Informatica Tutorial For Beginners | Informatica Powercenter Tutorial | EdurekaEdureka!
This Edureka Informatica Tutorial helps you understand Informatica PowerCenter in detail. This Informatica tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Informatica concepts. Below are the topics covered in this tutorial:
1. What Is Informatica?
2. Informatica Products and Functionalities
3. Informatica Architecture Overview and Components
4. Domain and Nodes
5. Informatica Services
6. Overview of ETL
7. Component Based Development
Informatica Transformations with Examples | Informatica Tutorial | Informatic...Edureka!
This Edureka Informatica Transformations tutorial will help you in understanding the various transformations in Informatica with examples. Firstly, you will understand why we need transformations and what is a transformation. Then this tutorial talks about 5 commonly used transformations with different examples. Below are the topics covered in this tutorial:
1. Why do we need Transformation?
2. What is Transformation?
3. Types of Transformation in Informatica
4. Commonly used Transformation in Informatica
5. Source Qualifier Transformation
6. Joiner Transformation
7. Union Transformation
8. Expression Transformation
9. Normalizer Transformation
Informatica products and usage, informatica developer,informatica analyst,informatica powerexchange,informatica powercenter,informatica data quality,master data management,data masking,data visualization,informatica products list
Informatica PowerCenter Tutorial | Informatica Tutorial for Beginners | EdurekaEdureka!
This Edureka Informatica PowerCenter Tutorial will help you in understanding the various components of Informatica PowerCenter in detail with examples. You will be given a detailed understanding of each client and administrator tool. You will also understand the role of these tools in various phases to solve a use case. Below are the topics covered in this tutorial:
1. Informatica PowerCenter Overview
2. Why Do We Need Data Integration?
3. ETL Process
4. Informatica PowerCenter Administrator Console.
5. Informatica PowerCenter Repository Manager.
6. Informatica PowerCenter Designer
7. Informatica PowerCenter Workflow Manager
8. Informatica PowerCenter Workflow Monitor
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.
All about Informatica PowerCenter features for both Business and Technical staff, it illustrates how Informatica PowerCenter solves core business challenges in Data Integration projects.
Informatica Tutorial For Beginners | Informatica Powercenter Tutorial | EdurekaEdureka!
This Edureka Informatica Tutorial helps you understand Informatica PowerCenter in detail. This Informatica tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Informatica concepts. Below are the topics covered in this tutorial:
1. What Is Informatica?
2. Informatica Products and Functionalities
3. Informatica Architecture Overview and Components
4. Domain and Nodes
5. Informatica Services
6. Overview of ETL
7. Component Based Development
Informatica Transformations with Examples | Informatica Tutorial | Informatic...Edureka!
This Edureka Informatica Transformations tutorial will help you in understanding the various transformations in Informatica with examples. Firstly, you will understand why we need transformations and what is a transformation. Then this tutorial talks about 5 commonly used transformations with different examples. Below are the topics covered in this tutorial:
1. Why do we need Transformation?
2. What is Transformation?
3. Types of Transformation in Informatica
4. Commonly used Transformation in Informatica
5. Source Qualifier Transformation
6. Joiner Transformation
7. Union Transformation
8. Expression Transformation
9. Normalizer Transformation
Informatica products and usage, informatica developer,informatica analyst,informatica powerexchange,informatica powercenter,informatica data quality,master data management,data masking,data visualization,informatica products list
Informatica PowerCenter Tutorial | Informatica Tutorial for Beginners | EdurekaEdureka!
This Edureka Informatica PowerCenter Tutorial will help you in understanding the various components of Informatica PowerCenter in detail with examples. You will be given a detailed understanding of each client and administrator tool. You will also understand the role of these tools in various phases to solve a use case. Below are the topics covered in this tutorial:
1. Informatica PowerCenter Overview
2. Why Do We Need Data Integration?
3. ETL Process
4. Informatica PowerCenter Administrator Console.
5. Informatica PowerCenter Repository Manager.
6. Informatica PowerCenter Designer
7. Informatica PowerCenter Workflow Manager
8. Informatica PowerCenter Workflow Monitor
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.
All about Informatica PowerCenter features for both Business and Technical staff, it illustrates how Informatica PowerCenter solves core business challenges in Data Integration projects.
This slides presents the architecture of the Informatica PowerCenter and each of its component.
This can help ETL PowerCenter developers understand how their mapping works internally and it's an introduction to the Informatica Administration.
Informatica has become a market leader in ETL because of its wide usage. Live interactive and best in industry Informatica Online Training is provided at IQ Online Training. For a FREE LIVE demo, register at IQ OnlineTraining.
Learn What is inforamatica powercenter and its uses, Informatica powercenter designer,informatica powercenter repository, oltp system informatica,olap system informatica,informatica powercenter etl processing
Informatica Training | Informatica PowerCenter | Informatica Tutorial | EdurekaEdureka!
