MANOJ
•Download as DOCX, PDF•
0 likes•213 views
J.Manoj Prabhakar is seeking a position that allows him to utilize his 2 years of experience with ETL methodologies using Informatica. He has strong skills in data extraction, transformation, and loading from various sources into data warehouses. His experience includes projects migrating data from legacy systems to new platforms for clients in insurance and banking. He is proficient with SQL and databases and has worked extensively on testing software functionality.
Report
Share
Report
Share
Recommended
Database ResumeLinkedIn
Patrick A. Seery has over 3 years of experience programming DB2 and Oracle databases. He has a BS in Psychology and credits towards a Business Administration degree. His education also includes certificates in database design, PL/SQL, SQL, and SAS programming. For the Wisconsin Department of Transportation, he was responsible for designing, coding, and testing systems to load and maintain highway inventory data in a DB2 database, including converting location data between systems. He also added metric data and validation to their online and batch bridge data systems. Additionally, he participated in extracting, converting, and loading data between Oracle and Sybase databases for a school district in Texas.
Dqs mds-matching 15042015
This document provides an overview of Data Quality Services (DQS) matching and Master Data Services (MDS). It discusses record matching, data issues that affect matching, the DQS matching process, and key components like the matching policy and knowledge base. It also introduces MDS and its configuration tools.
Resume
Prasad has over 3 years of experience as a software developer using Microsoft BI tools like SQL Server Integration Services, Reporting Services and Analysis Services. He has extensive experience developing ETL processes in SSIS to load data from various sources into data warehouses built on SQL Server. He has worked on projects for clients like CIBER and ICICI Prudential, developing SSIS packages to extract, transform and load data from different systems into a centralized data warehouse for reporting purposes.
Session#5; data resource managment
This document discusses data resource management and provides an overview of key concepts. It covers managing large amounts of data from various sources, the database approach for organizing data in tables with records and fields, and database management systems that allow centralized access and management of data. The document also discusses business intelligence tools for analyzing data to improve decision-making, including data warehousing, online analytical processing, and data mining.
ETL Developer Resume
This document contains a resume for Tefari Heyie. It summarizes his professional experience which includes over 3 years working with SQL Server, databases, and data integration. He has expertise in SQL queries, indexes, stored procedures, SSIS ETL packages, and SSRS reports. He is proficient in designing databases, data warehousing, and business intelligence solutions. His education includes a Bachelor's degree in Computer Science and Microsoft SQL Server certifications.
Venkatesh-MSBI
This document contains the resume of Venkatesh Annam. It summarizes his professional experience in business intelligence and data warehousing using Microsoft SQL Server. It lists his skills like Extract, Transform, Load development in SSIS, cube development in SSAS, and report development in SSRS. It describes two projects he worked on, one for Equitable Life Insurance involving ETL development and report building, and another for ICICI Prudential involving data integration through SSIS packages between various source systems.
PharmMD ETL Developer Job Description
PharmMD has a new job opening for an ETL Developer. See job description attached. Interested parties should send their resume to Cynthia.Sandahl@pharmmd.com
Migration to Drupal
This document provides guidance on migrating data from an existing system to Drupal. It outlines steps to understand the existing data, migrate it to a common format, import it into the Drupal database, and test the results. Key steps include understanding relationships in the original data, migrating it to a format like XML or CSV, importing it into the Drupal MySQL database using modules like Table Wizard or Migrate, and thoroughly testing the imported data. Proper planning and backups are also emphasized.
Recommended
Database ResumeLinkedIn
Patrick A. Seery has over 3 years of experience programming DB2 and Oracle databases. He has a BS in Psychology and credits towards a Business Administration degree. His education also includes certificates in database design, PL/SQL, SQL, and SAS programming. For the Wisconsin Department of Transportation, he was responsible for designing, coding, and testing systems to load and maintain highway inventory data in a DB2 database, including converting location data between systems. He also added metric data and validation to their online and batch bridge data systems. Additionally, he participated in extracting, converting, and loading data between Oracle and Sybase databases for a school district in Texas.
Dqs mds-matching 15042015
This document provides an overview of Data Quality Services (DQS) matching and Master Data Services (MDS). It discusses record matching, data issues that affect matching, the DQS matching process, and key components like the matching policy and knowledge base. It also introduces MDS and its configuration tools.
