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Website : http://www.todaycourses.com Informatica Online Training Concepts Introduction to Dataware housing (What/Why/How Dataware housing) Slowly Changing Dimensions (SCD1, SCD2, SCD3) Metadata Dimentinal Table Types Of Dim Tables Fact Table Types of Fact Tables OLTP (OnLine Transaction Processing) OLAP (Online Analysis And Processing) OLTP Vs OLAP Advantages of OLAP Different Methodologies of DWH PowerCenter Components and User Interface • 1.Informatica PowerCenter Architecture • 2.Informatica PowerCenter Client Tools • 3.Start Using of the Designer, Workflow Manager and Workflow Monitor informatica training,informatica online training,online informatica training,online informatica training, informatica online training, informatica corporate training, informatica training videos, informatica training material, informatica training videos, best informatica online training,informatica courses, informatica training online, informatica online training institutes in hyderabad,informatica online training videos, informatica video tutorials, informatica video training, informatica tutorial videos
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informatica Online Training Institute in India,USA,UK,Canada.
Informatica is ETL tool which is generally used for extracting the source information after utilizing the transformation which is requied, and loading it to the target. In another section we're planning to try to spell out the usage of Informatica using an example in the Data Warehouse atmosphere.we're supplying informatica Online Training in India,USA,UK,Canada.
http://smartmindonlinetraining.com/informatica-online-training/
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The document discusses changes to the ABAP dictionary in March 2005. It explains that objects must be activated in the SAP system to be used by other objects, and that activating an object releases any locks on it. It describes how SAP handles version management, maintaining both active and historical versions of objects. It also notes that changing a value table's primary key linked to a domain requires extensive changes due to embedded links between the domain and table.
Chapter 06 abap repository information system1
The document discusses the ABAP Repository Information System, which allows users to search for ABAP development objects. It describes the Find and Where-Used functions that allow searching for objects by type and attributes or finding all objects that use a specific object. The Repository Information System is demonstrated by searching for tables that use a standard SAP field using the Where-Used functionality.
Chapter 04 abap dictionary tables in relational databases1
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Informatica Online Training
Hi This is Rao, Informatica Online Trainer Providing online training globally. Please contact me for online training @ 9948713895
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The document describes how FME was used to consolidate a client's large national drainage asset database. Overlapping asset schemes caused duplication that needed resolving. FME processed the data through stages including duplicate removal, subject matter expert review, quality assurance checks, and submission to the client's system. It automated tasks like updating upstream/downstream references and support connections. FME also determined asset elevations from LiDAR point clouds. The resulting single consolidated drainage network provides the client an improved understanding of their extended asset inventory.
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Tuning a Spark ML model with cross-validation can be an extremely computationally expensive process. As the number of hyperparameter combinations increases, so does the number of models being evaluated. The default configuration in Spark is to evaluate each of these models one-by-one to select the best performing. When running this process with a large number of models, if the training and evaluation of a model does not fully utilize the available cluster resources then that waste will be compounded for each model and lead to long run times.
Enabling model parallelism in Spark cross-validation, from Spark 2.3, will allow for more than one model to be trained and evaluated at the same time and make better use of cluster resources. We will go over how to enable this setting in Spark, what effect this will have on an example ML pipeline and best practices to keep in mind when using this feature.
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informatica Online Training Institute in India,USA,UK,Canada.
Informatica is ETL tool which is generally used for extracting the source information after utilizing the transformation which is requied, and loading it to the target. In another section we're planning to try to spell out the usage of Informatica using an example in the Data Warehouse atmosphere.we're supplying informatica Online Training in India,USA,UK,Canada.
http://smartmindonlinetraining.com/informatica-online-training/
Chapter 07 abap dictionary changes1
The document discusses changes to the ABAP dictionary in March 2005. It explains that objects must be activated in the SAP system to be used by other objects, and that activating an object releases any locks on it. It describes how SAP handles version management, maintaining both active and historical versions of objects. It also notes that changing a value table's primary key linked to a domain requires extensive changes due to embedded links between the domain and table.
