI checklist - Evolving to Modern DW
TDWI checklist - Evolving to Modern DWJeannette Browning
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analyticsThe Marketing Distillery
 
The value of big data
The value of big dataThe value of big data
The value of big dataSeymourSloan
 
Modern Data Challenges require Modern Graph Technology
Modern Data Challenges require Modern Graph TechnologyModern Data Challenges require Modern Graph Technology
Modern Data Challenges require Modern Graph TechnologyNeo4j
 
Data Mining Services in various types
Data Mining Services in various typesData Mining Services in various types
Data Mining Services in various typesloginworks software
 
Are You Prepared For The Future Of Data Technologies?
Are You Prepared For The Future Of Data Technologies?Are You Prepared For The Future Of Data Technologies?
Are You Prepared For The Future Of Data Technologies?Dell World
 
10 top notch big data trends to watch out for in 2017
10 top notch big data trends to watch out for in 201710 top notch big data trends to watch out for in 2017
10 top notch big data trends to watch out for in 2017Ajeet Singh
 
Snowball Group Whitepaper - Spotlight on Big Data
Snowball Group Whitepaper - Spotlight on Big DataSnowball Group Whitepaper - Spotlight on Big Data
Snowball Group Whitepaper - Spotlight on Big DataSnowball Group
 
Accelerating Time to Success for Your Big Data Initiatives
Accelerating Time to Success for Your Big Data InitiativesAccelerating Time to Success for Your Big Data Initiatives
Accelerating Time to Success for Your Big Data Initiatives☁Jake Weaver ☁
 
What Is DataOps? When Agile Meets Data Analytics
What Is DataOps? When Agile Meets Data AnalyticsWhat Is DataOps? When Agile Meets Data Analytics
What Is DataOps? When Agile Meets Data AnalyticsBernard Marr
 

Similaire à Treselle Systems_CIO article (20)

ZEDventures-highres
ZEDventures-highresZEDventures-highres
ZEDventures-highres
 
The 10 best performing big data & business analytics companies july 2017
The 10 best performing big data & business analytics companies july 2017The 10 best performing big data & business analytics companies july 2017
The 10 best performing big data & business analytics companies july 2017
 
2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings2016 Strata Conference New York - Vendor Briefings
2016 Strata Conference New York - Vendor Briefings
 
Data as a Service (DaaS): The What, Why, How, Who, and When
Data as a Service (DaaS): The What, Why, How, Who, and WhenData as a Service (DaaS): The What, Why, How, Who, and When
Data as a Service (DaaS): The What, Why, How, Who, and When
 
Keyrus US Information
Keyrus US InformationKeyrus US Information
Keyrus US Information
 
Keyrus US Information
Keyrus US InformationKeyrus US Information
Keyrus US Information
 
Big Data Trends and Challenges Report - Whitepaper
Big Data Trends and Challenges Report - WhitepaperBig Data Trends and Challenges Report - Whitepaper
Big Data Trends and Challenges Report - Whitepaper
 
Idiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big Data
 
Tips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data AnalyticsTips --Break Down the Barriers to Better Data Analytics
Tips --Break Down the Barriers to Better Data Analytics
 
6 Reasons to Use Data Analytics
6 Reasons to Use Data Analytics6 Reasons to Use Data Analytics
6 Reasons to Use Data Analytics
 
TDWI checklist - Evolving to Modern DW
TDWI checklist - Evolving to Modern DWTDWI checklist - Evolving to Modern DW
TDWI checklist - Evolving to Modern DW
 
Getting down to business on Big Data analytics
Getting down to business on Big Data analyticsGetting down to business on Big Data analytics
Getting down to business on Big Data analytics
 
The value of big data
The value of big dataThe value of big data
The value of big data
 
Modern Data Challenges require Modern Graph Technology
Modern Data Challenges require Modern Graph TechnologyModern Data Challenges require Modern Graph Technology
Modern Data Challenges require Modern Graph Technology
 
Data Mining Services in various types
Data Mining Services in various typesData Mining Services in various types
Data Mining Services in various types
 
Are You Prepared For The Future Of Data Technologies?
Are You Prepared For The Future Of Data Technologies?Are You Prepared For The Future Of Data Technologies?
Are You Prepared For The Future Of Data Technologies?
 
10 top notch big data trends to watch out for in 2017
10 top notch big data trends to watch out for in 201710 top notch big data trends to watch out for in 2017
10 top notch big data trends to watch out for in 2017
 
Snowball Group Whitepaper - Spotlight on Big Data
Snowball Group Whitepaper - Spotlight on Big DataSnowball Group Whitepaper - Spotlight on Big Data
Snowball Group Whitepaper - Spotlight on Big Data
 
Accelerating Time to Success for Your Big Data Initiatives
Accelerating Time to Success for Your Big Data InitiativesAccelerating Time to Success for Your Big Data Initiatives
Accelerating Time to Success for Your Big Data Initiatives
 
What Is DataOps? When Agile Meets Data Analytics
What Is DataOps? When Agile Meets Data AnalyticsWhat Is DataOps? When Agile Meets Data Analytics
What Is DataOps? When Agile Meets Data Analytics
 