This Edureka Informatica Training tutorial will help you in understanding the various components of Informatica PowerCenter in detail with examples. You will be given a detailed understanding of Informatica PowerCenter architecture and ETL process. You will also understand the role of these tools in various phases to solve a use case. Below are the topics covered in this tutorial:
1) Informatica PowerCenter Overview
2) Informatica Architecture overview
3) ETL Process
4) Informatica PowerCenter Designer
5) Informatica PowerCenter Workflow Manger
6) Informatica PowerCenter Workflow Monitor
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.
Power BI Consultants | Power BI Solutions | Power BI ServiceAdmin iLink
Power BI is a suite of business analytics tools to analyze data & share insights. Get expert guidance from these certified Power BI consultants & partners.
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.
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI T...Edureka!
This Edureka SSIS Tutorial will help you learn the basics of MSBI. SSIS is a platform for data integration and workflow applications. This tutorial covers data warehousing concepts which is used for data extraction, transformation and loading (ETL). It is ideal for both beginners and professionals who want to brush up their basics of MSBI. Below are the topics covered in this tutorial:
1. Why do we need data integration?
2. What is data integration?
3. Why SSIS?
4. What is SSIS?
5. ETL process
6. Data Warehousing
7. Installation
8. What is SSIS Package?
This presentation explains what data engineering is and describes the data lifecycles phases briefly. I used this presentation during my work as an on-demand instructor at Nooreed.com
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Data Warehouse or Data Lake, Which Do I Choose?DATAVERSITY
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.
In this webinar, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how some real world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.
Building the Data Lake with Azure Data Factory and Data Lake AnalyticsKhalid Salama
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
Talend ETL Tutorial | Talend Tutorial For Beginners | Talend Online Training ...Edureka!
( Talend Training: https://www.edureka.co/talend-for-big... ) This Edureka PPT on Talend ETL Tutorial [Talend ETL Tutorial Blog: https://goo.gl/myMwuQ] will help you in understanding the basic concepts of ETL (Extract, Transform & Load) process and how Talend helps in simplifying the entire ETL process by integrating them into a single Job. This video helps you to learn following topics: Why ETL? What Is ETL? ETL Tools Talend As An ETL Tool Demo
Informatica power center performance tuningdivjeev
For more details visit http://free-informatica-tutorials.blogspot.com
Informatica power center performance tuning.Version 8.6.1
This presentation is a property of INFORMATICA
This slides presents the architecture of the Informatica PowerCenter and each of its component.
This can help ETL PowerCenter developers understand how their mapping works internally and it's an introduction to the Informatica Administration.
Informatica has become a market leader in ETL because of its wide usage. Live interactive and best in industry Informatica Online Training is provided at IQ Online Training. For a FREE LIVE demo, register at IQ OnlineTraining.
Learn What is inforamatica powercenter and its uses, Informatica powercenter designer,informatica powercenter repository, oltp system informatica,olap system informatica,informatica powercenter etl processing
Informatica Training | Informatica PowerCenter | Informatica Tutorial | EdurekaEdureka!
This Edureka Informatica Training tutorial will help you in understanding the various components of Informatica PowerCenter in detail with examples. You will be given a detailed understanding of Informatica PowerCenter architecture and ETL process. You will also understand the role of these tools in various phases to solve a use case. Below are the topics covered in this tutorial:
1) Informatica PowerCenter Overview
2) Informatica Architecture overview
3) ETL Process
4) Informatica PowerCenter Designer
5) Informatica PowerCenter Workflow Manger
6) Informatica PowerCenter Workflow Monitor
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.
Power BI Consultants | Power BI Solutions | Power BI ServiceAdmin iLink
Power BI is a suite of business analytics tools to analyze data & share insights. Get expert guidance from these certified Power BI consultants & partners.
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.
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI T...Edureka!
This Edureka SSIS Tutorial will help you learn the basics of MSBI. SSIS is a platform for data integration and workflow applications. This tutorial covers data warehousing concepts which is used for data extraction, transformation and loading (ETL). It is ideal for both beginners and professionals who want to brush up their basics of MSBI. Below are the topics covered in this tutorial:
1. Why do we need data integration?
2. What is data integration?
3. Why SSIS?
4. What is SSIS?
5. ETL process
6. Data Warehousing
7. Installation
8. What is SSIS Package?
This presentation explains what data engineering is and describes the data lifecycles phases briefly. I used this presentation during my work as an on-demand instructor at Nooreed.com
50-55 hours Training + Assignments + Actual Project Based Case Studies
All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Data Warehouse or Data Lake, Which Do I Choose?DATAVERSITY
Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.
Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.
In this webinar, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how some real world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.
Building the Data Lake with Azure Data Factory and Data Lake AnalyticsKhalid Salama
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
Talend ETL Tutorial | Talend Tutorial For Beginners | Talend Online Training ...Edureka!