Resume
Prasad has over 3 years of experience as a software developer using Microsoft BI tools like SQL Server Integration Services, Reporting Services and Analysis Services. He has extensive experience developing ETL processes in SSIS to load data from various sources into data warehouses built on SQL Server. He has worked on projects for clients like CIBER and ICICI Prudential, developing SSIS packages to extract, transform and load data from different systems into a centralized data warehouse for reporting purposes.
Session#5; data resource managment
This document discusses data resource management and provides an overview of key concepts. It covers managing large amounts of data from various sources, the database approach for organizing data in tables with records and fields, and database management systems that allow centralized access and management of data. The document also discusses business intelligence tools for analyzing data to improve decision-making, including data warehousing, online analytical processing, and data mining.
ETL Developer Resume
This document contains a resume for Tefari Heyie. It summarizes his professional experience which includes over 3 years working with SQL Server, databases, and data integration. He has expertise in SQL queries, indexes, stored procedures, SSIS ETL packages, and SSRS reports. He is proficient in designing databases, data warehousing, and business intelligence solutions. His education includes a Bachelor's degree in Computer Science and Microsoft SQL Server certifications.
Venkatesh-MSBI
This document contains the resume of Venkatesh Annam. It summarizes his professional experience in business intelligence and data warehousing using Microsoft SQL Server. It lists his skills like Extract, Transform, Load development in SSIS, cube development in SSAS, and report development in SSRS. It describes two projects he worked on, one for Equitable Life Insurance involving ETL development and report building, and another for ICICI Prudential involving data integration through SSIS packages between various source systems.
PharmMD ETL Developer Job Description
PharmMD has a new job opening for an ETL Developer. See job description attached. Interested parties should send their resume to Cynthia.Sandahl@pharmmd.com
Migration to Drupal
This document provides guidance on migrating data from an existing system to Drupal. It outlines steps to understand the existing data, migrate it to a common format, import it into the Drupal database, and test the results. Key steps include understanding relationships in the original data, migrating it to a format like XML or CSV, importing it into the Drupal MySQL database using modules like Table Wizard or Migrate, and thoroughly testing the imported data. Proper planning and backups are also emphasized.
Resume of Jay Zabinsky
This document summarizes Jay Zabinsky's experience as a consultant with over 15 years of experience in metadata management, data modeling, database design, data analysis, data integration, and data governance. He has extensive experience with software such as Oracle, SQL Server, IBM Information Analyzer, Erwin, and SSIS. His experience includes roles managing metadata repositories, data modeling, ETL development, data warehousing, and data integration projects.
Jalajaa_SQLDBA
This document contains the resume of Jalajaa Hariharan who has over 3 years of experience as a Microsoft SQL Server Database Administrator. Some of her key skills and responsibilities include installing, configuring, and managing SQL servers; designing and planning database capacity; migrating SQL servers; implementing backup strategies; performing performance tuning; and providing 24x7 support. She is proficient with SQL Server versions 2005 through 2016 and has experience with tools such as SSIS, SSRS, and PowerShell.
Master data services
Master Data Services (MDS) is a SQL Server solution that allows organizations to manage master lists of non-transactional reference data. The goal of MDS is to establish reliable, centralized master data that can be analyzed to support better business decisions. MDS includes tools for discovering, defining, and maintaining master data lists. It also integrates with Excel through an add-in to load, publish, and validate data.
A STUDY ON GRAPH STORAGE DATABASE OF NOSQL
Big Data is used to store huge volume of both structured and unstructured data which is so large and is
hard to process using current / traditional database tools and software technologies. The goal of Big Data
Storage Management is to ensure a high level of data quality and availability for business intellect and big
data analytics applications. Graph database which is not most popular NoSQL database compare to
relational database yet but it is a most powerful NoSQL database which can handle large volume of data in
very efficient way. It is very difficult to manage large volume of data using traditional technology. Data
retrieval time may be more as per database size gets increase. As solution of that NoSQL databases are
available. This paper describe what is big data storage management, dimensions of big data, types of data,
what is structured and unstructured data, what is NoSQL database, types of NoSQL database, basic
structure of graph database, advantages, disadvantages and application area and comparison of various
graph database.
