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Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using IBM Cognos Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager (Optional) Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

The best leaders are able to enable their team and the organisation to fulfil their potential by creating a highly motivational environment. This program will equip you with skills to: Establish and communicate organisational vision and values Lead change and promote innovation Develop effective teams and coach leaders Understand motivation and develop peoples' potential.

Leadership Foundations introduces the ideas and practical tools that help individuals, teams and organisations function more effectively. It is also known as 'Foundations of Success' and comprises the core principles and some initial resources that we share with all our clients: The Four Foundations of Leadership Personal responsibility and prioritisation The tyranny of the urgent & the secret of uninterrupted time Developing a planning and goal setting system Understanding Communication Styles Your personal goals and life balance 10 Magic Minutes daily planning

Before you can effective lead others, you must first lead yourself. This 12 module program will help you develop in the following areas: Self Knowledge & Emotional Intelligence Identifying your strengths and building on them Values and Personal Mission Statement Self-motivation and personal goals Taking personal responsibility Discovering your purpose Authentic leadership and influencing others

Duration 2 Days 12 CPD hours This course is intended for This course is recommended for technical professionals who automate, orchestrate, and troubleshoot Check Point secured environments. Overview Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API The goal of this course is to provide an understanding of the advanced concepts and skills necessary to automate and orchestrate tasks relating to managing Check Point Security Policies Course Ouline Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API Demonstrate how to create API commands to efficiently maintain the Check Point Security Management Server database Demonstrate how to use different methods to update the database with API commands Become familiar with client-side and server-side scripting and scripting languages Understand how to use the Bash shell to develop APIs Recognize and describe many of the open source tools that are available to assist with API development Demonstrate how to use a custom REST application to update the database of a Security Management Server Demonstrate how to use Postman to manage the Security Policy database through the Check Point API Understand what steps to take to troubleshoot and debug API scripts Demonstrate basic troubleshooting techniques by reviewing debugging messages in various forms Understand how to use self-service portal capabilities to provide general IT services Recognize how automation tools work with Check Point APIs to automate security management tasks and orchestrate workflow behind service portals Demonstrate common tasks that are automated in a Web portal to manage the Security Policy LAB Exercises Demonstrate Check Point automation and orchestration Manage objects using the Check Point API Create a management API shell script Use a variety of methods to execute API commands Use a custom REST tool for API calls Use Postman for API calls Debug the Check Point management API Automate tasks using a Check Point API enabled Web portal Additional course details: Nexus Humans CCAS Check Point Certified Automation Specialist training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CCAS Check Point Certified Automation Specialist course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 5 Days 30 CPD hours This course is intended for In order to be successful in this course you should have incoming hands-on experience with another programming language. This course is not for non-developers or new developers. Possible roles that may attend this course include: Software Developers: Professionals who have been working with other programming languages and want to expand their skillset by learning Java and its object-oriented features. Web Developers: Those who work on web applications and want to enhance their back-end development capabilities with Java. Mobile App Developers: Developers who wish to enter the world of Android app development, where Java is a widely used language for creating mobile applications. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how?it relates to OO programming and the Object Model Learn to use Java exception handling Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Become familiar with the concept of functional programming using Lambda Expressions Process large amounts of data using the Stream API introduced in Java 8 Discover the new Date/Time API Use the JDBC API for database access Work with annotations Take advantage of the Java tooling that is available with the programming environment being used in the class Java 8 Features: Lambda Expressions, Method and Constructor references, The Streams API, Collectors, The Optional class Geared for experienced developers, Basic Java Programming for Developers New to OO, this hands-on, workshop-style course will provide you with an immersive learning experience that will expand your skillset and open doors to new opportunities within the ever-growing technology landscape. Mastering Java and its powerful capabilities will provide you with the competitive edge you need to stand out in today's fast-paced development world. Working in a hands-on learning environment led by our expert coach, you?ll thoroughly explore the foundations of the Java platform, essential programming concepts, and advanced topics, ensuring you acquire a strong understanding of the language and its ecosystem. The object-oriented programming principles taught in this course promote code reusability and maintainability, enabling you to streamline development processes and reduce long-term costs. As you progress through the course, you will also gain familiarity with using an