342 Courses in Cardiff delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient,maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects,adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples

Duration 1 Days 6 CPD hours This course is intended for This course is designed for students who wish to use Microsoft Word to create and modify complex documents and use tools that allow them to customize those documents. Overview In this course, you will learn fundamental Word skills. You will: Organize content using tables and charts. Customize formats using styles and themes. Insert content using Quick Parts. Use templates to automate document formatting. Control the flow of a document. Simplify and manage long documents. Use mail merge to create letters, envelopes, and labels. After you master the basics of using Microsoft© Word such as creating, editing, and saving documents; navigating through a document; and printing, you're ready to move on to tackling the more advanced features. These features enable you to create complex and professional documents with a consistent look and feel. They also enable you to automate tedious tasks such as preparing a letter to send to every customer of your organization.Creating professional-looking documents can help you give your organization a competitive edge. Implementing time-saving features such as document templates and automated mailings helps your organization reduce expenses. Mastering these techniques will make you a valued employee in your organization.Note: Most Office users perform the majority of their daily tasks using the desktop version of the Office software, so that is the focus of this training. The course material will alsoenable you to access and effectively utilize many web-based resources provided with your Microsoft 365 subscription. This includes brief coverage of key skills for using Word for theWeb and OneDrive©. Helpful notes throughout the material alert you to cases where the online version of the application may function differently from the primary, desktop version.This course may be a useful component in your preparation for the Microsoft Word (Microsoft 365 Apps and Office 2019): Exam MO-100 and Microsoft Word Expert (Microsoft 365 Apps and Office 2019): Exam MO-101 certification exams. Lesson 1: Organizing Content Using Tables and Charts Topic A: Sort Table Data Topic B: Control Cell Layout Topic C: Perform Calculations in a Table Topic D: Create a Chart Topic E: Add an Excel Table to a Word Document Lesson 2: Customizing Formats Using Styles and Themes Topic A: Create and Modify Text Styles Topic B: Create Custom List or Table Styles Topic C: Apply Document Themes Lesson 3: Inserting Content Using Quick Parts Topic A: Insert Building Blocks Topic B: Create and Modify Building Blocks Topic C: Insert Fields Using Quick Parts Lesson 4: Using Templates to Automate Document Formatting Topic A: Create a Document Using a Template Topic B: Create and Modify a Template Topic C: Manage Templates with the Template Organizer Lesson 5: Controlling the Flow of a Document Topic A: Control Paragraph Flow Topic B: Insert Section Breaks Topic C: Insert Columns Topic D: Link Text Boxes to Control Text Flow Lesson 6: Managing Long Documents Topic A: Insert Blank and Cover Pages Topic B: Insert an Index Topic C: Insert a Table of Contents Topic D: Insert an Ancillary Table Topic E: Manage Outlines Topic F: Create a Master Document Lesson 7: Using Mail Merge to Create Letters, Envelopes, and Labels Topic A: Use Mail Merge Topic B: Merge Data for Envelopes and Label Additional course details: Nexus Humans Microsoft Word for Office 365 (Desktop or Online) (v1.1) Part 2 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 Microsoft Word for Office 365 (Desktop or Online) (v1.1) Part 2 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.