Data Quality Services in SQL Server 2012
An introduction to Data Quality Services. DQS enables to discover, build, and manage knowledge about your data. Use that knowledge to perform data cleansing, matching and profiling. We will explore the numerous features and capabilities of Data Quality Services and its integration with SSIS with the DQS Cleansing Transform. Data Quality Services in SQL Server 2012
Dm data pre processing
This document discusses data pre-processing techniques. It describes data cleaning which detects and corrects errors in data. Data integration combines data from different sources. Data transformation converts data between formats. Data reduction simplifies data through methods like editing, scaling, encoding, sorting and tabulation. The quality of raw data affects mining results, so pre-processing aims to improve data quality and efficiency.
5 data resource management
A database is a set of related data. A database management system (DBMS) allows users to access and perform operations on data in a database. Some key benefits of a DBMS include easy data use, centralized data control, and data security. Traditional file systems have disadvantages like data redundancy, inconsistency, and lack of integrity and security. There are different types of database models including hierarchical, network, relational, and object-oriented.
DBArtisan XE6 Datasheet
DBArtisan XE6 is a database administration tool that helps DBAs manage databases across platforms more efficiently. It streamlines common tasks, reduces errors, and provides comprehensive capabilities for data management. As data volumes grow, the role of the DBA is evolving to handle multiple concurrent responsibilities. DBArtisan facilitates this role by providing performance monitoring, space and data management tools, and security management in a single interface.
data resource management
Data resource management involves applying information systems technology to manage data resources. It includes activities like creating, storing, organizing, and retrieving data using database management systems. There are different types of databases like operational, distributed, data warehouses, data marts, and end user databases. Data warehouses store historical data from various operational databases to help identify trends. Data mining techniques are used to better understand data through analysis, sorting, extracting patterns and relationships to gain insights. Common applications of data mining include banking, customer relationship management, targeted marketing, fraud detection, and scientific data analysis.
Reconciling your Enterprise Data Warehouse to Source Systems
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Role of Data Cleaning in Data Warehouse
Data cleaning is an essential part of building a data warehouse as it improves data quality by detecting and removing errors and inconsistencies. Data warehouses integrate large amounts of data from various sources, so the probability of dirty data is high. Clean data is vital for decision making based on the data warehouse. The data cleaning process involves data analysis, defining transformation rules, verification of cleaning, applying transformations, and incorporating cleaned data. Tools can help support the different phases of data cleaning from data profiling to specialized cleaning of particular domains.
Lecture 04 data resource management
This document provides an overview of data resource management and file organization concepts. It discusses key terms like binary, bit, byte, field, record, and file. It explains different file organization methods like traditional file environments and database management systems. It also summarizes different types of databases like relational, hierarchical, network, and object-oriented databases. Finally, it discusses database design, management, querying, distribution, warehousing, and trends like linking databases to the web.
Context-Sensitive Indexes for Performance Optimization of SQL Queries in Mult...
This document discusses context-sensitive indexes in relational database management systems to optimize SQL query performance in multi-tenant and multi-application environments. It proposes allowing applications, tenants, and users to define their own indexes on shared database tables to optimize queries specific to them, while keeping these indexes isolated from other queries for optimization purposes. Currently, database optimizers consider all indexes on referenced tables uniformly, regardless of purpose, leading to suboptimal performance. The proposal aims to address this by making indexes sensitive to the context and origin of queries, improving optimization and response times for complex workloads on shared databases and schemas.
Data Modeling PPT
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
Advanced Database System
Here you can gain knowledge from traditional database system to advanced database system and also know about that new features of database.
Datawarehousing
The document discusses key concepts related to data warehousing including:
1) What data warehousing is, its main components, and differences from OLTP systems.
2) The typical architecture of a data warehouse including operational data sources, storage, and end-user access tools.
3) Important considerations like data flows, integration, management of metadata, and tools/technologies used.
4) Additional topics such as benefits, challenges, administration, and data marts.
Essbase
Oracle Essbase is a leading online analytical processing (OLAP) server that supports forecasting, variance analysis, scenario planning, and other advanced analytics functions. It integrates with multiple data sources and delivers information through a variety of reporting options. Oracle Essbase is designed to scale for large user communities and data sets while providing rapid analysis, calculation times, and a rich user experience through intuitive interfaces.
Ooluk Data Dictionary Manager
Ooluk Data Dictionary Manager allows easy metadata management for heterogeneous databases. You can document and tag your entire data envionment allowing users to better understand your data.