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Chapter 04 abap dictionary tables in relational databases1
This document discusses different types of tables in the SAP ABAP Dictionary, including transparent tables, structures, pool tables, cluster tables, and views. It describes technical settings that can optimize storage requirements and table access behavior, such as data class, size category, and buffering type. Indexes are also covered, and it is explained that unique index scans are generally faster than index range scans or full table scans when retrieving data.
Informatica Online Training
Hi This is Rao, Informatica Online Trainer Providing online training globally. Please contact me for online training @ 9948713895
1Spatial: Leeds FME World Tour: Improving the flow of asset information with FME
The document describes how FME was used to consolidate a client's large national drainage asset database. Overlapping asset schemes caused duplication that needed resolving. FME processed the data through stages including duplicate removal, subject matter expert review, quality assurance checks, and submission to the client's system. It automated tasks like updating upstream/downstream references and support connections. FME also determined asset elevations from LiDAR point clouds. The resulting single consolidated drainage network provides the client an improved understanding of their extended asset inventory.
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Model Parallelism in Spark ML Cross-Validation with Nick Pentreath and Bryan ...
Tuning a Spark ML model with cross-validation can be an extremely computationally expensive process. As the number of hyperparameter combinations increases, so does the number of models being evaluated. The default configuration in Spark is to evaluate each of these models one-by-one to select the best performing. When running this process with a large number of models, if the training and evaluation of a model does not fully utilize the available cluster resources then that waste will be compounded for each model and lead to long run times.
Enabling model parallelism in Spark cross-validation, from Spark 2.3, will allow for more than one model to be trained and evaluated at the same time and make better use of cluster resources. We will go over how to enable this setting in Spark, what effect this will have on an example ML pipeline and best practices to keep in mind when using this feature.
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Seminar on olap online analytical
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Productionizing Spark ML pipelines with the portable format for analytics
The common perception of machine learning is that it starts with data and ends with a model. In real-world production systems, the traditional data science and machine learning workflow of data preparation, feature engineering, and model selection, while important, is only one aspect. A critical missing piece is the deployment and management of models, as well as the integration between the model creation and deployment phases.
This is particularly challenging in the case of deploying Apache Spark ML pipelines for low-latency scoring. Because execution of Spark ML pipelines is tightly coupled with the Spark SQL runtime, deployment using Spark is ill-suited to the needs of real-time predictive applications.
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Data Science Training in Chennai at Credo Systemz provided by experienced Data Scientists. Our Data Science Course module is completely designed about how to analyze Big Data using R programming and Hadoop. Credo Systemz is the Best place to learn Data Science with Python Training in Chennai. Data Science course certification will help you be a professional Data Scientist. If you really Interested to Learn Best Data Science course in Chennai, then Credo Systemz is the Right place.
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Surprisingly, our findings are well spread between Spark SQL and Spark Scala and contrary to our expectations Spark Scala did not outperform Spark SQL in all aspects but support the idea that applied optimizations appear to be implemented in a different way by Spark for its core and its extension Spark SQL. The API on top of Spark provides extra information about the underlying structured data, which is probably used to perform additional optimizations.
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Why wait? Convert your e-resource bibliographic records to RDA. Library vendors can help convert your existing catalog records. In-house options are also available. The Library of Congress has updated thousands of authority records to RDA headings. Combine your RDA conversion project with authority control processing to maximize your effort. Some additional steps for the project may include use of ILS global update functions and load table profiles.
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Lift and Shift 20 Million Features with ArcGIS Data Interoperability
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FME Extensive Usage Inside the Mapping Production System of Natural Resources...
Natural Resources Canada (NRCan) uses FME software since 1998. Initially, it was used exclusively as a translation tools. As NRCan gained experience with the FME, it began to integrate it within its cartographic production processes. Today, FME is a centerpiece for validation, integration and dissemination of spatial data from NRCan. This presentation will describe the infrastructure (feature catalog, constraints management, database, etc.) surrounding the use of FME at NRCan and it will also present some interesting validation and spatial data management solutions.