( Talend Training: https://www.edureka.co/talend-for-big... ) This Edureka PPT on Talend ETL Tutorial [Talend ETL Tutorial Blog: https://goo.gl/myMwuQ] will help you in understanding the basic concepts of ETL (Extract, Transform & Load) process and how Talend helps in simplifying the entire ETL process by integrating them into a single Job. This video helps you to learn following topics: Why ETL? What Is ETL? ETL Tools Talend As An ETL Tool Demo
Informatica power center performance tuningdivjeev
For more details visit http://free-informatica-tutorials.blogspot.com
Informatica power center performance tuning.Version 8.6.1
This presentation is a property of INFORMATICA
BISP is committed to provide BEST learning material to the beginners
and advance learners. In the same series, we have prepared a complete
end-to end Hands-on Guide for building financial data model in
Informatica. The document focuses on how the real world requirement
should be interpreted. The mapping document template with very
simplified steps and screen shots makes the complete learning so easy.
The document focuses This document contains step by step process for
conditional lookup transformation (Unconnected lookup) in Informatica Power
Center 9.0.1. Join our professional training program and learn from
experts.
History:
Are you a young professional who just got out of college and unsure which career path to follow? Are you thinking about changing your career to something completely new and looking for options? Either way, this webinar is the right one for you. It’s the first in a series that the new ODTUG Career Track Community will bring you to show what Oracle careers look like and where/how to start with them.
During this webinar, we will talk about what an ETL developer career looks like, what the expectations are, challenges, rewards, and which steps are needed to be successful. We will discuss a wide range of topics, such as tools used on the job, certification paths, the importance of social media, user groups, and more. This webinar will be presented by Rodrigo Radtke de Souza, who has been working in the Oracle ETL world for quite some time now and has achieved great accomplishments as an ETL developer, such as Oracle ACE nomination, frequent Kscope speaker, ODTUG Leadership Program participant, and a successful career at Dell.
In a fast-moving business environment, finance leaders are successfully leveraging technology advancements to transform their finance organizations and generate value for the business.
Oracle’s Enterprise Performance Management (EPM) applications are an integrated, modular suite that supports a broad range of strategic and financial performance management tools that help business to unlock their potential.
Dell’s global financial environment contains over 10,000 users around the world and relies on a range of EPM tools such as Hyperion Planning, Essbase, Smart View, DRM, and ODI to meet its needs.
This session shows the complexity of this environment, describing all relationships between those tools, the techniques used to maintain such a large environment in sync, and meeting the most varied needs from the different business and laws around the world to create a complete and powerful business decision engine that takes Dell to the next level.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
Delta Lake, an open-source innovations which brings new capabilities for transactions, version control and indexing your data lakes. We uncover how Delta Lake benefits and why it matters to you. Through this session, we showcase some of its benefits and how they can improve your modern data engineering pipelines. Delta lake provides snapshot isolation which helps concurrent read/write operations and enables efficient insert, update, deletes, and rollback capabilities. It allows background file optimization through compaction and z-order partitioning achieving better performance improvements. In this presentation, we will learn the Delta Lake benefits and how it solves common data lake challenges, and most importantly new Delta Time Travel capability.
Informatica Online Training By Keylabstraining.com with Real time and certified consultants. In this Informatica Training we will teach you basic Data base training and also we will cover some Unix concepts . And also we can provide you Video recordings.
Contact: info@keylabstraining.com , +91- 9550645679(IND) , +1-908-366-7933( USA).
Overview of PowerAnalyzer 4.0
Schema definition - Analytics Design
Creating a Report
Working with Report Data
Working with the Dashboards
Administrating PowerAnalyzer
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
173. INFORMATICA POWERCENTER 7.1 ENHANCEMENTS This Presentation part describes new features and enhancements to Informatica PowerCenter version 7.0. forming Informatica PowerCenter version 7.1
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Editor's Notes
Global repository. The global repository is the hub of the domain. Use the global repository to store common objects that multiple developers can use through shortcuts. These objects may include operational or application source definitions, reusable transformations, mapplets, and mappings. Local repositories. A local repository is within a domain that is not the global repository. Use local repositories for development. From a local repository, you can create shortcuts to objects in shared folders in the global repository. These objects typically include source definitions, common dimensions and lookups, and enterprise standard transformations. You can also create copies of objects in non-shared folders.
Global repository. The global repository is the hub of the domain. Use the global repository to store common objects that multiple developers can use through shortcuts. These objects may include operational or application source definitions, reusable transformations, mapplets, and mappings. Local repositories. A local repository is within a domain that is not the global repository. Use local repositories for development. From a local repository, you can create shortcuts to objects in shared folders in the global repository. These objects typically include source definitions, common dimensions and lookups, and enterprise standard transformations. You can also create copies of objects in non-shared folders.
The Figure shows the processing path between the Informatica Server, repository, source, and target
The Informatica Server can combine data from different platforms and source types. For example, you can join data from a flat file and an Oracle source, and write the transformed data to a Microsoft SQL Server database. When a session starts, the Informatica Server retrieves mapping and session metadata from the repository to extract data from the source, transform it, and load it into the target. The Informatica Server can combine data from different platforms and source types
The Informatica Server can combine data from different platforms and source types. For example, you can join data from a flat file and an Oracle source, and write the transformed data to a Microsoft SQL Server database. When a session starts, the Informatica Server retrieves mapping and session metadata from the repository to extract data from the source, transform it, and load it into the target. The Informatica Server can combine data from different platforms and source types
The Load Manager is the primary Informatica Server process
The Load Manager holds the connection to the repository for the value set in the Informatica Server configuration, LMStayConnectToRepositDuration When you start the Informatica Server. When you start the Informatica Server, the Load Manager launches and queries the repository for a list of sessions configured to run on the Informatica Server. When you configure a session. When you add, update, or schedule a session in the Server Manager, the repository stores all the session metadata. The Load Manager maintains a list of sessions and session start times. When a session starts. When a session starts, the Load Manager fetches the session information from the repository to perform the validations and verifications prior to starting the DTM process. The execute lock allows the Informatica Server to run the session and prevents you from starting the session again until it completes. If the session is already locked, the Informatica Server cannot start the session. A session may be locked if it is already running, or if an error occurred during the previous run that prevented the repository from releasing the execute lock.
