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144188195215245280

Treselle Systems Private Limited

Chennai, Tamil Nadu

| GST  33AACCT0645H1ZN

| Verified Supplier

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Treselle Systems Private Limited - Service Provider of data lake architecture, big data strategy and roadmap & big data testing in Chennai, Tamil Nadu.

Data Lake Architecture
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Data Lake Architecture

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Hortonworks: HDP (Hortonworks Data Platform) is entirely based on open source projects managed by Ambari that provides an entire Hadoop ecosystem and provide controls to choose necessary components in the ecosystem based on the business needs. It is possible to set up a pure batch or streaming or hybrid mode that enables business to set up required Data Lake architecture

        Cloudera: Another well known Hadoop distribution built on slightly different stack unlike HDP and enables businesses to set up required Data Lake architecture. It has proprietary products such as Cloudera Manager Enterprise for infrastructure management that had advanced functionalities compared to Ambari and Cloudera Navigator for Data Governance capabilities

         AWS: A Data Lake architecture can be entirely built on cloud by using  AWS managed services such as API Gateway, Lambda, Elastic Map Reduce (EMR), Spark, Kinesis, DynamoDB, S3, ElasticSearch, etc. Those businesses who are already using AWS services and don’t require lot of control over the infrastructure can choose AWS

        Custom Infrastructure: Not all Big Data needs require Hadoop ecosystem and many business use cases can be achieved using custom infrastructure such as Standalone Spark clusters that satisfies most of the big data needs such as batch, streaming, machine learning, graph process and programming interfaces with Python and R. SparkSQL is capable of connecting to variety of data stores that are in RDBMS, NoSQL, S3, etc. Apache Drill is another interesting technology that can infer schema on the fly and enables to perform joins across multiple data stores such as HDFS, S3, RDBMS, NoSQL, etc

Infrastructure management & migration: Treselle can help businesses to manage their existing Big Data infrastructure as well as migrate to the most suitable infrastructure based on their busin

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Big Data Strategy And Roadmap
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Visualizing large data is challenging. Along with increase in volume, there are new kinds of datasets which are becoming more and more mainstream. The need to analyze user comments, sentiments, customer calls and various unstructured data has resulted in the use of new kinds of visualizations. The use of graph databases, streaming data, geo-map, and machine learning models are some of the examples of how things are changing because of velocity and variety.

Treselle has helped clients with big data visualization needs ranging from custom built solutions and open source notebooks to well know commercial visualization products that are targeted to different user groups such as Business Analyst, Data Science team, Curators, and others 

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    • Commercial Products: Tableau & Qlik Sense are some of the most popular visualization vendors that can integrate with Hadoop ecosystem using Hive or Spark connectors and databases via JDBC/ODBC capable drivers. Apache Drill can be used to perform cross join queries across multiple SQL & NoSQL databases and connect with Tableau using JDBC driver to create interesting visualizations at scale while data is located in the original sources
Open Source Visualizations: The visualization needs for Data Science teams and Curators are quite different as they are mostly responsible for performing exploratory analysis on large scale of unrefined data to find insights and patterns. These visualizations are not based on pre-materialized views and had to run on clusters when an analysis is performed. Visualization tools such as Zeppelin,

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Big Data Testing
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Big Data Testing

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  • rontend test: Selenium web driver, PhantomJS, Nightwatch.js, Handlebars, Angular performance inspector, Audit, Network & timeline test, Webpage Test, Google PSI, Sauce Labs, Jasmine, Protractor, Karma, Navigation & routing test, Controller test, Directives test, Events dispatch test, Filters test
  • Rest API test: SOAPUI, Selenium, Gatling, Apache Benchmark test, JSON payload test, Supertest, Mocha, Should, Chai
  • Database test: Metabase, Zeppelin, Jupyter, SQL query, Python & shell scripts
  • TMS: Zephyr, TestLink

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Legacy Application Modernization
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AWS Cloud Migration Service
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Businesses are increasingly moving to cloud based services for computing, elasticity, cheap storage, better security and access controls, and other managed services to save cost, achieve scalability, and prepare for capacity growth plan. Treselle has helped businesses in migrating on-premise and private data center applications to AWS cloud services based on business needs

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AWS Cloud Application Development Service
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Treselle has experience building different types of applications on cloud such as complete SaaS product, batch data processing, long running process, streaming data, data storage persistence using different AWS storage services, event and notification execution model, etc

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AWS Cloud Infrastructure Management Service
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Treselle has helped clients in managing their AWS cloud infrastructure with continuous cost saving plans by using reserved or spot instead of on-demand instances, migrate old and degraded instances to new instances, monitor health of different services using cloudwatch, manage security across different AWS services using IAM & security groups, prepare roadmap plan based on business requirements, automation

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SQL Database Service On Cloud Service
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Many businesses have moved to cloud based AWS RDS database systems running on MySQL, Oracle, Postgres, and Aurora providing same on-premise capabilities minus administration tasks related to upgrades, patching, backups, etc. Treselle has helped clients implementing SQL database solutions on AWS that includes data modeling for master and transaction data, schema evolution, implementing complex statistical computations on stored procedures, etc.

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Big Data Engineering
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Big Data Engineering

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Big Data Engineering is a specialized field that helps businesses to ingest, store, transform, perform analytics, run machine learning models, identify patterns and insights, manage security and governance and prepare the data for visualization purpose. Treselle has helped clients in building different big data engineering solutions based on the proposed architecture with a wide variety of tools and technologies. Treselle can help businesses either in complete Big Data Engineering implementation or any part/layer of the stack as below: 

  1. Ingestion – batch or streaming
  2. Data Storage – SQL, NoSQL, Cloud storage
  3. Data Processing – wrangling, cleansing, normalizing, filtering, transformations, ETL
  4. Analytics – aggregation, correlation, statistical computation, machine learning models
  5. Operations – manage & monitor clusters, data governance, data security, information lifecycle management, Metadata – business, technical, and operation

Treselle has experience in implementing variety of Big Data implementation from non-distributed to distributed computing system and commercial products.

Non-distributed Computing Systems: Businesses that have a lot of varieties but not volume or velocity doesn’t need complicated distributed computing systems such as Hadoop or Spark. There are different tools and technologies that can be used to create loosely coupled and highly cohesive data processing pipeline based on open source technologies such as Camel, Talend, Nutch, Java/Python

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Data Science

Data Science

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About Us

Treselle Systems Private Limited - Service Provider of data lake architecture, big data strategy and roadmap & big data testing in Chennai, Tamil Nadu.

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Nature of Business

Service Provider

Legal Status of Firm

Private Limited Company

GST Number

33AACCT0645H1ZN

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Treselle Systems Private LimitedNew No.7/Old No.4, 4th Avenue Dr.Ambedkar Road, Dr.Ambedkar Road, Kodambakkam,
Chennai-600024, Tamil Nadu, India

Sathyaraj (Sr. Application Software Engineer)

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