Look at some of the more advanced planning features available in Project. Course overview Duration: 1 day (6.5 hours) Our Project – Advanced Planning and Control course looks at advanced planning and resourcing techniques in Microsoft Project and how to customise your schedule to give better visibility and flexibility. The course is designed for experienced users of Project who have attended our Project Planning and Control introduction course or have equivalent knowledge. You must be confident using Project to build and resource schedules and create task dependencies. Objectives  By the end of the course you will be able to: Work with different types of task Amend resource load on a task Work with multiple resource rates Create custom tables Add custom fields Create calculated fields Add drop down lists in fields Filter and extract information Create new views Export information Content Advanced planning techniques Splitting tasks Task types Spreading work across activities Advanced resourcing techniques Resource types Assignment views Effective dates Work contours Overtime work Using multiple resource rates Creating custom tables Customising tables Adding fields Creating custom fields Adding text, number, date and time fields Using flag fields Defining pick lists Renaming custom fields Creating calculated fields Creating formulas Using graphical indicators Uploading and tracking progress Completing work Completing work per resource Updating tasks Updating the project Working with the status date Rescheduling work Viewing baseline against schedule Project overview statistics Working with filters Building standard filters Building interactive filters Task and resource filters Using highlight filters Creating custom views Creating customised views Customising text styles Using grouping techniques Exporting information Exporting to Excel

Duration 3 Days 18 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who are currently using desktop or web-based data management tools such as Microsoft Excel or SQL Server reporting services to perform numerical or general data analysis. They are responsible for connecting to cloud-based data sources, as well as shaping and combining data for the purpose of analysis. They are also looking for alternative ways to analyze business data, visualize insights, and share those insights with peers across the enterprise. This includes capturing and reporting on data to peers, executives, and clients. This course is also designed for professionals who want to pursue the Microsoft Power BI Data Analyst (Exam PL-300) certification. Overview In this course, you will analyze data with Microsoft Power BI. You will: Analyze data with self-service BI. Connect to data sources. Perform data cleaning, profiling, and shaping. Visualize data with Power BI. Enhance data analysis by adding and customizing visual elements. Model data with calculations. Create interactive visualizations. Use advanced analysis techniques. Enhance reports and dashboards. Publish and share reports and dashboards. Extend Power BI beyond the desktop. As technology progresses and becomes more interwoven with our businesses and lives, more data is collected about business and personal activities. This era of 'big data' is a direct result of the popularity and growth of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantages. Creating data-backed visualizations is key for data scientists, or any professional, to explore, analyze, and report insights and trends from data. Microsoft© Power BI© software is designed for this purpose. Power BI was built to connect to a wide range of data sources, and it enables users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Power BI's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, enabling users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action. Analyzing Data with Self-Service BI Topic A: Data Analysis and Visualization for Business Intelligence Topic B: Self-Service BI with Microsoft Power BI Connecting to Data Sources Topic A: Create Data Connections Topic B: Configure and Manage Data Relationships Topic C: Save Files in Power BI Performing Data Cleaning, Profiling, and Shaping Topic A: Clean, Transform, and Load Data with the Query Editor Topic B: Profile Data with the Query Editor Topic C: Shape Data with the Query Editor Topic D: Combine and Manage Data Rows Visualizing Data with Power BI Topic A: Create Visualizations in Power BI Topic B: Chart Data in Power BI Enhancing Data Analysis Topic A: Customize Visuals and Pages Topic B: Incorporate Tooltips Modeling Data with Calculations Topic A: Create Calculations with Data Analysis Expressions (DAX) Topic B: Create Calculated Measures and Conditional Columns Creating Interactive Visualizations Topic A: Create and Manage Data Hierarchies Topic B: Filter and Slice Reports Topic C: Create Dashboards Using Advanced Analysis Techniques Topic A: Create Calculated Tables, Variables, and Parameters Topic B: Enhance Visuals with Statistical Analysis Topic C: Perform Advanced Analysis Enhancing Reports and Dashboards Topic A: Enhance Reports Topic B: Enhance Dashboards Publishing and Sharing Reports and Dashboards Topic A: Publish Reports Topic B: Create and Manage Workspaces Topic C: Share Reports and Dashboards Extending Power BI Beyond the Desktop Topic A: Use Power BI Mobile Topic B: Extend Access with the Power BI API Additional course details: Nexus Humans Microsoft Power BI: Data Analysis Professional (Second Edition) (v1.3) 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 Microsoft Power BI: Data Analysis Professional (Second Edition) (v1.3) 