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Informatica course content
We are the best Informatica Training Institute in chennai with placement. Informatica is an ETL tool loading with quality services.
http://www.datawaretools.in/course/informatica-training-in-chennai/
Ten tools for ten big data areas 01 informatica
The document provides an overview of Informatica, a data integration tool, including:
1) Informatica's approach focuses on using a graphical user interface and centralized metadata management to simplify data integration, compared to traditional hand-coding.
2) Key components of Informatica PowerCenter include the Designer tool for building mappings between data sources and targets, and the Workflow Manager for scheduling jobs.
3) Informatica's Big Data Edition extends its ETL capabilities to big data platforms like Hadoop, allowing users to develop and run mappings within a single tool.
Informatica and datawarehouse Material
- A data warehouse is a central repository for an organization's historical data that is used to support management reporting and decision making. It contains data from multiple sources integrated into a consistent structure.
- Data warehouses are optimized for querying and analysis rather than transactions. They use a dimensional model and denormalized structures to improve query performance for business users.
- There are two main approaches to data warehouse design - the dimensional model advocated by Kimball and the normalized model advocated by Inmon. Both have advantages and disadvantages for query performance and ease of use.
Informatica student meterial
Informatica is a software tool designed to simplify Data Warehouse design and routine tasks related to
data transformation and migration i.e ETL -> Extract,transform and Load.
It is a visual interface and you will be dragging and dropping with the mouse in the Designer(client Application).This graphical approach to communicate with all major databases and can move/transform data between them. It can move huge bulk of data in a very effective way.
Informatica comes in different packages:
Informatica PowerCenter license - has all options, including distributed metadata, ability to organize repositories into a data mart domain and share metadata accross repositories.
PowerMart PowerMart - a limited license (all features except distributed metadata and multiple registered servers)Working
Working with Informatica:
Source database(s), target database(s), repository metadatabase
Informatica Server
Client Software: Designer, Server Manager and Repository Manager.
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The common perception of machine learning is that it starts with data and ends with a model. In real-world production systems, the traditional data science and machine learning workflow of data preparation, feature engineering, and model selection, while important, is only one aspect. A critical missing piece is the deployment and management of models, as well as the integration between the model creation and deployment phases.
This is particularly challenging in the case of deploying Apache Spark ML pipelines for low-latency scoring. Because execution of Spark ML pipelines is tightly coupled with the Spark SQL runtime, deployment using Spark is ill-suited to the needs of real-time predictive applications.
In this talk I will introduce the Portable Format for Analytics (PFA) for portable, open, and standardized deployment of data science pipelines and analytic applications. I will also introduce and evaluate Aardpfark, a library for exporting Spark ML pipelines to PFA, as well as compare and contrast it to other available alternatives including PMML, MLeap, ONNX, and Apple’s CoreML.
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Data Science Training in Chennai at Credo Systemz provided by experienced Data Scientists. Our Data Science Course module is completely designed about how to analyze Big Data using R programming and Hadoop. Credo Systemz is the Best place to learn Data Science with Python Training in Chennai. Data Science course certification will help you be a professional Data Scientist. If you really Interested to Learn Best Data Science course in Chennai, then Credo Systemz is the Right place.
Our Best Data Science Training kick starts from statistics and insights of the large volume of data. So that we ranked as Best Data Science Training Institute in Chennai, Velachery. At the end of the course, you become a Data Scientist.
Checkout: http://bit.ly/2Mub6xP
SAS Online Training
The document outlines the course content for a 40 hour SAS Online Training course, which will cover topics such as the SAS programming environment, the SAS language, accessing and manipulating data, generating reports, debugging errors, and an introduction to SAS macros. Students will learn how to read and write data, combine datasets, use conditional logic and loops, and work with SAS procedures to analyze and report on data. Upon completion, students will have gained foundational skills in SAS programming.
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The intention of this research was the integration of a TPC-H on Spark Scala benchmark into ALOJA, an open-source and public platform for automated and cost-efficient benchmarks and to perform an evaluation on the runtime of Spark Scala with or without Hive Metastore compared to Spark SQL. Various alternate file formats with different applied compressions on underlying data and its impact are evaluated. The conducted performance evaluation exposed diverse and captivating outcomes for both benchmarks. Further investigations attempt to detect possible bottlenecks and other irregularities. The aim is to provide an explanation to enhance knowledge of Spark’s engine based on examining the physical plans. Our experiments show, inter alia, that: (1) Spark Scala performs better in case of heavy expression calculation, (2) Spark SQL is the better choice in case of strong data access locality in combination with heavyweight parallel execution. In conclusion, diverse results were observed with the consequence that each API has its advantages and disadvantages.