Treselle Systems_CIO article

  • 1. | |JULY 2014 140CIOReview CIOREVIEW.COMJULY 19, 2016BIG DATA SPECIAL 100 Most Promising Big Data Solution Providers 2016 Company: Treselle Systems Description: Provides Big Data strategy, architecture, product development, and project execution services to assist customers gain strategic business insights by capturing, supporting, managing, and seamlessly accessing variety of data across multiple platforms Key Person: Sudharsan Madabusi, President and CEO Website: treselle.com Treselle Systems recognized by magazine as An annual listing of 100 companies that are at the forefront of providing bigdata solutions and impacting the marketplace CIOReviewT h e N a v i g a t o r f o r E n t e r p r i s e S o l u t i o n s ‘B ig Data’ is no more a buzzword. Now that organizations have already put their wide arms around Big Data, the next impediment lies in refining the data to bring out insightful and meaningful results. With every bit of ‘0’ and ‘1’ being harnessed as meaningful “collections,” enterprises are sure to achieve complete utilization of their concrete information, and attain significant outcomes. Another trend that has gained notable traction is capitalization of cloud for storing invaluable sets of data. While majority of enterprises consider it as a risky venture owing to the concerns of security, others embark upon it for the sake of business agility. With myriad of such transformations, enterprises are confident to embrace innovative ways to hold together the regulations of corporate world, and ensure their participation in the realm of Big Data. In order to uphold a fine balance, it has become critical for the CIOs to choose proper technology and select best vendors that are at the forefront of effectively tacking the impediments across the Big Data realm. To help them accomplish their objective, CIO Review presents “100 Most Promising Big Data Solution Providers 2016.” A distinguished panel comprising of CEOs, CIOs, VCs, and analysts including CIO Review’s editorial board has decided the top Big Data Solution Providers from over thousand companies. The companies featured in this list provide a look into how their products work in the real world, so that you can gain a comprehensive understanding of the solutions available and how they stand against competition. We present to you CIO Review’s 100 Most Promising Big Data Solution Providers 2016.
  • 2. | |JULY 2014 141CIOReview| |July 2016 192CIOReview Treselle Systems Transforming Data into Business Insights We enable our clients to efficiently ingest, transform, aggregate, and gain better insights from variety of data sources W ith the rapid data explo- sion, today, the complex- ity of data is changing from structured to un- structured—from one-dimensional trans- actional data flow to multi-dimensional interaction data flow. Additionally, the variety of data types that are managed and analyzed is changing at a rapid rate. In such a scenario, understanding where big data can drive competitive advantage and realizing its value can be challenging for data managers. Defining how businesses can and should utilize big data, Treselle Systems provides big data strategy & ar- chitecture service that assists businesses to capture, support, manage, and seam- lessly access all the data from multiple data platforms. The company’s big data strategy, entity information management, and governance services generate business insights from the variety of data with proper master data management and data governance strategies. “We enable our clients to efficiently ingest and aggregate data from various sources using Hadoop & Spark ecosystem and other modern techniques—Talend and Camel for the ETL, mediation, and routing,” says Sudharsan Madabusi, President and CEO, Treselle Systems. Treselle has expertise in data visualization technologies and can perform time-series analysis, geo-spatial analysis, forecasting, classification, clustering, graph-based visualization and back-testing analysis. The company also has extensive experience with multiple NoSQL databases, Big Data SQL Engine, Big Data Cloud computing, Statistical & Quantitative analysis, Text Search & NLP, and Big Data Quality Assurance. Treselle’s Big Data R&D team con- stantly explores technologies that solve interesting use cases for its clients. For example, Treselle implemented OrientDB as a Polyglot persistence mechanism, for one of their clients, due to its multi-model capabilities that stores data in document database but still has relationship between documents to provide graphing capabili- ties. Furthermore, Treselle recommended Apache Drill, a flexible query execution framework that has self-describing data exploration behavior across different data stores to avoid too much data movement & syncing issues causing staleness across MongoDB, MySQL, S3, and flat files by keeping data at source. Inoneinstance,aclientfromhealthcare sector, processing more than 4000 data sources was struggling with ineffective entity identification, disambiguation, and linkage, since same information about healthcare practitioners came in various formats. The client’s existing data processing technique was too tedious, slow and error-prone to processing large data sets. The client required a system, which can effectively process their data and integrate with their data management platform, identifying and linking the entities within their massive 40 million nodes and relationships managed in Neo4j. Treselle’s Big Data engineering team utilized various advanced technologies and integration points to perform data manipulation, munging, cleansing, and transformation. The team used Hadoop ecosystem with Pig and other user defined functions to do the data transformation in batch mode, R’s text engineering capabilities to perform cleansing, entity identification and linking, and integrated these backend systems with OpenRefine GUI with custom GREL macro expressions to provide excel-like features on the web for the client’s data science team. This reduced their data scientist’s time from days to hours to perform various data munging capabilities and enriched the data with client’s internal APIs. The average organization today collects more data than ever before, and the variety of data types that are stored, managed, and analyzed has increased exponentially. Engineering talent with different data skills is needed to ingest, transform, aggregate, model, analyze and create insights. “We help businesses by providing the talent to build strong data teams that include data engineers, modelers, scientists, and BI analysts,” concludes Madabusi. Sudharsan Madabusi