Resume - Vikash Chilana - 3yrs Exp
- Vikash Chilana is seeking a role utilizing his 3.3 years of experience in ETL testing and 1 year of experience monitoring and testing enterprise solutions in Informatica.
- He has comprehensive knowledge of SQL/PL-SQL and hands-on experience writing SQL queries, stored procedures, and cursors.
- His technical skills include Informatica, ETL, SQL, VB-Macros, Oracle 10g, Windows, Unix, Toad, PL/SQL, HP-QC, and Crystal Reports.
Arun Mathew Thomas_resume
This document provides a detailed summary of Arun Mathew Thomas's work experience in IT and data warehousing. It outlines his over 9 years of experience in developing and maintaining data warehouse applications, with expertise in ETL processes, data modeling, performance tuning, and working with tools like Informatica, Teradata, and SQL. It also provides details on two specific roles he held, including developing mappings to load data from various sources into an enterprise data warehouse for Anthem Inc., and serving as an ETL/data quality architect for customer data projects.
8143320263_krishna12
Krishna has over 2 years of experience designing and developing ETL processes in IBM InfoSphere Datastage. He has expertise extracting data from heterogeneous systems, transforming it according to business logic, and loading it into target databases. Some of his skills include designing parallel jobs, working with various Datastage stages, and using the Datastage Administrator, Designer, and Director tools. He has worked on data warehouse projects in the banking and insurance industries.
Ramachandran_ETL Developer
Ramachandran has over 9 years of experience as a Senior Informatica Developer. He has expertise in data warehousing, ETL development and implementation using Informatica PowerCenter. Some of his key skills include dimensional modeling, mapping complex transformations, tuning Informatica workflows, and working with databases such as Oracle, SQL Server and Teradata. He has worked on multiple projects in the healthcare domain for clients in the US and India.
More Related Content
What's hot
Resume of Jay Zabinsky
This document summarizes Jay Zabinsky's experience as a consultant with over 15 years of experience in metadata management, data modeling, database design, data analysis, data integration, and data governance. He has extensive experience with software such as Oracle, SQL Server, IBM Information Analyzer, Erwin, and SSIS. His experience includes roles managing metadata repositories, data modeling, ETL development, data warehousing, and data integration projects.
Jalajaa_SQLDBA
This document contains the resume of Jalajaa Hariharan who has over 3 years of experience as a Microsoft SQL Server Database Administrator. Some of her key skills and responsibilities include installing, configuring, and managing SQL servers; designing and planning database capacity; migrating SQL servers; implementing backup strategies; performing performance tuning; and providing 24x7 support. She is proficient with SQL Server versions 2005 through 2016 and has experience with tools such as SSIS, SSRS, and PowerShell.
Master data services
Master Data Services (MDS) is a SQL Server solution that allows organizations to manage master lists of non-transactional reference data. The goal of MDS is to establish reliable, centralized master data that can be analyzed to support better business decisions. MDS includes tools for discovering, defining, and maintaining master data lists. It also integrates with Excel through an add-in to load, publish, and validate data.
A STUDY ON GRAPH STORAGE DATABASE OF NOSQL
Big Data is used to store huge volume of both structured and unstructured data which is so large and is
hard to process using current / traditional database tools and software technologies. The goal of Big Data
Storage Management is to ensure a high level of data quality and availability for business intellect and big
data analytics applications. Graph database which is not most popular NoSQL database compare to
relational database yet but it is a most powerful NoSQL database which can handle large volume of data in
very efficient way. It is very difficult to manage large volume of data using traditional technology. Data
retrieval time may be more as per database size gets increase. As solution of that NoSQL databases are
available. This paper describe what is big data storage management, dimensions of big data, types of data,
what is structured and unstructured data, what is NoSQL database, types of NoSQL database, basic
structure of graph database, advantages, disadvantages and application area and comparison of various
graph database.
Data Quality Services in SQL Server 2012
An introduction to Data Quality Services. DQS enables to discover, build, and manage knowledge about your data. Use that knowledge to perform data cleansing, matching and profiling. We will explore the numerous features and capabilities of Data Quality Services and its integration with SSIS with the DQS Cleansing Transform. Data Quality Services in SQL Server 2012
Dm data pre processing
This document discusses data pre-processing techniques. It describes data cleaning which detects and corrects errors in data. Data integration combines data from different sources. Data transformation converts data between formats. Data reduction simplifies data through methods like editing, scaling, encoding, sorting and tabulation. The quality of raw data affects mining results, so pre-processing aims to improve data quality and efficiency.