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 Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Duration 2 Days 12 CPD hours This course is intended for Authors Overview Please refer to course overview This course teaches experienced authors advanced report building techniques to enhance, customize, manage, and distribute reports. Additionally, the student will learn how to create highly interactive and engaging reports that can be run offline by creating Active Reports. Create query models Build a query and connect it to a report Answer a business question by referencing data in a separate query Create reports based on query relationships Create join relationships between queries Combine data containers based on relationships from different queries Create a report comparing the percentage of change Introduction to dimensional reporting concepts Examine data sources and model types Describe the dimensional approach to queries Apply report authoring styles Introduction to dimensional data in reports Use members to create reports Identify sets and tuples in reports Use query calculations and set definitions Dimensional report context Examine dimensional report members Examine dimensional report measures Use the default measure to create a summarized column in a report Focus your dimensional data Focus your report by excluding members of a defined set Compare the use of the filter() function to a detail filter Filter dimensional data using slicers Calculations and dimensional functions Examine dimensional functions Show totals and exclude members Create a percent of base calculation Create advanced dynamic reports Use query macros Control report output using a query macro Create a dynamic growth report Create a report that displays summary data before detailed data and uses singletons to summarize information Design effective prompts Create a prompt that allows users to select conditional formatting values Create a prompt that provides users a choice between different filters Create a prompt to let users choose a column sort order Create a prompt to let users select a display type Examine the report specification Examine report specification flow Identify considerations when modifying report specifications Customize reporting objects Distribute reports Burst a report to email recipients by using a data item Burst a list report to the IBM Cognos Analytics portal by using a burst table Burst a crosstab report to the IBM Cognos Analytics portal by using a burst table and a master detail relationship Enhance user interaction with HTML Create interactive reports using HTML Include additional information with tooltips Send emails using links in a report Introduction to IBM Cognos Active Reports Examine Active Report controls and variables Create a simple Active Report using Static and Data-driven controls Change filtering and selection behavior in a report Create interaction between multiple controls and variables Active Report charts and decks Create an Active Report with a Deck Create an Active Report with 11.0 visualizations

Duration 2 Days 12 CPD hours This course is intended for Report Authors Overview Create query models Create reports based on query relationships Introduction to dimensional data Introduction to dimensional data in reports Dimensional report context Focus your dimensional data Calculations and dimensional functions Create advanced dynamic reports This offering teaches Professional Report Authors about advanced report building techniques using relational data models, dimensional data, and ways of enhancing, customizing, managing, and distributing professional reports. The course builds on topics presented in the Fundamentals course. Activities will illustrate and reinforce key concepts during this learning activity. Create query models Build a query and connect it to a report Answer a business question by referencing data in a separate query Create reports based on query relationships Create join relationships between queries Combine data containers based on relationships from different queries Create a report comparing the percentage of change Introduction to dimensional reporting concepts Examine data sources and model types Describe the dimensional approach to queries Apply report authoring styles Introduction to dimensional data in reports Use members to create reports Identify sets and tuples in reports Use query calculations and set definitions Dimensional report context Examine dimensional report members Examine dimensional report measures Use the default measure to create a summarized column in a report Focus your dimensional data Focus your report by excluding members of a defined set Compare the use of the filter() function to a detail filter Filter dimensional data using slicers Calculations and dimensional functions Examine dimensional functions Show totals and exclude members Create a percent of base calculation Create advanced dynamic reports Use query macros Control report output using a query macro Create a dynamic growth report Create a report that displays summary data before detailed data and uses singletons to summarize information Design effective prompts Create a prompt that allows users to select conditional formatting values Create a prompt that provides users a choice between different filters Create a prompt to let users choose a column sort order Create a prompt to let users select a display type Examine the report specification Examine report specification flow Identify considerations when modifying report specifications Customize reporting objects Distribute reports Burst a report to email recipients by using a data item Burst a list report to the IBM Cognos Analytics portal by using a burst table Burst a crosstab report to the IBM Cognos Analytics portal by using a burst table and a master detail relationship Enhance user interaction with HTML Create interactive reports using HTML Include additional information with tooltips Send emails using links in a report Introduction to IBM Cognos Active Reports Examine Active Report controls and variables Create a simple Active Report using Static and Data-driven controls Change filtering and selection behavior in a report Create interaction between multiple controls and variables Active Report charts and decks Create an Active Report with a Data deck Use Master detail relationships with Decks Optimize Active Reports Create an Active Report with new visualizations