IDE, enhancing your development workflow and collaboration with other Java developers, enabling you to integrate seamlessly into new projects and teams. You?ll also gain practical experience in applying the concepts and techniques learned, solidifying your newly acquired skills and facilitating their direct application in real-world scenarios. You?ll exit this course empowered to create robust, scalable, and efficient Java-based applications that drive innovation and growth for your organization The Java Platform The Java Platform Lifecycle of a Java Program Responsibilities of JVM Documentation and Code Reuse Using the JDK Explain the JDK?s file structure Use the command line compiler to compile a Java class Use the command line Java interpreter to run a Java application class The IntelliJ Paradigm Introduce the IntelliJ IDE The Basics of the IntelliJ interface IntelliJ Projects and Modules Creating and running Java applications Writing a Simple Class Write a Java class that does not explicitly extend another class Define instance variables for a Java class Create object instances Primitives vs Object References Implement a main method to create an instance of the defined class Adding Methods to the Class Write a class with accessor methods to read and write instance variables Write a constructor to initialize an instance with data Write a constructor that calls other constructors of the class to benefit from code reuse Use the this keyword to distinguish local variables from instance variables Object-Oriented Programming Real-World Objects Classes and Objects Object Behavior Methods and Messages Inheritance, Abstraction, and Polymorphism Encapsulation Inheritance Method Overriding Polymorphism Essential Java Programming Essential Java Programming Language Statements Arithmetic operators Operators to increment and decrement numbers Comparison operators Logical operators Return type of comparison and logical operators Use for loops Switch Expressions Switch Expressions and yield Using Strings and Text Blocks Create an instance of the String class Test if two strings are equal Get the length of a string Parse a string for its token components Perform a case-insensitive equality test Build up a string using StringBuffer Contrast String, StringBuffer,and StringBuilder Compact Strings Text Blocks Specializing in a Subclass Constructing a class that extends another class Implementing equals and toString Writing constructors that pass initialization data to parent constructor Using instanceof to verify type of an object reference Pattern matching for instanceof Overriding subclass methods Safely casting references to a more refined type Fields and Variables Discuss Block Scoping Rules Distinguish between instance variables and method variables within a method Explain the difference between the terms field and variable List the default values for instance variables Final and Static fields and methods Local Variable type inference Using Arrays Declaring an array reference Allocating an array Initializing the entries in an array Writing methods with a variable number of arguments Records Data Objects in Java Introduce records as carrier of immutable data Defining records Java Packages and Visibility Use the package keyword to define a class within a specific package Discuss levels of accessibility/visibility Using the import keyword to declare references to classes in a specific package Using the standard type naming conventions Visibility in the Java Modular System Correctly executing a Java application class The Java modular system Defining Modules Inheritance and Polymorphism Write a subclass with a method that overrides a method in the superclass Group objects by their common supertype Utilize polymorphism Cast a supertype reference to a valid subtype reference Use the final keyword on methods and classes to prevent overriding Interfaces and Abstract Classes Define supertype contracts using abstract classes Implement concrete classes based on abstract classes Define supertype contracts using interfaces Implement concrete classes based on interfaces Explain advantage of interfaces over abstract classes Explain advantage of abstract classes over interfaces Static, default and private methods in interfaces Sealed classes Introduce Sealed classes The sealed and permits modifiers Sealed Interfaces Exception Handling Introduction to Exception Handling Introduce the Exception architecture Defining a try/catch blocks Checked vs Unchecked exceptions Exceptions Defining your own application exceptions Automatic closure of resources Suppressed exceptions Handling multiple exceptions in one catch Helpful Nullpointers Enhanced try-with-resources Java Developer's Toolbox Developing applications Introduce the wrapper classes Explain Autoboxing and Unboxing Converting String representations of primitive numbers into their primitive types Defining Enumerations Using static imports Deprecating methods Advanced Java Programming Introduction to Generics Generics and Subtyping Bounded Wildcards Generic Methods Legacy Calls To Generics When Generics Should Be Used Lambda Expressions and Functional Interface Understanding the concept of functional programming Writing lambda expressions Understanding functional interfaces Collections Provide an overview of the Collection API Review the different collection implementations (Set, List and Queue) Explore how generics are used with collections Examine iterators for working with collections Using Collections Collection Sorting Comparators Using the Right Collection Lambda expressions in Collections Bonus Topics: Time Permitting Streams Understanding the problem with collections in Java Thinking of program solutions in a declarative way Use the Stream API to process collections of data Understand the difference between intermediate and terminal stream operations Filtering elements from a Stream Finding element(s) within a Stream Collecting the elements from a Stream into a List takeWhile and dropWhile intermediate operations Collectors Using different ways to collect the items from a Stream Grouping elements within a stream Gathering statistics about numeric property of elements in a stream