5 data resource management
A database is a set of related data. A database management system (DBMS) allows users to access and perform operations on data in a database. Some key benefits of a DBMS include easy data use, centralized data control, and data security. Traditional file systems have disadvantages like data redundancy, inconsistency, and lack of integrity and security. There are different types of database models including hierarchical, network, relational, and object-oriented.
DBArtisan XE6 Datasheet
DBArtisan XE6 is a database administration tool that helps DBAs manage databases across platforms more efficiently. It streamlines common tasks, reduces errors, and provides comprehensive capabilities for data management. As data volumes grow, the role of the DBA is evolving to handle multiple concurrent responsibilities. DBArtisan facilitates this role by providing performance monitoring, space and data management tools, and security management in a single interface.
data resource management
Data resource management involves applying information systems technology to manage data resources. It includes activities like creating, storing, organizing, and retrieving data using database management systems. There are different types of databases like operational, distributed, data warehouses, data marts, and end user databases. Data warehouses store historical data from various operational databases to help identify trends. Data mining techniques are used to better understand data through analysis, sorting, extracting patterns and relationships to gain insights. Common applications of data mining include banking, customer relationship management, targeted marketing, fraud detection, and scientific data analysis.
Reconciling your Enterprise Data Warehouse to Source Systems
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Role of Data Cleaning in Data Warehouse
Data cleaning is an essential part of building a data warehouse as it improves data quality by detecting and removing errors and inconsistencies. Data warehouses integrate large amounts of data from various sources, so the probability of dirty data is high. Clean data is vital for decision making based on the data warehouse. The data cleaning process involves data analysis, defining transformation rules, verification of cleaning, applying transformations, and incorporating cleaned data. Tools can help support the different phases of data cleaning from data profiling to specialized cleaning of particular domains.
Lecture 04 data resource management
This document provides an overview of data resource management and file organization concepts. It discusses key terms like binary, bit, byte, field, record, and file. It explains different file organization methods like traditional file environments and database management systems. It also summarizes different types of databases like relational, hierarchical, network, and object-oriented databases. Finally, it discusses database design, management, querying, distribution, warehousing, and trends like linking databases to the web.
Context-Sensitive Indexes for Performance Optimization of SQL Queries in Mult...
This document discusses context-sensitive indexes in relational database management systems to optimize SQL query performance in multi-tenant and multi-application environments. It proposes allowing applications, tenants, and users to define their own indexes on shared database tables to optimize queries specific to them, while keeping these indexes isolated from other queries for optimization purposes. Currently, database optimizers consider all indexes on referenced tables uniformly, regardless of purpose, leading to suboptimal performance. The proposal aims to address this by making indexes sensitive to the context and origin of queries, improving optimization and response times for complex workloads on shared databases and schemas.
Data Modeling PPT
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
Advanced Database System
Here you can gain knowledge from traditional database system to advanced database system and also know about that new features of database.
Datawarehousing
The document discusses key concepts related to data warehousing including:
1) What data warehousing is, its main components, and differences from OLTP systems.
2) The typical architecture of a data warehouse including operational data sources, storage, and end-user access tools.
3) Important considerations like data flows, integration, management of metadata, and tools/technologies used.
4) Additional topics such as benefits, challenges, administration, and data marts.
Essbase
Oracle Essbase is a leading online analytical processing (OLAP) server that supports forecasting, variance analysis, scenario planning, and other advanced analytics functions. It integrates with multiple data sources and delivers information through a variety of reporting options. Oracle Essbase is designed to scale for large user communities and data sets while providing rapid analysis, calculation times, and a rich user experience through intuitive interfaces.
Ooluk Data Dictionary Manager
Ooluk Data Dictionary Manager allows easy metadata management for heterogeneous databases. You can document and tag your entire data envionment allowing users to better understand your data.
What's hot (18)
Reconciling your Enterprise Data Warehouse to Source Systems
Reconciling your Enterprise Data Warehouse to Source Systems
Context-Sensitive Indexes for Performance Optimization of SQL Queries in Mult...