Surprisingly, our findings are well spread between Spark SQL and Spark Scala and contrary to our expectations Spark Scala did not outperform Spark SQL in all aspects but support the idea that applied optimizations appear to be implemented in a different way by Spark for its core and its extension Spark SQL. The API on top of Spark provides extra information about the underlying structured data, which is probably used to perform additional optimizations.
In conclusion, our research demonstrates that there are differences in the generation of query execution plans that goes hand-in-hand with similar discoveries leading to inefficient joins, and it underlines the importance of our benchmark to identify disparities and bottlenecks.
Speaker
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The document discusses different tools for spatial planners, with a focus on portal solutions for managing and sharing data. It describes the basic components of a portal including: uploading services to allow standardized and non-standardized data formats; updating services to download, upload, and make online and mobile updates to data; data management tools; visualization tools to view internal and external services; and sharing services to allow internal and external access to data and discovery services. Standardized data formats can be directly uploaded while non-standardized formats require transformation models and repositories.
Dan Querimit - BI Portfolio
This document outlines the design of a business intelligence portfolio for All Works Construction Company including a data warehouse, ETL processes, OLAP cube, and reports. The data warehouse will use a snowflake schema design. The ETL processes will load dimension and fact data into a staging area. An OLAP cube will be created using SQL Server Analysis Services with a MOLAP storage mode and partitioning strategy. Reports will be created in SQL Server Reporting Services, Excel Services, and Performance Point and published to SharePoint.
Converting your e resource records to rda-guajardo
Why wait? Convert your e-resource bibliographic records to RDA. Library vendors can help convert your existing catalog records. In-house options are also available. The Library of Congress has updated thousands of authority records to RDA headings. Combine your RDA conversion project with authority control processing to maximize your effort. Some additional steps for the project may include use of ILS global update functions and load table profiles.
Presenter
Richard Guajardo
Head of Resource Discovery Systems, University of Houston
SAS Online Training
Revanth Technologies provides SAS Online training from Hyderabad India with real time experts.
For more details please contact 9290971883, 9247461324 or drop a mail to revanthonlineenquiry@gmail.com
Olap operations
The document discusses OLAP (Online Analytical Processing), which is a data discovery tool that enables multidimensional analysis of data. It describes key features of OLAP like business-focused calculations and consistency of information. The document also defines common OLAP operations like roll-up, drill-down, slicing, dicing and pivoting which allow users to aggregate, navigate and select subsets of data in different dimensions. It concludes by thanking the reader and wishing them a nice day.
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Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
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new_informatica_1
This document provides an overview of the topics that will be covered in an Informatica Power Center 7.x/8.x/9.x training course. The training will cover fundamental concepts like ETL logic, data warehousing, data modeling, and the differences between OLTP and OLAP systems. It will also provide in-depth training on using Informatica Power Center's core components like the Designer, Workflow Manager, Transformations, Mappings, Source Analyzer and Target Designer to develop ETL mappings and workflows. Advanced topics like complex dimension mappings, rapidly changing dimensions, parallel pipelines and debugging/optimizing performance will also be covered.
Lift and Shift 20 Million Features with ArcGIS Data Interoperability
Over three hundred Esri Data Interopability Scripts comprised of over 36,000 transformers and a lot of late nights helped move over 20 million water utility features between 40 databases. As part of a data migration effort within American Water, Magnolia River Services GIS Team leveraged the Data Interoperability Extension to automate complex mapping between legacy and updated water network enterprise databases. The resulting scripts cut the data migration time down to under 20 hours.
cognos_1
This document provides an overview of Cognos 10.2 business intelligence software. It discusses topics such as creating relational and cube models in Framework Manager, building various types of reports in Report Studio like list, cross-tab and chart reports, and administering security and scheduling in Cognos Connection. Advanced concepts covered include using the Model Design Accelerator, Business Insight dashboards, Active Reports, Cube Designer, and integrating Cognos with Microsoft Office.