Duration 5 Days 30 CPD hours This course is intended for This course is intended for individuals who are Application designers and database developers, database administrators and web server administrators. Overview Upon successful completion of this course, students will be able to work with Oracle database programming using the PL/SQL programming language. They will learn the syntax, structure and features of the language. In this course, students will learn the foundation for the programming series and the use of database-resident stored program units for Oracle 12c. Selection & Setup of the Database Interface Considering Available Tools Selecting the Appropriate Tool Oracle Net Database Connections Oracle PAAS Database Connections Setup SQL Developer Setup SQL*Plus Setup Jdeveloper About Bind & Substitution Variables Using SQL Developer Using SQL*Plus Choosing a Database Programming Language What is Database Programming? PL?SQL Performance Advantages Integration wth Other Languages PL/SQL Language Fundamentals PL/SQL Program Structure LANGUAGE SYNTAX RULES EMBEDDING SQL WRITING READABLE CODE GENERATING DATABASE OUTPUT SQL*PLUS INPUT OF A PROGRAM BLOCK Declare Section About the Declare Section DECLARE PRIMITIVE TYPES DECLARATION OPTIONS NOT NULL CONSTANT DATA DICTIONARY INTEGRATION %TYPE DECLARE SIMPLE USER---DEFINED TYPES TYPE... TABLE TYPE... RECORD EXTENDED USER---DEFINED TYPES Begin Section About the Begin Section Manipulating Program Data Logic Control & Branching GOTO LOOP IF-THEN-ELSE CASE Exception Section ABOUT THE EXCEPTION SECTION ISOLATING THE SPECIFIC EXCEPTION PRAGMA EXCEPTION_INIT SQLCODE &SQLERRM Example SQL%ROWCOUNT &SELECT...INTO Beyond the Basics: Explicit Cursors ABOUT EXPLICIT CURSORS EXTENDED CURSOR TECHNIQUES FOR UPDATE OF Clause WHERE CURRENT OF Clause Using FOR?LOOP Cursors Beyond the Basics: Nested BlocksBeyond the Basics: Declared Subprograms USING DECLARED SUBPROGRAMS DECLARED PROCEDURE DECLARED FUNCTION Introducing Databse-Resident Program Units ABOUT DATABASE---RESIDENT PROGRAMS PHYSICAL STORAGE & EXECUTION TYPES OF STORED PROGRAM UNITS STORED PROGRAM UNIT ADVANTAGES MODULAR DESIGN PRINCIPLES Creating Stored Procedures & Functions STORED PROCEDURES & FUNCTIONS CREATE PROCEDURE / CREATE FUNCTION CREATING PROCEDURES & FUNCTIONS RAISE_SALARY() Procedure SALARY_VALID() Function THE PARAMETER SPECIFICATION DEFAULT Clause SYSTEM & OBJECT PRIVILEGES USING THE DEVELOPMENT TOOLS Executing Stored Procedures & Functions CALLING PROCEDURES & FUNCTIONS UNIT TESTING WITH EXECUTE ANONYMOUS BLOCK UNIT TESTING SPECIFYING A PARAMETER NOTATION SQL WORKSHEET UNIT TESTING CALLING FUNCTIONS FROM SQL Maintaining Stored Program Units RECOMPILING PROGRAMS Mass Recompilation Using UTL_RECOMP() DROPPING PROCEDURES & FUNCTIONS DROP PROCEDURE / FUNCTION DATA DICTIONARY METADATA Using USER_OBJECTS Using USER_SOURCE Using USER_ERRORS Using USER_OBJECT_SIZE Using USER_DEPENDENCIES Managing Dependencies DEPENDENCY INTERNALS TRACKING DEPENDENCIES THE DEPENDENCY TRACKING UTILITY SQL DEVELOPER DEPENDENCY INFO DEPENDENCY STRATEGY CHECKLISTS Creating & Maintaining Packages ABOUT PACKAGES CREATING PACKAGES MAINTAINING PACKAGES PERFORMANCE CONSIDERATIONS Advanced Package Capabilities DEFINER & INVOKER RIGHTS WHITE LITS & ACCESSIBLE BY PERSISTENT GLOBAL OBJECTS DEFINING INITIALIZATION LOGIC OBJECT ORIENTATION SUPPORT Advanced Cursor Techniques USING CUSROS VARIABLES USING SYS_REFCURSOR USING CURSOR EXPRESSIONS Using System-Supplied Package DBMS_OUTPUT() UTL_FILE() FOPEN() EXAMPLE Database Trigger Concepts ABOUT DATABASE TRIGGERS DML EVENT TRIGGER SUB---TYPES DATABASE TRIGGER SCENARIO TRIGGER EXECUTION MECHANISMS TRIGGERS WITHIN SQL WORKSHEET Creating Database Triggers STATEMENT-LEVEL TRIGGERS Using RAISE_APPLICATION_ERROR() ROW---LEVEL TRIGGERS EXAMPLES OF TRIGGERS EMPLOYEE_SALARY_CHECK Example EMPLOYEE_JOURNAL Example BUDGET_EVENT Example INSTEAD OF TRIGGERS TRIGGERS WITHIN AN APPLICATION Maintaining Database Triggers CALL SYNTAX TRIGGER MAINTENANCE TASKS SHOW ERRORS TRIGGER DROP TRIGGER ALTER TRIGGER MULTIPLE TRIGGERS FOR A TABLE HANDLING MUTATING TABLE ISSUES Implementing System Event Triggers WHAT ARE SYSTEM EVENT TRIGGERS? DEFININGTHE SCOPE AVAILABLE SYSTEM EVENTS SYSTEM EVENT ATTRIBUTES