Context-Sensitive Indexes for Performance Optimization of SQL Queries in Mult...
Similar to MANOJ
Resume - Vikash Chilana - 3yrs Exp
- Vikash Chilana is seeking a role utilizing his 3.3 years of experience in ETL testing and 1 year of experience monitoring and testing enterprise solutions in Informatica.
- He has comprehensive knowledge of SQL/PL-SQL and hands-on experience writing SQL queries, stored procedures, and cursors.
- His technical skills include Informatica, ETL, SQL, VB-Macros, Oracle 10g, Windows, Unix, Toad, PL/SQL, HP-QC, and Crystal Reports.
Arun Mathew Thomas_resume
This document provides a detailed summary of Arun Mathew Thomas's work experience in IT and data warehousing. It outlines his over 9 years of experience in developing and maintaining data warehouse applications, with expertise in ETL processes, data modeling, performance tuning, and working with tools like Informatica, Teradata, and SQL. It also provides details on two specific roles he held, including developing mappings to load data from various sources into an enterprise data warehouse for Anthem Inc., and serving as an ETL/data quality architect for customer data projects.
8143320263_krishna12
Krishna has over 2 years of experience designing and developing ETL processes in IBM InfoSphere Datastage. He has expertise extracting data from heterogeneous systems, transforming it according to business logic, and loading it into target databases. Some of his skills include designing parallel jobs, working with various Datastage stages, and using the Datastage Administrator, Designer, and Director tools. He has worked on data warehouse projects in the banking and insurance industries.
Ramachandran_ETL Developer
Ramachandran has over 9 years of experience as a Senior Informatica Developer. He has expertise in data warehousing, ETL development and implementation using Informatica PowerCenter. Some of his key skills include dimensional modeling, mapping complex transformations, tuning Informatica workflows, and working with databases such as Oracle, SQL Server and Teradata. He has worked on multiple projects in the healthcare domain for clients in the US and India.
Ashish_Maheshwari_Data_Analyst
Ashish Maheshwari has over 8 years of experience in data modeling, integration, analytics, mining, ETL processes, BI applications, and data warehousing. He currently works as a Technical Lead at Ness Technologies, Bangalore and has experience working on projects for clients such as FGL, Marks, and Target. His skills include Oracle SQL, PL/SQL, Datastage, data warehousing concepts, R programming, and Agile development processes.
Nitin Paliwal
The document contains Nitin Paliwal's resume. It includes his contact information, career objective, professional summary highlighting over 4.5 years of experience in data warehousing using Datastage ETL. It lists his technical skills and certifications in Datastage, Cognos, SQL. It details his professional experience as an ETL Datastage developer at Tech Mahindra working on projects for Chevron Corporation involving data integration, data quality management, and runtime support. It concludes with his educational qualifications and hobbies.
RAM PRASAD SVK
This document provides a summary of experience and qualifications for Ram Prasad SVK, an Informatica developer with over 4 years of experience developing and enhancing data warehousing projects using Informatica PowerCenter. It includes details of his work experience on 3 projects involving ETL development from various data sources to load into data warehouses and data marts. It also lists his educational qualifications and technical skills including expertise in Informatica, Oracle, and Windows.
Varadarajan CV
Varadarajan Sourirajan is a data architect with over 16 years of experience seeking a new position. He has extensive experience in data modeling for both online transaction processing and data warehousing applications. Currently he is working on implementing a data warehouse for the treasury line of business at a large bank in the US, drawing on his experience delivering previous data warehouse projects and a proven track record of success.
ChakravarthyUppara
This document contains a resume for Chakravarthy Uppara. It summarizes his contact information, objective, 6+ years of experience in database development using SQL Server and SSIS. It details his roles and responsibilities in projects for Tesco and Accenture developing ETL processes and interfaces to integrate various systems. His technical skills include SQL Server, SSIS, SSAS and .NET. He holds a B-Tech in Information Technology and is currently employed as a Senior Software Engineer at Tesco in Bangalore, India.
Arun Kondra
This document contains a professional summary and resume for Arun Roy Kondra. It summarizes his experience of over 4 years working with data warehousing and ETL solutions using Informatica PowerCenter. It details his technical skills and 3 projects he has worked on extracting and transforming data from various sources like Oracle, GreenPlum and flat files into data warehouses.
