390 Business Intelligence (BI) courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are System Administrators and System Architects. Overview Explain the architecture in SAP BusinessObjects Business Intelligence platformConfigure SAP BusinessObjects Business Intelligence platformPerform common server management and administrative tasks in SAP BusinessObjects Business Intelligence platform In this course, students learn how to explain the architecture in the SAP BusinessObjects Business Intelligence platform and perform common server management and administrative tasks in the SAP BusinessObjects Business Intelligence platform. SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Architecture Installation of SAP BusinessObjects Business Intelligence Platform Installing SAP BusinessObjects Business Intelligence Platform: Server-Side Installation Installing SAP BusinessObjects Business Intelligence Platform: Client-Side Installation Server Administration and Management Using the Central Management Console (CMC) Using the Central Configuration Manager (CCM) Web Application Servers Management Configuring Web Application Servers Central Management Server (CMS) Database Managing the Central Management Server (CMS) and System Database Configuring Auditing File Repository Server Management Managing the File Repository Server Using the Repository Diagnostic Tool Adaptive Servers Managing the Adaptive Job Server Managing the Adaptive Processing Server Crystal Reports Servers Demonstrating Information Flows in Crystal Reports Configuring Crystal Reports Managing Crystal Reports Servers Web Intelligence Server Managing Web Intelligence Document Schedules Viewing Web Intelligence Documents Configuring a Web Intelligence Processing Server Configuring a Connection Server Dashboard Servers Configuring Dashboard Servers Managing Dashboard Design Servers Explorer Servers Configuring Explorer Servers Managing Information Spaces Event Servers Configuring Event Servers Managing Event Servers SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Monitoring the SAP BusinessObjects Business Intelligence Platform 4.1 Using the SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Dashboard Additional course details: Nexus Humans BOE320 SAP BI Platform - Admin Servers (Win) 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 BOE320 SAP BI Platform - Admin Servers (Win) 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 The audience for this course should have previous experience with functional or technical focus in Dynamics 365: Finance and Operations Applications. Primarily for those who are aspired to be and new to solution architect role Overview After completing this course, students will be able to: Understand the tasks expected to be completed by the solution architect for Dynamics implementation Complete the solution blueprint artifacts Know where to find technical information to address their customer's questions This course is developed for those aspired to be and new to the solution architect role. This course provides the technical information focusing on application architecture and technical skills to start their journey into this role. This course will not cover the industrial skills and delivery skills required for this role. The Architect Role The solution architect role Manage Interactions with FastTrack Get to know FastTrack Make the most of FastTrack templates Solution Blueprint Solution blueprint definition and components Project governance and timeline Solution architecture and organizational structure Working with business process catalog Define Environments, Tools, and Deployment Strategy Understand environment planning Application lifecycle management and deployment strategy Using LCS and Azure DevOps Determine Data Management Strategy Data management overview Develop data migration strategy Determine Integration and Interfaces Strategies Develop integration strategy Integration options Define Security Architecture Important security aspects Security framework Define security strategy Define Testing Strategy Testing strategy overview Testing planning and execution Define Performance Testing Strategy Prepare for performance topics Utilize performance testing tools Business Intelligence and Reporting Implement business intelligence and reporting Determine Licensing and Support Understand licensing estimation Understand support options Prepare for Go-Live Complete solution blueprint Prepare for go-live Class recap Additional course details: Nexus Humans MB-700T00 Microsoft Dynamics 365: Finance and Operations Apps Solution Architect 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 MB-700T00 Microsoft Dynamics 365: Finance and Operations Apps Solution Architect 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 This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 2 Days 12 CPD hours This course is intended for This course is aimed at anyone currently working with data who is interested in using data visualisation to more effectively communicate their results. Overview At completion, delegates will understand how data visualisations can be best used to communicate actionable insights from data and be competent with the tools required to do it. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. Course Outline The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding. The companies doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. To attend this course delegates should be competent in the use of data analysis tools such as reporting tools, spreadsheet software or business intelligence tools. The course will explore the following topics through a series of interactive workshop sessions: Fundamentals of data visualisation Data characteristics & dimensions Mapping visual encodings to data dimensions Colour theory Graphical perception & communication Interaction design Visualisation different characteristics of data: trends, comparisons, correlations, maps, networks, hierarchies, text Designing effective dashboards