FME Extensive Usage Inside the Mapping Production System of Natural Resources...
Natural Resources Canada (NRCan) uses FME software since 1998. Initially, it was used exclusively as a translation tools. As NRCan gained experience with the FME, it began to integrate it within its cartographic production processes. Today, FME is a centerpiece for validation, integration and dissemination of spatial data from NRCan. This presentation will describe the infrastructure (feature catalog, constraints management, database, etc.) surrounding the use of FME at NRCan and it will also present some interesting validation and spatial data management solutions.
Informatica course content
This course introduces students to Informatica PowerCenter 9.x through lectures and hands-on exercises. It is designed for database developers new to PowerCenter and covers using tools like Designer, Workflow Manager, and Monitor to create ETL processes involving extractions, transformations, loads and more. The course also covers topics like mappings, transformations, lookups, workflows and parameterization to load and transform data between sources and targets. Students will learn through both conceptual and practical lessons to design and implement ETL solutions with PowerCenter.
Informatica course content
We are the best Informatica Training Institute in chennai with placement. Informatica is an ETL tool loading with quality services.
http://www.datawaretools.in/course/informatica-training-in-chennai/
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Productionizing Spark ML pipelines with the portable format for analytics
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Software tools directly useable for spatial planners
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Lift and Shift 20 Million Features with ArcGIS Data Interoperability
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Ten tools for ten big data areas 01 informatica
The document provides an overview of Informatica, a data integration tool, including:
1) Informatica's approach focuses on using a graphical user interface and centralized metadata management to simplify data integration, compared to traditional hand-coding.
2) Key components of Informatica PowerCenter include the Designer tool for building mappings between data sources and targets, and the Workflow Manager for scheduling jobs.
3) Informatica's Big Data Edition extends its ETL capabilities to big data platforms like Hadoop, allowing users to develop and run mappings within a single tool.
Informatica and datawarehouse Material
- A data warehouse is a central repository for an organization's historical data that is used to support management reporting and decision making. It contains data from multiple sources integrated into a consistent structure.
- Data warehouses are optimized for querying and analysis rather than transactions. They use a dimensional model and denormalized structures to improve query performance for business users.
- There are two main approaches to data warehouse design - the dimensional model advocated by Kimball and the normalized model advocated by Inmon. Both have advantages and disadvantages for query performance and ease of use.
Informatica student meterial
Informatica is a software tool designed to simplify Data Warehouse design and routine tasks related to
data transformation and migration i.e ETL -> Extract,transform and Load.
It is a visual interface and you will be dragging and dropping with the mouse in the Designer(client Application).This graphical approach to communicate with all major databases and can move/transform data between them. It can move huge bulk of data in a very effective way.
Informatica comes in different packages:
Informatica PowerCenter license - has all options, including distributed metadata, ability to organize repositories into a data mart domain and share metadata accross repositories.
PowerMart PowerMart - a limited license (all features except distributed metadata and multiple registered servers)Working
Working with Informatica:
Source database(s), target database(s), repository metadatabase
Informatica Server
Client Software: Designer, Server Manager and Repository Manager.
Management in Informatica Power Center
Informatica provides the market's leading data integration platform. Tested on nearly 500,000 combinations of platforms and applications, the data integration platform inter operates with the broadest possible range of disparate standards, systems, and applications. This unbiased and universal view makes Informatica unique in today's market as a leader in the data integration platform. It also makes Informatica the ideal strategic platform for companies looking to solve data integration issues of any size.
SendGrid Improves Email Delivery with Hybrid Data Warehousing
When you received your Uber ‘Tuesday Evening Ride Receipt’ or Spotify’s ‘This Week’s New Music’ email, did you think about how they got there?
SendGrid’s reliable email platform delivers each month over 20 Billion transactional and marketing emails on behalf of many of your favorite brands, including Uber, Airbnb, Spotify, Foursquare and NextDoor.
