3.19 PC86 – Purge older versions of objects in a versioned PowerCenter Repository
pmrep connect -r Repo_Name -d Domain_Name -n Administrator -x Pwd> test.out pmrep purgeversion -n -f > test1.out last_n_versions_to_keep — Number of latest checked-in object versions to keep for an active object in the folder specified (note: -f is an optional feature). The value must be an integer greater than 0. For example, enter 5 to purge all […]
3.18 PC86 – Informatica Services Not able to Start
Informatica Repository and Integration Services will be Not able to Start and you can view below error codes in admin console and server logs ERROR CODES: [CNX_53021 ],[DOM_10022], [LGS_10048],[DOM_10055],[SPC_10050],[SPC_10013],[SPC_10008] and [InfPrivilegeSynchronizationEngine] Logs: Admin Console: ERROR Mon Sep 24 00:00:33 2012 1833290048 CNX_53021 Received an invalid request. Service Manager ERROR Mon Sep 24 04:07:21 2012 Thread 2 of 6 in DomainServiceThreadPool DOM_10055 Unable […]
DM: Part 4.5 Physical Data Modeling
Physical Database Design Physical database design is the process of developing a set of required data structures on a selected database. It involves the following tasks: Converting entities into tables Converting relationships into foreign keys Converting attributes into columns Defining constraints The purpose of physical design is to optimize performance as closely as possible. Along […]
DM – Part 4.4 Logical Data Modeling
Introduction to Logical Model Logical Data Model refers to the actual implementation of a conceptual module in a database. It represents normalized design of common data model which is required to support the design of an information system. The very core of the logical data model is the definition of the three types of […]
DM: Part 4.3 Dimensional Data Model
4.3 Dimensional Data Modeling 4.3.1 Steps in Dimensional Modeling 4.3.2 Star Schema & Snowflake Schema4.3.3 The Implementation Approach (Bill & Ralph)4.3.4 Dimensional Modeling Fundamentals4.3.4.1 Dimensional Modeling Overview 4.3.4.2 Dimensional Modeling Steps 4.3.5 Confirmed Dimensions4.3.6 Slowly Changing Dimension 4.3.7 Additivity of Measures4.3.8 Dimensional Modeling framework 4.3.1 Steps in Dimensional Modeling 4.3.2 Star Schema & Snowflake […]
Dm – Part 4.2 Relational Data Modeling
4.2 Relational Data Modeling 4.2.1 Relational Data Model Concepts 4.2.2 ER to Relational Mapping Algorithm 4.2.3 Relational Database Design 4.2.3.1 Relational Database Design Approach 4.2.3.2 Normalization 4.2.1 Relational Data Model Concepts Relation Data Model A relational data model is a representational or implementation or record-based data model The model uses the concept of a mathematical […]
DM – Part 4.1 Conceptual Data Modeling
4. Data Modeling 4.1 Conceptual Data Modeling 4.1.1 Introduction to Conceptual Data Model 4.1.2 Stages in Conceptual Modeling 4.1.3 Components of a Conceptual Data Model 4.1.4 ER Modeling Basic Concepts 4.1.5 Enhanced ER Modeling 4.1.6 Guidelines for ER Modeling 4: 4.1 Conceptual Data Model Conceptual Data Model A conceptual schema or conceptual data […]
DM – Part 3: How to Data Model
3.1: Identify Entity Types Entity Object that can be observed and classified by its properties and characteristics Business definition with a clear boundary Characterized by a noun Example: Product, Employee 3.2: Identify Attributes Attributes Characteristics and properties of entities Example : Book Id, Description, book category are attributes of entity “Book” Attribute name should […]
DM – Part 2: Data Model
Advanced Data Modeling and Architecture Table of Contents Part 1: Data Modeling Overview 2.1 : Definition of a Data Model Model Representation of a set of business requirements in a standard structured framework understood by the users Data Model A collection of concepts that can be used to describe the structure of a database […]
DM – Part 1: Data Modeling Overview
Advanced Data Modeling and Architecture Table of Contents 1.1: Prerequisites for this Session Pre-Requisites Should be aware of DBMS ConceptsS Should be aware of Data warehouse concepts Should be aware of Data base concepts (any database) Should have 2+ years of experience on any ETL Tool 1.2 : Expectations from Session 1.3: Scope of […]