Four transformation threads. The DTM creates one transformation thread for each partition. The DTM creates an additional transformation thread for partition for each Aggregator or Rank transformation. So, the DTM creates four transformation threads to process the mapping in Figure above.
Standalone repository. A repository that functions individually, unrelated and unconnected to other repositories. Global repository. (PowerCenter only.) The centralized repository in a domain, a group of connected repositories. Each domain can contain one global repository. The global repository can contain common objects to be shared throughout the domain through global shortcuts. Once created, you cannot change a global repository to a local repository. You can promote an existing local repository to a global repository. Local repository. (PowerCenter only.) A repository within a domain that is not the global repository. Each local repository in the domain can connect to the global repository and use objects in its shared folders. A folder in a local repository can be copied to other local repositories while keeping all local and global shortcuts intact.
When restoring a repository, you must have a database available for the repository. You can restore the repository in a database that has a different code page from the original database, if the code pages are compatible. If a repository already exists at the location, the Repository Manager asks you to delete the repository before restoring a backup repository. If no repository exists, the Repository Manager creates a repository before restoring the backup repository.
Source and target dependencies report (S2t_dep.rpt) - Shows the source and target dependencies as well as the transformations performed in each mapping
Write lock - Created when you create or edit a repository object in a folder for which you have write permission Execute lock - Created when you start a session or batch, or when the Informatica Server starts a scheduled session or batch Save lock - Created when you save information to the repository The repository permits multiple read locks, one write lock, and one execute lock simultaneously on each repository object. This means that one user can edit a session while the Informatica Server runs the session, and another user can view the session properties at the same time. You can view existing locks in the repository in the Repository Manager. The Repository Manager provides two ways to view locks: Browse the repository. Use the Navigator and main windows to display the folders, versions, and objects in use. Show locks. Use a menu command to view all locks in the repository. This method provides more detailed information and allows you to sort your view of the locks.
You must create a folder in a new repository before you can connect to the repository using the Designer or Workflow Manager. You can copy objects from one folder to another, so if you want to use an object in a non-shared folder, you can copy it into your working folder. If you work with multiple repositories, you can also copy objects across repositories. You can continue working in the new version, while preserving the older version. You might use versions to archive work while continuing with development.
In your repository, you might create folders for each data warehouse development project, subject area, user, or type of metadata. If you can divide the data warehouse into different types of information, you might create a single folder for each type of data. For instance, when you set up the accounting data warehouse, you might create one folder for accounts payable and another for accounts receivable. You can create a folder for each repository user, designed to store work for that user only. If users work on separate projects, this technique avoids any problems that might occur if two people attempt to edit the same piece of metadata at the same time. You might create a different folder for each type of metadata (source definitions, target definitions, mappings, schemas, and reusable transformations) that you create through the Designer.
When you copy a folder from a global repository to a local repository in the same domain, the Repository Manager verifies whether a folder of the same name exists in the global repository. If it does not, the Repository Manager uses the folder name for the copied folder. If it does, the Repository Manager asks you to rename the folder. The Repository Manager preserves shortcuts to shared folders in the global repository, changing the local shortcuts to global shortcuts. When you copy both a shared folder and a non-shared folder with dependent shortcuts across repositories and then recopy the shared folder from the source repository, the shortcuts in the non-shared folder in the target repository point to the folder in the source repository. The shortcuts in the non-shared folder always point to the folder you select when you copy/replace a shared folder.
Re-establish shortcuts. Maintain shortcuts to objects in shared folders. If the Repository Manager cannot re-establish shortcuts, it marks the affected mappings, mapplets, and sessions invalid in the repository and lists them in the Output window. Choose an Informatica Server. Use the Informatica Server to run all sessions and batches in the folder if a matching Server does not exist in the target repository. Copy connections. Copy database, FTP, and external loader connection information if matching connection names do not exist in the target repository. Copy persisted values. Copy the saved persisted values for mapping variables used in a session. Compare folders. Compare folders to determine how they are related with the compare folders functionality. Replace folders. Replace an existing folder, including all objects associated with the folder. The Repository Manager copies and replaces folders as a single transaction. If you cancel the copy before it completes, the Repository Manager rolls back all changes.