SendGrid was looking to evolve its data warehouse architecture in order to improve decision making and optimize customer experience. They needed a scalable and reliable architecture that would allow them to move nimbly and efficiently with a relatively small IT organization, while supporting the needs of both business and technical users at SendGrid.
SendGrid’s Director of Enterprise Data Operations will be joining architects from Amazon Web Services (AWS) and Informatica to discuss SendGrid’s journey to a hybrid cloud architecture and how a hybrid data warehousing solution is optimized to support SendGrid’s analytics initiative. Speakers will also review common technologies and use cases being deployed in hybrid cloud today, common data management challenges in hybrid cloud and best practices for addressing these challenges.
Join us to learn:
• How to evolve to a hybrid data warehouse with Amazon Redshift for scalability, agility and cost efficiency with minimal IT resources
• Hybrid cloud data management use cases
• Best practices for addressing hybrid cloud data management challenges
Informatica Powercenter Architecture
Watch Tutorial On Informatica Powercenter Architecture with video,informatica powercenter architecture diagram,informatica powercenter architecture over view,informatica powercenter architecture 8 diagram,informatica powercenter 9.5 architecture,informatica powercenter architecture ppt
ETL Using Informatica Power Center
This document provides an overview of an Informatica training course offered by Edureka. The course covers topics such as ETL fundamentals, Informatica PowerCenter components, transformations, debugging techniques, and performance tuning. It aims to help students of varying experience levels learn skills for roles like ETL developer, data specialist, and Informatica administrator. The course contains modules on PowerCenter installation, administration, architecture, and best practices, along with hands-on labs and projects. Students will receive a certificate upon completion. More details on the course structure and registration are available on Edureka's website.
Informatica PowerCenter
All about Informatica PowerCenter features for both Business and Technical staff, it illustrates how Informatica PowerCenter solves core business challenges in Data Integration projects.
Red Goldfish - Motivating Sales and Loyalty Through Shared Passion and Purpose
This document summarizes the book "Red Goldfish" which discusses how businesses can motivate sales and loyalty through shared passion and purpose. It outlines how business purpose has evolved from solely focusing on shareholders (Version 1.0) to also prioritizing customers (Version 2.0), employees (Version 3.0), and broader purpose (Version 4.0). The book advocates for "Red Goldfish" - small things companies can do to bring their purpose to life, like programs at Patagonia, Harley Davidson, Apple, Google, Nike, and others. It explores 8 archetypes of Red Goldfish inspired by Maslow's hierarchy of needs.
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SendGrid Improves Email Delivery with Hybrid Data Warehousing
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The document outlines the course content for Informatica Power Center 8.x training which includes 30 hours of online instruction and hands-on labs. Students will learn the fundamentals of PowerCenter including architecture, components, transformations, mappings, workflows and monitoring. The training covers source and target definitions, ETL concepts, debugging, error handling, performance tuning and real-world case studies to provide students with the skills needed to be successful PowerCenter developers.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with various transformations, and best practices for administration, performance tuning, and error handling. The course includes over 30 lab sessions to reinforce lessons on working with sources, targets, mappings, workflows, and other PowerCenter components and functions.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with various transformations, working with workflows and sessions, debugging, and more. The course aims to provide students with the skills needed to become successful PowerCenter developers.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through lectures and hands-on labs. Students will learn about data warehousing concepts, installing and using PowerCenter, transforming and mapping data, debugging workflows, and more. The course includes over 30 lab sessions where students can practice working with PowerCenter.
Informatica
This document provides an overview of the course content for Informatica Power Center 8.x online training. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lessons and hands-on labs. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with transformations like Filter, Joiner, Lookup and Aggregator, and monitoring workflows. The course also covers topics like error handling, performance tuning, reusable objects, and slowly changing dimensions.
INFORMATICA ONLINE TRAINER
This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
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This document provides an overview of the course content for Informatica Power Center 8.x online training. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lessons and hands-on labs. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with transformations like Filter, Joiner, Lookup and Aggregator, and monitoring workflows. The course also covers topics like error handling, performance tuning, reusable objects, and slowly changing dimensions.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lectures and 30 hands-on labs.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
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This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lessons and 30 labs.