Duration 2 Days 12 CPD hours This course is intended for Report authors working with dimensional data sources. Through interactive demonstrations & exercises, participants will learn how to author reports that navigate & manipulate dimensional data structures using the specific dimensional functions & features available in IBM Cognos Analytics. Introduction to Dimensional Concepts Identify different data sources and models Investigate the OLAP dimensional structure Identify dimensional data items and expressions Differentiate the IBM Cognos Analytics query language from SQL and MDX Differentiate relational and dimensional report authoring styles Introduction to Dimensional Data in Reports Work with members Identify sets and tuples in IBM Cognos Analytics Dimensional Report Context Understand the purpose of report context Understand how data is affected by default and root members Focus Your Dimensional Data Compare dimensional queries to relational queries Explain the importance of filtering dimensional queries Evaluate different filtering techniques Filter based on dimensions and members Filter based on measure values Filter using a slicer Calculations & Dimensional Functions Use IBM Cognos Analytics dimensional functions to create sets and tuples Perform arithmetic operations in OLAP queries Identify coercion errors and rules Functions for Navigating Dimesional Hierarchies Navigate dimensional data using family functions Relative Functions Navigate dimensional data using relative functions Navigate dimensional data using relative time functions Advanced Drilling Techniques & Member Sets Understand default drill-up and drill-down functionality Identify cases when you need to override default drilling behavior Configure advanced drilling behavior to support sophisticated use cases Define member sets to support advanced drilling Define member sets to support functions Set Up Drill-Through Reports Navigate from a specific report to a target report Drill down to greater detail and then navigate to target report Navigate between reports created using different data sources End-to-End Workshop Review concepts covered throughout the course

Duration 5 Days 30 CPD hours This course is intended for This hands-on course is geared for experienced DBAs new to Oracle 19c, who can work in Linux and have basic experience with SQL scripting. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: How to use tools to access an Oracle Database Generate database creation scripts by using DBCA How to create a container database (CDB) by using the CREATE DATABASE command Learn about Startup and shut down Oracle databases Initialization parameter files and initialization parameters Tools that are used to administer Oracle Net Services How to use the Oracle Connection Manager Control utility to administer Oracle Connection Manager How to create a new PDB from the PDB seed. Logical and physical storage structures in an Oracle database Usage of Oracle Database features that save space Explanation of DML and undo data generation Learn about general architecture of Oracle Data Pump and SQL*Loader How to use SQL*Loader to load data from a non-Oracle database (or user files) Bonus Content / Time Permitting: Explanation of maintenance windows Bonus Content / Time Permitting: Employ basic monitoring procedures and manage performance Oracle 19C Database Administration I (Oracle DBA I) is a comprehensive, hands-on course provides concrete information on the design of an Oracle Database instance and database, allowing you to manage your database investment. In this class, you will learn how to create database storage structures that align with your requirements and business models. You will also learn how to create users and administer databases as well as harden the databases to meet your business requirements. This is the foundational course for learning about Oracle Database and it does not assume prior knowledge or Oracle technologies, however you should have incoming experience working with SQL, and be comfortable with Linux and working from the command line. This training is NOT Official Oracle University training. This is independent, adjustable content that aligns with current topics, skills and tools that participants need to excel in these areas. Introduction to Oracle Database Oracle Multitenant Container Database Oracle Database Instance Configurations Database Sharding Oracle Database Server Accessing an Oracle Database Oracle Database Tools Database Tool Choices SQL Developer Enterprise Manager Database Express Creating an Oracle Database by Using DBCA Planning the Database Choosing a Database Template Configuration Assistant Creating an Oracle Database by Using a SQL Command Creating a Container Database Enable Pluggable Database Starting Up and Shutting Down a Database Instance Starting the Oracle Database