Versions to compare. The wizard automatically selects pairs of versions with the same version number in each folder for comparison. You can also specify the versions to compare in each folder. Object types to compare. You can specify the object types to compare and display between folders. The Repository Manager compares objects based upon specific object attributes. See Table 6-3 for a list of compared attributes for object types. Direction of comparison. The Repository Manager performs directional comparisons. A directional comparison checks the contents of one folder against the contents of the other. You can specify either one-way or two-way comparisons.
Figure shows two folders in the same repository, Orders1 and Orders2. If you compare the folders using a one-way comparison, the source definition ORDER_ITEMS, present in Orders2 but not in Orders1, is not noted as a comparison. If you compare the folders using a two-way comparison, the absence of ORDER_ITEMS in Orders1 is noted as a difference.
Because sessions and batches are not associated with version numbers, the version pairs specified in the Versions to compare list do not impact a comparison of sessions or batches. If you want to compare only sessions and batches, you can accept the default version pairs without affecting the outcome of the comparison. The Repository Manager does not compare the field attributes of the objects in the folders when performing the comparison. For example, if two folders that have matching source names and column or port names but differing port or column attributes, such as precision or datatype, the Repository Manager does not note these as different.
Can delete a folder version to remove unnecessary versions from the repository By archiving the contents of a folder into a version each time you reach a development landmark, you can access those versions if later edits prove unsuccessful. For example, you can create a folder version after completing a version of a difficult mapping, then continue working on the mapping. If you are unhappy with the results of subsequent work, you can revert to the previous version, then create a new version to continue development. Thus you keep the landmark version intact, but available for regression. When working with multiple versions, make sure you have the appropriate version active. The repository saves version information by workspace, so if someone else uses your machine and changes the active version, that version remains active on your machine until changed
Exporting and importing an object is similar to copying an object from one folder or repository to another folder or repository. When you copy objects between folders or repositories, you must be connected to both repositories simultaneously. However, when you export an object from one repository and import the object into another repository, you do not need to connect to both repositories simultaneously. You might want to export an object in any of the following circumstances: You want to copy an object between two repositories, but you cannot connect to both repositories from the same client. Export the object and electronically transfer the XML file to the target machine. Then import the object from the XML file into the target repository. You previously copied a mapping or mapplet that uses a reusable transformation to another repository. Then later you changed the reusable transformation. Instead of copying the entire mapping or mapplet again, you can export and import the reusable transformation. You want to export an object from your development repository and deploy it in the production repository. You have an invalid session that you need to troubleshoot. Export the invalid session and its associated mapping, electronically transfer the XML file to someone else for troubleshooting.
To import a source definition: In the Source Analyzer, choose Sources-Import from Database. Select the ODBC data source used to connect to the source database. If you need to create or modify an ODBC data source, click the Browse button to open the ODBC Administrator. Create the appropriate data source and click OK. Select the new ODBC data source. Enter a database username and password to connect to the database. Note: The username must have the appropriate database permissions to view the object. You may need to specify the owner name for database objects you want to use as sources. Click Connect. If no table names appear or if the table you want to import does not appear, click All. Drill down through the list of sources to find the source you want to import. Select the relational object or objects you want to import. You can hold down the Shift key to select blocks of record sources within one folder, or hold down the Ctrl key to make non-consecutive selections within a folder. You can also select all tables within a folder by selecting the folder and clicking the Select All button. Use the Select None button to clear all highlighted selections.
When you create a flat file source definition, you must define the properties of the file. The Source Analyzer provides a Flat File Wizard to prompt you for the above mentioned file properties. You can import fixed-width and delimited flat file source definitions that do not contain binary data. When importing the definition, the source file must be in a directory local to the client machine. In addition, the Informatica Server must be able to access all source files during the session.
You can create the overall relationship, called a schema , as well as the target definitions, through wizards in the Designer. The Cubes and Dimensions Wizards follow common principles of data warehouse design to simplify the process of designing related targets.
Connectors - Connect sources, targets, and transformations so the Informatica Server can move the data as it transforms it A mapplet is a set of transformations that you build in the Mapplet Designer and can use in multiple mappings
When you edit and save a mapping, some changes cause the session to be invalid even though the mapping remains valid. The Informatica Server does not run invalid sessions
The Designer marks a mapping invalid when it detects errors that will prevent the Informatica Server from executing the mapping The Designer performs connection validation each time you connect ports in a mapping and each time you validate or save a mapping. At least one mapplet input port and output port is connected to the mapping. If the mapplet includes a Source Qualifier that uses a SQL override, the Designer prompts you to connect all mapplet output ports to the mapping. You can validate an expression in a transformation while you are developing a mapping. If you did not correct the errors, the Designer writes the error messages in the Output window when you save or validate the mapping. When you validate or save a mapping, the Designer verifies that the definitions of the independent objects, such as sources or mapplets, match the instance in the mapping. If any of the objects change while you configure the mapping, the mapping might contain errors.
Example of an active transformation is a Filter transformation that removes rows that do not meet the configured filter condition. Example of a passive transformation is an an Expression transformation that performs a calculation on data and passes all rows through the transformation An unconnected transformation is not connected to other transformations in the mapping. It is called within another transformation, and returns a value to that transformation.