Informatica online training from inida
This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with transformations like Filter, Joiner, Lookup and Aggregator, managing workflows, and performing administrative tasks. The goal is for students to gain a solid foundation in PowerCenter development.
Informatica online training from inida
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Informatica online training from inida
This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, designing mappings and workflows, and transforming and loading data. The course covers all the major PowerCenter components, transformations, and features through a combination of lectures and 30 hands-on labs.
Informatica online training from inida
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Informatica online training from inida
This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with transformations like Filter, Joiner, Lookup and Aggregator, managing workflows, and performing administrative tasks. The goal is for students to gain a solid foundation in PowerCenter development.
Informatica online training from inida
This document provides an overview of the content covered in an Informatica PowerCenter 8.x online training course. The 30-hour course teaches students the fundamentals of Informatica PowerCenter through online lectures and hands-on lab exercises. Students will learn about data warehousing concepts, installing and using PowerCenter, developing mappings with transformations like Filter, Joiner, Lookup and Aggregator, managing workflows, and best practices for administration, security and performance tuning.
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unix training | unix training videos | unix course unix online training
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Introduction about Operating System(OS)
Introduction to UNIX
List of UNIX vendors available in Market
Introduction to various UNIX Implementations
History of UNIX OS Evolution from 1969
Open Source (vs.) Shared source (vs.) Closed source
Is Unix Open Source software?
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LINUX OS background
LINUX (vs.) WINDOWS
Popular LINUX distributions/Vendors
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About POSIX standards
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Unix Servers/Dumb terminals/nodes
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UNIX day-to-day used commands:
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This document provides an overview of topics covered in an Oracle Application Express (APEX) online training course. It outlines sections on introducing APEX and its architecture, developing applications using the Application Builder and SQL Workshop, implementing advanced features like forms, reports and security, deploying applications, and using additional tools like plug-ins and team development capabilities. The document lists over 20 individual topics that will be covered in the training spanning the full APEX development lifecycle and environment.
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Oracle ADF Online Training Course Content :
Introduction to Fusion and ADF
Oracle ADF and JDeveloper
Oracle Fusion Middleware
Oracle Fusion Architecture
ADF and MVC
More about ADF
Exploring Jdeveloper
JDeveloper 11g New Features
Building ADF Application in JDeveloper
Configuring JDeveloper Preferences
Database Schema Design
JDeveloper 11g New Features
Database Designing Tools in JDeveloper
Creating Offline Objects
Synchronize Online-Offline Database
Data Modeling with ADF Business Components
Advantages of ADF BC
ADF BC Categories
Creating ADF Business Components
Business Component Browser
Entity Objects and Associations
Data Persistence using Entity Objects
Creating Entity Objects
Modify Entity Object Default Behavior
Associations
View Objects and View Links
Populating Data in View Objects
Creating View Objects
Modify View Object Default Behavior
View Links
Creating View Criteria
Creating List of Values
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Website : http://www.todaycourses.com
C# Online Training Concepts :
Introduction to Web Controls
Thinking about .NET
Using Visual Studio 2005
Debugging and Handling Exceptions
Data Types and Variables
Introducing Variables and Data Types
Working with Variables and Data Types
Using the .NET Framework
Using .NET Framework Classes
Working with Strings
Working with Dates and Times
Branching and Flow Control
Branching in Code
Repeating Code Blocks
Unconditional Branching
Classes and Objects
Introducing Objects and Classes
Creating Your Own Classes
Working with Classes
Properties and Methods
Overview of Properties and Methods
Working with Properties
Working with Methods
Object-Oriented Techniques
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Website : http://www.todaycourses.com
ASP .NET Online Training Concepts :
Introduction
A Review of Classic ASP
ASP.NET Web Applications
Rendering HTML with Server Controls
Data Binding in ASP.NET
Web Development Using Visual Studio
Working with Controls
Introduction to Web Controls
Simple Input Controls
HyperLink and Button Controls
List Controls
Controlling Focus
Accessing Data
Overview of ADO.NET
Connecting to Data
Executing Commands
Working with Data
Choosing an ADO.NET Provider
LINQ
Language Integrated Query
LINQ Syntax
LINQ to SQL
LINQ to DataSets
LINQ to XML
Configuration
Configuration Overview
Using the Web Site Administration Tool
Programming Configuration Files
Encrypting Configuration Sections
Data Binding
Introducing Data Source Controls
Reading and Write Data Using the Sql Data Source Control
Displaying and Editing Middle-Tier Data using the Object Data Source Control
Displaying XML Data Using the Xml Data Source Control
Validating User Input
Overview of ASP.NET Validation Controls
Using the Simple Validators
Using the Complex Validators
Summarizing Results with the Validation Summary Control
Separating Validation into Validation Groups
Css
Introducing Cascading Style Sheets
Investigating Styles
Using Visual Studio 2008's Tools for Working with Styles
Themes and Master Pages
Creating a Consistent Web Site
ASP.NET 2.0 Themes
Master Pages
Site Navigation
ASP.NET Web Site Navigation
Creating an XML Site Map File
Site Navigation Controls
Using the Site Navigation API
URL Mapping
Security Trimming
Displaying Data with the GridView Control
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.net training | learn .net | Microsoft dot net Course | Microsoft dot net onl...