Duration 3 Days 18 CPD hours This course is intended for The course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data. Overview After completing this course, students will be able to: ? Perform Power BI desktop data transformation. ? Describe Power BI desktop modelling. ? Create a Power BI desktop visualization. ? Implement the Power BI service. ? Describe how to connect to Excel data. ? Describe how to collaborate with Power BI data. ? Connect directly to data stores. ? Describe the Power BI developer API. ? Describe the Power BI mobile app. The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App. Introduction to Self-Service BI Solutions Introduction to business intelligence Introduction to data analysis Introduction to data visualization Overview of self-service BI Considerations for self-service BI Microsoft tools for self-service BI Lab : Exploring an Enterprise BI solution Introducing Power BI Power BI The Power BI service Lab : Creating a Power BI dashboard Power BI Using Excel as a data source for Power BI The Power BI data model Using databases as a data source for Power BI The Power BI service Lab : Importing data into Power BI Shaping and Combining Data Power BI desktop queries Shaping data Combining data Lab : Shaping and combining data Modelling data Relationships DAX queries Calculations and measures Lab : Modelling Data Interactive Data Visualizations Creating Power BI reports Managing a Power BI solution Lab : Creating a Power BI report Direct Connectivity Cloud data Connecting to analysis services Lab : Direct Connectivity Developer API The developer API Custom visuals Lab : Using the developer API Power BI mobile app The Power BI mobile app Using the Power BI mobile app Power BI embedded

Duration 2 Days 12 CPD hours This course is intended for This course is intended for SQL professionals, Microsoft Analysis Services cube and report developers, and business intelligence professionals. Overview ?Understand common Analysis Services solutions.?Understand version changes of SSAS from 2008-2014.?Understand Analysis Services installation and architecture.?Understand how to choose the right model.?Understand the Analysis Services tools available.?Understand the multidimensional model.?Utilize data sources and data source views.?Create a cube.?Understand and utilize dimensions.?Understand and utilize attributes.?Understand and utilize relationships.?Understand and utilize hierarchies.?Understand and utilize measures and measure groups.?Understand and utilize calculated members.?Understand and utilize perspectives.?Understand and utilize translations.?Browse perspectives and translations.?Understand and utilize deployment options.?Understand and utilize processing strategies.?Understand and utilize security.?Deploy a multidimensional model.?Understand the tabular model.?Create a tabular project.?Analyze the data using Microsoft Excel.?Create and configure calculated measures and calculated fields.?Backup and Restore. This course is intended for IT professionals who are interested in quickly learning how to utilize an Analysis Services multidimensional or tabular solution. Course Overview Introduction Course Materials Facilities Prerequisites What We'll Be Discussing Lab 1: Course Overview Introduction to Microsoft SQL Server Analysis Services Common Analysis Services Solutions Version Changes of SSAS from 2008-2014 Analysis Services Installation and Architecture: One Product, Two Models Choosing the Right Model Analysis Services Tools Lab 1: Introduction to Microsoft SQL Server Analysis Services The Multidimensional Solution Understanding the Multidimensional Model Utilizing Data Sources and Data Source Views Creating a Cube Lab 1: The Multidimensional Solution Dissecting with Dimensions Developing Dimensions Utilizing Attributes Relating with Relationships Handling Hierarchies Lab 1: Dissecting with Dimensions Managing Measures Measures and Measure Groups Calculated Members Lab 1: Managing Measures Configuring Cube Options Understanding Perspectives Utilizing Translations Browsing Perspectives and Translations Lab 1: Configuring Cube Options Deploying Examining Deployment Options Processing Strategies Exploring Security Lab 1: Deploying The Tabular Solution Understanding the Tabular Model Creating a Tabular Project Deploying Browsing the Model Querying the Solution and Understanding DAX Maintaining and Optimizing Lab 1: The Tabular Solution

Duration 3 Days 18 CPD hours This course is intended for This course is most suited for IT professionals who have a need to understand the current requirements and core competences for managing IT in mission-critical environments. Overview After completion of the course the participant will be able to: 1. Provide guidance and implementation for IT strategy as set by senior IT and business management 2. Select and manage staff, implement training programs, career plan development and job rotation programs 3. Select, evaluate and negotiate vendors using RFI, RFP and selection criteria 4. Provide guidance for developing, testing and implementing business applications 5. Manage and/or assist in IT project management 6. Design and implement service management processes for incident, problem and change management 7. Understand the need for business continuity and design the business continuity plan 8. Review and implement information security practices and controls 9. Assist and initiate risk management practices 10. Understand and select new technologies such as cloud computing, big data, Internet of Things and social media to support business change demands 11. Select strategies for information management 12. Measure and improve quality of IT services CITS is designed to teach the skills, knowledge and competencies required of the modern IT specialist working at the senior professional, team-leader, supervisor or management level in IT management. IT Strategy The need for Information Technology Enterprise architecture Service catalogue Service level management Sustainable development IT Organisation Personnel need Roles and responsibilities Sourcing Selection process Hiring staff Managing staff Career planning Training / job rotation Performance appraisal Staff departures Vendor Selection / Management The importance of vendors Vendor selection Request For Information (RFI) Request For Proposal (RFP) Proposal evaluation Vendor reference checks Contract negotiation Contract management Vendor management Re-compete vendors Project Management Methodologies Project organisation Starting up / initiating Planning / initiation a project Risk Quality Scope Work / Product Breakdown Structure PERT diagram / Gantt chart Cost Communication Application Management Software Development Life Cycle (SDLC) Software Quality Assurance (SQA) Requirements Development Testing Adoption (implementation) Maintenance Service Management