The Informatica Server performs aggregate calculations as it reads, and stores necessary data group and row data in an aggregate cache Aggregate expression - Entered in an output port, can include non-aggregate expressions and conditional clauses Group by port - Indicates how to create groups. can be any input, input/output, output, or variable port Sorted Input option - Use to improve session performance. To use Sorted Input, you must pass data to the Aggregator transformation sorted by group by port, in ascending or descending order Aggregate cache - Aggregator stores data in the aggregate cache until it completes aggregate calculations. It stores group values in an index cache and row data in data cache
You can enter multiple expressions in a single Expression transformation. As long as you enter only one expression for each output port, you can create any number of output ports in the transformation. In this way, you can use one Expression transformation rather than creating separate transformations for each calculation that requires the same set of data.
As an active transformation, the Filter transformation may change the number of rows passed through it. A filter condition returns TRUE or FALSE for each row that passes through the transformation, depending on whether a row meets the specified condition. Only rows that return TRUE pass through this transformation. Discarded rows do not appear in the session log or reject files. To maximize session performance, include the Filter transformation as close to the sources in the mapping as possible. Rather than passing rows you plan to discard through the mapping, you then filter out unwanted data early in the flow of data from sources to targets. You cannot concatenate ports from more than one transformation into the Filter transformation. The input ports for the filter must come from a single transformation. The Filter transformation does not allow setting output default values.
Allows to join sources that contain binary data To join more than two sources in a mapping, add additional Joiner transformations An input transformation is any transformation connected to the input ports of the current transformation. Specify one of the sources as the master source, and the other as the detail source. This is specified on the Properties tab in the transformation by clicking the M column. When you add the ports of a transformation to a Joiner transformation, the ports from the first source are automatically set as detail sources. Adding the ports from the second transformation automatically sets them as master sources. The master/detail relation determines how the join treats data from those sources based on the type of join. For example, you might want to join a flat file with in-house customer IDs and a relational database table that contains user-defined customer IDs. You could import the flat file into a temporary database table, then perform the join in the database. However, if you use the Joiner transformation, there is no need to import or create temporary tables.
Can configure the lookup transformation to be connected or unconnected, cached or uncached
Connected and unconnected transformations receive input and send output in different ways. Sometimes you can improve session performance by caching the lookup table. If you cache the lookup table, you can choose to use a dynamic or static cache. By default, the lookup cache remains static and does not change during the session. With a dynamic cache, the Informatica Server inserts rows into the cache during the session. Informatica recommends that you cache the target table as the lookup. This enables you to look up values in the target and insert them if they do not exist.
NewLookupRow. The Designer automatically adds this port to a Lookup transformation configured to use a dynamic cache. Indicates whether or not the row is in lookup cache. To keep the lookup cache and the target table synchronized, you want to pass rows to the target when the NewLookupRow value is equal to 1. Associated Port. Associate lookup ports with either an input/output port or a sequence ID. The Informatica Server uses the data specified in the associated ports to insert into the lookup cache when it does not find a row in the lookup cache. If you associate a sequence ID, the Informatica Server generates a primary key for the inserted row in the lookup cache.
The Informatica Server builds the cache when it processes the first request lookup request. It queries the cache based on the lookup condition for each row that passes into the transformation. When the Informatica Server receives a new row (a row that is not in the cache), it inserts the row into the cache. You can configure the transformation to insert rows into the cache based on input ports or generated sequence IDs. The Informatica Server flags the row as new. When the Informatica Server receives an existing row (a row that is in the cache), it flags the row as existing. The Informatica Server does not insert the row into the cache. Use a Router or Filter transformation with the dynamic Lookup transformation to route new rows to the cached target table. You can route existing rows to another target table, or you can drop them. When you partition a source that uses a dynamic lookup cache, the Informatica Server creates one memory cache and one disk cache for each transformation.
The Router transformation is more efficient when you design a mapping and when you run a session For example, to test data based on three conditions, you only need one Router transformation instead of three filter transformations to perform this task. Likewise, when you use a Router transformation in a mapping, the Informatica Server processes the incoming data only once. When you use multiple Filter transformations in a mapping, the Informatica Server processes the incoming data for each transformation
The Informatica Server generates a value each time a row enters a connected transformation, even if that value is not used. When NEXTVAL is connected to the input port of another transformation, the Informatica Server generates a sequence of numbers. When CURRVAL is connected to the input port of another transformation, the Informatica Server generates the NEXTVAL value plus one.
Connect NEXTVAL to multiple transformations to generate unique values for each row in each transformation. For example, you might connect NEXTVAL to two target tables in a mapping to generate unique primary key values. The Informatica Server creates a column of unique primary key values for each target table. If you want the same generated value to go to more than one target that receives data from a single preceding transformation, you can connect a Sequence Generator to that preceding transformation. This allows the Informatica Server to pass unique values to the transformation, then route rows from the transformation to targets.
The Source Qualifier displays the transformation datatypes. The transformation datatypes in the Source Qualifier determine how the source database binds data when you import it. Do not alter the datatypes in the Source Qualifier. If the datatypes in the source definition and Source Qualifier do not match, the Designer marks the mapping invalid when you save it.