Website : http://www.todaycourses.com
.Net Online Training Concepts :
NET FUNDAMENTALS
Why .NET?
The .NET initiative
Introduction to .NET framework
Advantages of .NET framework
System requirements
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Why .NET?
The .NET initiative
Introduction to .NET framework
Advantages of .NET framework
System requirements
INTRODUCTION TO VISUAL STUDIO .NET
Base class libraries
Common language-runtime (CLR)
Microsoft intermediate language (MSIL)
Optimized just-in-time (JIT)
Common type systems (CTS)
Common language specification (CLS)
Compilation and execution of .NET application
Assemblies
Namespace
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unix training | unix training videos | unix course unix online training
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oracle adf training | oracle adf course | oracle adf certification training
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c# training | c# training videos | c# object oriented programming | c# course
asp .net training | asp.net course | asp.net training online | learn asp.net
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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- 2. Introduction to Dataware housing SCD1, SCD2, SCD3 Metadata Dimentinal Table Types Of Dim Tables Fact Table Types of Fact Tables OLTP (OnLine Transaction Processing) OLAP (Online Analysis And Processing) OLTP Vs OLAP Contents 1 Contents 2 CONTENTS
- 3. Advantages of OLAP Different Methodologies of DWH PowerCenter Components and User Interface Dimentinal Table Types Of Dim Tables Source Qualifier Expression, Filter File Lists and Workflow Scheduler OLAP (Online Analysis And Processing) Joins, Features and Techniques I Contents 3 Contents 4 CONTENTS
- 4. Lookups and Reusable Transformations Debugger Sequence Generator Sequence Generator Lookup Caching Router, update Strategy and Overrides Dynamic Lookup and Error Logging Unconnected Lookup, Parameters and Variables Sorter, Aggregator and Self-Join Mapplets I Contents 5 Contents 6 CONTENTS
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- 16. Dynamic Lookup and Error Logging • Dynamic Lookup • Error Logging • Lab – Load Customer Dimension Table
- 17. Unconnected Lookup, Parameters and Variables • Unconnected Lookup Transformation • System Variables • Mapping Parameters and Variables • Lab – Load Sales Fact Table
- 18. Sorter, Aggregator and Self- Join • Sorter Transformation • Aggregator Transformation • Active and Passive Transformations • Data Concatenation • Self-Join • Lab – Reload the Employee Staging Table and Real time issues • SCD type1 – Hands-On LAB • SCD type2 – Hands-On LAB • SCD type3 – Hands-On LAB
- 19. Mapplets • Mapplets • Lab – Load Product Daily Aggregate Table • Review and more Lab Activities and Real time issues
- 20. Workflow Variables and Tasks • Link Conditions • Workflow Variables • Assignment Task • Decision Task • Email Task • Lab – Load Product Weekly Aggregate Table
- 21. More Tasks and Reusability • Event Raise Task • Event Wait Task • Command Task • Reusable Tasks • Reusable Session Task • Reusable Session Configuration
- 22. Worklets and More Tasks • Worklets • Timer Task • Control Task