Incident management Problem management Change management Business Continuity Management Standards and guidelines Objectives Context Interested parties Scope Roles and responsibilities Resources and competences Awareness and communication Documentation Business Impact Analysis Risk Management Guidelines Context establishment Identification Analysis Evaluation Treatment Communication Monitoring and control Information Security Management Standards Confidentiality Integrity Availability Controls types Guideline for controls selection Control categories Information security awareness Security incident response Information and Knowledge Management Information management Data management Information management - technologies Business intelligence Data management - technologies Best practices in data governance Pitfalls in data governance Business Change Management Business change Frameworks, models and techniques Needs identification Cloud computing Social media / digital marketing Big data Internet of Things (IoT) Quality Management Standards, guidelines and frameworks Objectives Activities Services review Customer feedback Customer survey Key Performance Indicators (KPI) Metrics Scorecards and reports Quality register Exam Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Duration 3 Days 18 CPD hours This course is intended for Senior Executives CIOs and CTOs Business Intelligence Executives Marketing Executives Data & Business Analytics Specialists Innovation Specialists & Entrepreneurs Academics, and other people interested in Big Data Overview More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection. Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students. Workshop Application Use Cases Oz Metropolitan Architectural questions Team activity: Analyze Metroz Application Use Cases Application Vertical Slice Definition Minimizing risk of an unsound architecture Selecting a vertical slice Team activity: Identify an initial vertical slice for Metroz Application Processing Real time, near real time processing Batch processing Data access patterns Delivery and processing guarantees Machine Learning pipelines Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines Application Data Three V?s of Big Data Data Lifecycle Data Formats Transforming Data Team activity: Metroz Data Requirements Scalable Applications Scale up, scale out, scale to X Determining if an application will scale Poll: scalable airport terminal designs Hadoop and Spark Scalability Team activity: Scaling Metroz Fault Tolerant Distributed Systems Principles Transparency Hardware vs. Software redundancy Tolerating disasters Stateless functional fault tolerance Stateful fault tolerance Replication and group consistency Fault tolerance in Spark and Map Reduce Application tolerance for failures Team activity: Identify Metroz component failures and requirements Security and Privacy Principles Privacy Threats Technologies Team activity: identify threats and security mechanisms in Metroz Deployment Cluster sizing and evolution On-premise vs. Cloud Edge computing Team activity: select deployment for Metroz Technology Selection HDFS HBase Kudu Relational Database Management Systems Map Reduce Spark, including streaming, SparkSQL and SparkML Hive Impala Cloudera Search Data Sets and Formats Team activity: technologies relevant to Metroz Software Architecture Architecture artifacts One platform or multiple, lambda architecture Team activity: produce high level architecture, selected technologies, revisit vertical slice Vertical Slice demonstration Additional course details: Nexus Humans Big Data Architecture Workshop 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 Big Data Architecture Workshop 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 Data Modelers Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Dynamic Cubes Define and differentiate Dynamic Cubes Dynamic Cubes characteristics Examine Dynamic Cube requirements Examine Dynamic Cube components Examine high level architecture IBM Cognos Dynamic Query Review Dimensional Data Structures Dynamic Cubes caching Create & Design a Dynamic Cube Explore the IBM Cognos Cube Designer Review the cube development process Examine the Automatic Cube Generation Manual development overview Create dimensions Model the cube Best practice for effective modeling Deploy & Configure a Dynamic Cube Deploy a cube Explore the Estimate Hardware Requirements Identify cube management tasks Examine Query Service administration Explore Dynamic Cube properties Schedule cube actions Use the DCAdmin comment line tool Advanced Dynamic Cube Modelling Examine advanced modeling concepts Explore modeling caveats Calculated measures and members Model Relative Time Explore the Current Period property Define period aggregation rules for measures Advanced Features of Cube Designer Examine multilingual support Examine ragged hierarchies and padding members Define Parent-Child Dimensions Refresh Metadata Import Framework Manager packages Filter measures and dimensions Optimize Performance with Aggregates Identify aggregates and aggregate tables In-memory aggregates Use Aggregate Advisor to identify aggregates User defined in-memory aggregates Optimize In-Memory Aggregates automatically Aggregate Advisor recommendations Monitor Dynamic Cube performance Model aggregates (automatically vs manually) Use Slicers to define aggregation partitions Define Security Overview of Dynamic Cube security Identify security filters The Security process - Three steps Examine security scope Identify scope rules Identify roles Capabilities and access permissions Cube security deep dive Model a Virtual Cube Explore virtual cubes Create the virtual cube Explore virtual cube objects Examine virtual measures and calculated members Currency conversion using virtual cubes Security on virtual cubes Introduction to IBM Cognos Analytics Define IBM Cognos Analytics Redefined Business Intelligence Self-service Navigate to content in IBM Cognos Analytics Interact with the user interface Model data with IBM Cognos Analytics IBM Cognos Analytics components Create reports Perform self-service with analysis and Dashboards IBM Cognos Analytics architecture (high level) IBM Cognos Analytics security Package / data source relationship Create Data modules Upload files Additional course details: Nexus Humans B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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.