In the mapping shown above, although there are many columns in the source definition, only three columns are connected to another transformation. In this case, the Informatica Server generates a default query that selects only those three columns: SELECT CUSTOMERS.CUSTOMER_ID, CUSTOMERS.COMPANY, CUSTOMERS.FIRST_NAME FROM CUSTOMERS When generating the default query, the Designer delimits table and field names containing the slash character (/) with double quotes.
In the mapping shown above, although there are many columns in the source definition, only three columns are connected to another transformation. In this case, the Informatica Server generates a default query that selects only those three columns: SELECT CUSTOMERS.CUSTOMER_ID, CUSTOMERS.COMPANY, CUSTOMERS.FIRST_NAME FROM CUSTOMERS When generating the default query, the Designer delimits table and field names containing the slash character (/) with double quotes.
In the mapping shown above, although there are many columns in the source definition, only three columns are connected to another transformation. In this case, the Informatica Server generates a default query that selects only those three columns: SELECT CUSTOMERS.CUSTOMER_ID, CUSTOMERS.COMPANY, CUSTOMERS.FIRST_NAME FROM CUSTOMERS When generating the default query, the Designer delimits table and field names containing the slash character (/) with double quotes.
In the mapping shown above, although there are many columns in the source definition, only three columns are connected to another transformation. In this case, the Informatica Server generates a default query that selects only those three columns: SELECT CUSTOMERS.CUSTOMER_ID, CUSTOMERS.COMPANY, CUSTOMERS.FIRST_NAME FROM CUSTOMERS When generating the default query, the Designer delimits table and field names containing the slash character (/) with double quotes.
It determines how to handle changes to existing records When you design your data warehouse, you need to decide what type of information to store in targets. As part of your target table design, you need to determine whether to maintain all the historic data or just the most recent changes. For example, you might have a target table, T_CUSTOMERS, that contains customer data. When a customer address changes, you may want to save the original address in the table, instead of updating that portion of the customer record. In this case, you would create a new record containing the updated address, and preserve the original record with the old customer address. This illustrates how you might store historical information in a target table. However, if you want the T_CUSTOMERS table to be a snapshot of current customer data, you would update the existing customer record and lose the original address.
It determines how to handle changes to existing records When you design your data warehouse, you need to decide what type of information to store in targets. As part of your target table design, you need to determine whether to maintain all the historic data or just the most recent changes. For example, you might have a target table, T_CUSTOMERS, that contains customer data. When a customer address changes, you may want to save the original address in the table, instead of updating that portion of the customer record. In this case, you would create a new record containing the updated address, and preserve the original record with the old customer address. This illustrates how you might store historical information in a target table. However, if you want the T_CUSTOMERS table to be a snapshot of current customer data, you would update the existing customer record and lose the original address.
The Rank transformation differs from the transformation functions MAX and MIN, in that it allows you to select a group of top or bottom values, not just one value. For example, you can use Rank to select the top 10 salespersons in a given territory. Or, to generate a financial report, you might also use a Rank transformation to identify the three departments with the lowest expenses in salaries and overhead. While the SQL language provides many functions designed to handle groups of data, identifying top or bottom strata within a set of rows is not possible using standard SQL functions. Allows to create local variables and write non-aggregate expressions
During a session, the Informatica Server compares an input row with rows in the data cache. If the input row out-ranks a stored row, the Informatica Server replaces the stored row with the input row. If the Rank transformation is configured to rank across multiple groups, the Informatica Server ranks incrementally for each group it finds.
During a session, the Informatica Server compares an input row with rows in the data cache. If the input row out-ranks a stored row, the Informatica Server replaces the stored row with the input row. If the Rank transformation is configured to rank across multiple groups, the Informatica Server ranks incrementally for each group it finds.
Limitations exist on passing data, depending on the database implementation Stored procedures are stored and run within the database. Not all databases support stored procedures, and database implementations vary widely on their syntax. You might use stored procedures to: Drop and recreate indexes. Check the status of a target database before moving records into it. Determine if enough space exists in a database. Perform a specialized calculation. Database developers and programmers use stored procedures for various tasks within databases, since stored procedures allow greater flexibility than SQL statements. Stored procedures also provide error handling and logging necessary for mission critical tasks. Developers create stored procedures in the database using the client tools provided with the database.
You can run several Stored Procedure transformations in different modes in the same mapping. For example, a pre-load source stored procedure can check table integrity, a normal stored procedure can populate the table, and a post-load stored procedure can rebuild indexes in the database. However, you cannot run the same instance of a Stored Procedure transformation in both connected and unconnected mode in a mapping. You must create different instances of the transformation. If the mapping calls more than one source or target pre- or post-load stored procedure in a mapping, the Informatica Server executes the stored procedures in the execution order that you specify in the mapping.