Instance Shutting Down an Oracle Database Instance Opening and Closing PDBs Managing Database Instances Investigating Initialization Parameter Files Viewing Initialization Parameters by Using SQL*Plus Modifying Initialization Parameters by Using SQL*Plus Viewing Diagnostic Information Oracle Net Services Overview Oracle Net Services Components Oracle Net Listener Configuring Naming Methods Configuring the Oracle Network to Access a Database Creating a Net Service Name for a PDB Configuring and Administering the Listener Exploring the Default Listener Creating a Second Listener Connecting to a Database Service Using the New Listener Configuring a Shared Server Architecture Configuring Shared Server Mode Configuring Clients to Use a Shared Server Configuring Oracle Connection Manager for Multiplexing and Access Control Oracle Connection Manager Processes Filtering Rules Session Multiplexing Creating PDBs Creating a New PDB from the PDB Seed Cloning Remote PDBs in Hot Mode Relocating PDBs Managing PDBs Renaming a PDB Setting Parameter Values for PDBs Database Storage Overview Logical and Physical Database Structures Tablespaces and Data Files Types of Segments Monitoring Tablespace Space Usage Creating and Managing Tablespaces Viewing Tablespace Information Creating a Tablespace Managing Temporary and Permanent Tablespaces Improving Space Usage Managing Space in Tablespaces Using Compression Enabling the Resumable Space Allocation Feature Creating and Managing User Accounts Creating Common and Local Users Creating a Local User for an Application Exploring OS and Password File Authentication Configuring Privilege and Role Authorization Granting a Local Role (DBA) to PDBADMIN Using SQL*Developer to Create Local Roles Configuring User Resource Limits Using SQL*Developer to Create a Local Profile & Users Configuring a Default Role for a User Implementing Oracle Database Auditing Enabling Unified Auditing Creating Audit Users Creating an Audit Policy Introduction to Loading and Transporting Data General Architecture Oracle Data Pump SQL Loader Loading Data into a PDB from an External File Moving Data from One PDB to Another PDB Transporting a Tablespace Using External Tables to Load and Transport Data Querying External Tables Unloading External Tables Automated Maintenance Tasks Overview Automated Maintenance Tasks Maintenance Windows Predefined Maintenance Windows Bonus: Managing Tasks and Windows Enabling and Disabling Automated Maintenance Tasks Modifying the Duration of a Maintenance Window Bonus: Database Monitoring and Performance Tuning Overview Performance Planning Considerations Automatic Workload Repository (AWR) Advisory Framework Bonus: Monitoring Database Performance & Processes Server-Generated Alerts Setting Metric Thresholds Performance Monitoring Examining the Database Background Processes Bonus: Tuning Database Memory Viewing Memory Configurations Bonus: Analyzing SQL and Optimizing Access Paths Using the Optimizer Statistics Advisor

Duration 3 Days 18 CPD hours This course is intended for Authors Overview Please refer to course overview This course provides authors with an introduction to build reports using Cognos Analytics. Techniques to enhance, customize, and manage reports will be explored. Activities will illustrate and reinforce key concepts during this learning opportunity. What is IBM Cognos Analytics - Reporting The Welcome page Consume report content Interactive filtering Working with reports Dimensionally modeled relational dataUse personal data sources and data modules Upload personal data Upload custom images Using navigation paths in a data module Examine list reports Group data Format columns Include headers and footers Aggregate fact data Identify differences in aggregation Multiple facts and repeated information Use shared dimensions to create multi-fact queries Present repeated information Add repeated information to reports Create a mailing list report Create crosstab reports Add measures to a crosstab Data sources for a crosstab Create complex crosstab reports Add items as peers Create crosstab nodes and crosstab members Work with crosstab data Format, sort, and aggregate a crosstab Create discontinuous crosstab reportsCreate visualization reports Visualization categories Customize visualizations Client side visualizations Enhanced map visualizations Focus reports using filters Create filters to narrow the focus Use advanced detail filters Apply a filter with aggregation Use summary filters Focus reports using prompts Examine parameters and prompts Create a parameter for a report item Add a prompt page Add a prompt item to a report Identify a prompt type Create a cascading prompt Use calculations What are calculations Add Date and Time functions Add string functions Display prompt selections in report titles Customize reports with conditional formatting Three steps for conditional formatting Create a variable Assign the variable to a report object Format based on the conditional value Conditionally render report objects Drill-through definitions Navigate to related data Enhance report layout View the structure of a report Use Guided report layout Force page breaks Create horizontal pagination Modify the report structure Format objects across reports Use additional report-building techniques Enhance a report design Add objects to reports Convert a list to a crosstab Explore reuse Additional course details: Nexus Humans B6258 IBM Cognos Analytics - Author Reports Fundamentals 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 B6258 IBM Cognos Analytics - Author Reports Fundamentals 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.