Sanket_Informatica_CV
Sanket Gaware is an experienced ETL developer with over 4 years of experience using Informatica Power Center 9.x to develop mappings and load data. He has worked on projects in various domains extracting data from sources like Oracle, SQL Server, MySQL and loading into data warehouses. Currently he works as an ETL developer for IBrain Decision Software developing mappings for their veterinary management system.
Prasad_Resume
Prasad Kommoju has 5 years of experience in ETL development using Informatica. He has worked on projects in banking and manufacturing. His skills include Informatica PowerCenter, IDQ, MDM, DIH, SQL, and UNIX. Currently he works as a Senior Software Engineer at Tech Mahindra on a project with MasterCard managing customer data.
Mani_Sagar_ETL
Mani Sagar is an ETL Sr Developer and Lead with over 8 years of experience in designing, developing, and maintaining large enterprise applications. He has expert knowledge of ETL technologies like Informatica and data management processes including data migration, profiling, quality, security, and warehousing. He has led teams of up to 8 developers and delivered projects on time for clients across various industries.
Levin_Michael_2016-04
This document is a resume for R. Michael Levin summarizing his objective, clearances, technical skills, and professional experience. Levin has over 20 years of experience in fields like enterprise architecture, data architecture, data modeling, database administration, and project management. He currently works as a Solution Architect and Technical Project Manager developing data warehouses and managing teams. His previous roles include positions as a Principal Solution Data Architect, Senior Data Architect, and Senior Database Architect at various companies.
Pradeepa dharmappa
Pradeepa Dharmappa is seeking a job with career growth and financial growth. She has over 5 years of experience in data warehousing using tools like Informatica and SQL. She has worked as a Software Engineer at HCL Technologies and as a Senior Software Engineer at InterCall. Her experience includes ETL development, data modeling, performance tuning, and working with databases like Oracle, SQL Server, and Informix. She has a bachelor's degree in computer science with over 80% marks.
Madhukar_Eunny_BIDW_Consultant
This document contains the professional summary and experience of Madhukar Eunny. He has over 12 years of experience working as a senior consultant on data warehousing projects. His roles have included ETL architect, developer, team lead, and production support. He has strong skills in ETL tools like Informatica and databases like Teradata, Oracle, and SQL Server. He currently works as a senior BI consultant for Medibank where he is responsible for requirements gathering, data modeling, ETL development, and providing business support.
Resume_Kunal N Kadbhane
Kunal N Kadbhane has over 3 years of experience as a software engineer in the IT industry. He has extensive experience with Informatica PowerCenter 9x, developing ETL mappings and transformations between various data sources like Oracle, SQL Server, and flat files. He has worked on multiple projects involving data warehousing and migration for clients such as Ultra Tech Cement and Reliance Industries. His responsibilities included requirement gathering, mapping development, testing, production support, and issue resolution.
Borden_resume_1JUN16
Gary Borden has over 25 years of experience in ERP systems such as SAP and Oracle, with a focus on master data management, business analytics, and CRM systems like Salesforce.com. He currently works as an SAP Material Master Coordinator and Salesforce.com Database Administrator at ACCO Brands. Previously he has held data analyst roles at Corbus LLC, CSC, and MeadWestvaco where he managed ERP data migration projects, developed reports, and performed mass data loads. He has a bachelor's degree in management science from Wright State University.
manasiCV_oracleDBA
Manasi Sunil Narvankar is seeking a job that allows her to learn and grow. She has two years of experience as a Database Administrator supporting Oracle instances. Her responsibilities included database administration, troubleshooting, installation, patching, and upgrades. She currently works as an Oracle DBA for IT Source India Pvt Ltd, representing HP India Sales Pvt. Ltd., where her duties involve working with production, testing, and standby databases and upgrading databases from 10g to 11g.
Shraddha Verma_IT_ETL Architect_10+_CV
This document contains the resume of Shraddha Verma, a Data Warehouse Architect with over 10 years of experience in designing and developing ETL applications for data warehouses. She has extensive experience with tools like DataStage, Informatica, and Teradata utilities. She has worked on projects in various domains for clients like United Health Group, Sapient, and Tata Consultancy Services. Her skills include ETL design, data quality, project management, and people management. She is looking for a role as a techno-functional consultant in the data warehousing/BI domain.