The stored procedure issues a status code that notifies whether or not the stored procedure completed successfully
You can pass a value from a port, literal string or number, variable, Lookup transformation, Stored Procedure transformation, External Procedure transformation, or the results of another expression. Separate each argument in a function with a comma. Except for literals, the transformation language is not case-sensitive. Except for literals, the Designer and Informatica Server ignore spaces. The colon (:), comma (,), and period (.) have special meaning and should be used only to specify syntax. The Informatica Server treats a dash (-) as a minus operator. If you pass a literal value to a function, enclose literal strings within single quotation marks. Do not use quotation marks for literal numbers. The Informatica Server treats any string value enclosed in single quotation marks as a character string. When you pass a mapping parameter or variable to a function within an expression, do not use quotation marks to designate mapping parameters or variables. Do not use quotation marks to designate ports. You can nest multiple functions within an expression (except aggregate functions, which allow only one nested aggregate function). The Informatica Server evaluates the expression starting with the innermost function.
After you save a mapplet, you can use it in a mapping to represent the transformations within the mapplet. When you use a mapplet in a mapping, you use an instance of the mapplet. Like a reusable transformation, any changes made to the mapplet are automatically inherited by all instances of the mapplet. Can use it in a mapping to represent the transformations within the mapplet
After you save a mapplet, you can use it in a mapping to represent the transformations within the mapplet. When you use a mapplet in a mapping, you use an instance of the mapplet. Like a reusable transformation, any changes made to the mapplet are automatically inherited by all instances of the mapplet. Can use it in a mapping to represent the transformations within the mapplet
Apply the following rules while designing mapplets: Use only reusable Sequence Generators Do not use pre- or post-session stored procedures in a mapplet Use exactly one of the following in a mapplet: Source Qualifier transformation ERP Source Qualifier transformation Input transformation Use at least one Output transformation in a mapplet
This does not replace the Server Manager, since there are many tasks that you can perform only with the Server Manager
Repository username. This can be configured optionally as an environment variable. Repository password. This can be configured optionally as an environment variable. Connection type. The type of connection from the client machine to the Informatica Server (TCP/IP or IPX/SPX). Port or connection. The TCP/IP port number or IPX/SPX connection (Windows NT/2000 only) to the Informatica Server. Host name. The machine hosting the Informatica Server (if running pmcmd from a remote machine through a TCP/IP connection). Session or batch name. The names of any sessions or batches you want to start or stop. Folder name. The folder names for those sessions or batches (if their names are not unique in the repository). Parameter file . The directory and name of the parameter file you want the Informatica Server to use with the session or batch.
Target-based commit. The Informatica Server commits data based on the number of target rows and the key constraints on the target table. The commit point also depends on the buffer block size and the commit interval. Source-based commit. The Informatica Server commits data based on the number of source rows. The commit point is the commit interval you configure in the session properties.
For example, a session is configured with target-based commit interval of 10,000. The writer buffers fill every 7,500 rows. When the Informatica Server reaches the commit interval of 10,000, it continues processing data until the writer buffer is filled. The second buffer fills at 15,000 rows, and the Informatica Server issues a commit to the target. If the session completes successfully, the Informatica Server issues commits after 15,000, 22,500, 30,000, and 40,000 rows.
Although the Filter, Router, and Update Strategy transformations are active transformations, the Informatica Server does not use them as active sources in a source-based commit session.
The Informatica Server might commit less rows to the target than the number of rows produced by the active source. For example, you have a source-based commit session that passes 10,000 rows through an active source, and 3,000 rows are dropped due to transformation logic. The Informatica Server issues a commit to the target when the 7,000 remaining rows reach the target. The number of rows held in the writer buffers does not affect the commit point for a source-based commit session. For example, you have a source-based commit session that passes 10,000 rows through an active source. When those 10,000 rows reach the targets, the Informatica Server issues a commit. If the session completes successfully, the Informatica Server issues commits after 10,000, 20,000, 30,000, and 40,000 source rows.
If a session fails or if you receive unexpected results in your target, you can run the Debugger against the session You might also want to run the Debugger against a session if you want the Informatica Server to process the configured session properties
Can create data or error breakpoints for transformations or for global conditions Cannot create breakpoints for mapplet Input and Output transformations Create breakpoints. You create breakpoints in a mapping where you want the Informatica Server to evaluate data and error conditions. Configure the Debugger. Use the Debugger Wizard to configure the Debugger for the mapping. You can choose to run the Debugger against an existing session or you can create a debug session. When you run the Debugger against an existing session, the Informatica Server runs the session in debug mode. When you create a debug session, you configure a subset of session properties within the Debugger Wizard, such as source and target location. You can also choose to load or discard target data. Run the Debugger. Run the Debugger from within the Mapping Designer. When you run the Debugger the Designer connects to the Informatica Server. The Informatica Server initializes the Debugger and runs session. The Informatica Server reads the breakpoints and pauses the Debugger when the breakpoints evaluate to true. Monitor the Debugger. While you run the Debugger, you can monitor the target data, transformation and mapplet output data, the debug log, and the session log. When you run the Debugger, the Designer displays the following windows: Debug log. View messages from the Debugger. Session log. View session log. Target window. View target data. Instance window. View transformation data. Modify data and breakpoints. When the Debugger pauses, you can modify data and see the effect on transformations, mapplets, and targets as the data moves through the pipeline. You can also modify breakpoint information.