Similar to MANOJ (20)
MANOJ
- 1. J.MANOJ PRABHAKAR Mobile : 09742314702| manojkarunya2013@gmail.com Objective I am looking forward to join a progressive organization. I am Strong team builder. I have high level of personal morals and integrity. I am Goal oriented, self-motivated and committed to the successful outcome of the project. I am willingtoworkhardand have a great desire tolearn. About Me Education Two year, One months of experience in using ETL methodologies for supporting Data Extraction, Data Migration, Data Transformation and loading using InformaticaPowercenter8.6.0and9.0.1 Strong experience in Extraction, Transformation, Loading (ETL) data from various sources into Data Warehouses and Data Marts using Informatica Power Centre (Designer, Workflow Manager, Workflow Monitor,Metadata Manger). Strongunderstandingof OLAPandOLTP Concepts Experience inSQL Strong interpersonal skills, including experience workinginfastpaced,team-orientedenvironments M.C.A with CGPA 6.87 (on 10.0) from Karunya University,Coimbatore. B.Sc(CS) with60.43%, fromPeriyarUniversity. HSC with 52%, from AET Higher Secondary School,ATTUR. SSLC with 58%, Tagore Higher Secondary School, ATTUR. Work Experience 8Months GAPBRIDGE Software Solution, Bangalore For HCL Client ,Chennai Technology ETL TOOL( Informatica),Sql Server,Software Testing(MANUAL),SopraMigrationTool, Tableau Domain Insurance
- 2. Projects Project Title : Fundamento Data Migration Client : AEGON, Netherland Description: This project is for migration of data from a system called HAS (Mainframe Based system) to another System called SOPRA.HAS is mortgage administration system.SOPRA is a Loan Servicing System. All the data from HAS is moved to SOPRA Loan Servicing DB with set of Business Requirements. Business Requirements are implemented by Informatica ETL tool. The Data from HAS is Extracted to VSAM files and the same is Processed with Two Staging areas (Primary and Secondary Staging) and a Target file is Generated (called target SLS file).Statements to load the File generated to the Loan Servicing DB of SOPRA. Once after Migrationof all the data, the Mortgage ProcessingiscarriedoutbySOPRA. Responsibilities: CreatedMappingsinInformaticaDesignertoextractdatafrom Heterogeneousdatasourceslike Oracle,files,MS SQL Server,MS Access& Excel Sheetsto loadintothe data warehouse withvarioustypesof transformationslike Aggregator,Expression,Filter,Joiner,Lookup,External Procedure,Router&Update Strategy. Createdandmaintaineddocumentsincludingdataqualityplandesign,mappinginventory,mappingspecifications, change requestform,unittestplan,testcase list,target-source matrix etc. InvolvedinfixinginvalidMappings,testingof StoredProceduresandFunctions,UnitandIntegrationTestingof InformaticaTasks,Workflowsandthe TargetData. Work Experience 1Year 4 Months COLIZEEUM Technology, Chennai As Informatica Developer Technology ETL TOOL( Informatica),Sql Server,Software Testing(MANUAL) Domain Banking
- 3. Description: ICICIBank had variousproducts like Accounts&Deposits,Loans,Insurance andPremiumBankingetc.Thisprojectis mainlytotestthe Accounts& Depositsmodule functionality.The Accounts&Depositshasdifferentaccounttypes like Savings,Salary,Current,Demat,Deposits,Rural andSafe Depositlocker. Responsibilities: CreatedMappingsinInformaticaDesignertoextractdatafrom Heterogeneousdatasourceslike Oracle,files,MS SQL Server,MS Access& Excel Sheetstoloadintothe data warehouse withvarioustypesof transformations like Aggregator,Expression,Filter,Joiner,Lookup,Router&Update Strategy. Createdandmaintaineddocumentsincludingdataqualityplandesign,mappinginventory,mappingspecifications, change requestform,unittestplan,testcase list,target-source matrix etc. Languages : Tamil, English Skills ETL ( Tool ) INFORMATICA Databases Sql Server,Oracle Areasof Interest Coding,Analyst. Testing Software Testing(Manual) Personal Information DOB 10.06.1989 Email ID : manojkarunya2013@gmail.com PAN CHHPM1314H Gender : MALE [J.MANOJ PRABHAKAR] Tamil English