26 Courses in Liverpool delivered Live Online

This module aims to develop knowledge and understanding of the use of customs warehousing in the export and in import of goods. This includes the use of duty deferral, temporary storage, the processing of merchandise, bonded stock, consolidation and special processes and services.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

This module aims to develop knowledge and understanding of the role of logistics including an understanding of air, sea, road and rail freight and courier services. It will explore the advantages and disadvantages of using the different modes of transport the world of international trade.

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Program/Project Managers, Technology Consultants, and Users. In this course, students will gain SAP Netweaver Business Warehouse knowledge necessary for successful implementation and administration within a heterogeneous SAP NetWeaver BW system landscape. Data Warehousing Describing Data Warehouse Systems Describing Data Warehouse Architecture Using the Data Warehousing Workbench Master Data Modeling in SAP BW Describing InfoObjects Creating Characteristic InfoObjects The Loading of Master Data from SAP Data Sources Describing Data Flow Modeling a Master Data Flow Loading a Master Data Flow Modeling with the Graphical Data Flow Tool Loading of Transaction Data from SAP DataSources Describing the Core InfoProviders Creating a Key Figure InfoObject Creating a DataStore Object (DSO) Loading Transaction Data into a Data Store Object Describing the Extended Star Schema of an InfoCube Creating InfoCubes Loading Transaction Data into an InfoCube Master Data Loading from Flat File Data Sources Loading Data From a Flat File Describing the Data Flow in Detail Describing the Data Loading Process in Detail InfoProviders in SAP BW Explaining the InfoProviders Used in SAP BW ? Introduction Creating MultiProviders Usage of SAP BI Content Using BI Content Query Performance Optimization Optimizing Query Performance Monitoring Performance Creating and Filling Aggregates The SAP BW Administration Describing Administrative Tasks and Tools Administrating the InfoCubes Administrating the DataStore Objects Creating Process Chains

Duration 1 Days 6 CPD hours This course is intended for The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Overview Describe core data concepts Identify considerations for relational data on Azure Describe considerations for working with non-relational data on Azure Describe an analytics workload on Azure In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization. 1 - Explore core data concepts Identify data formats Explore file storage Explore databases Explore transactional data processing Explore analytical data processing 2 - Explore data roles and services Explore job roles in the world of data Identify data services 3 - Explore fundamental relational data concepts Understand relational data Understand normalization Explore SQL Describe database objects 4 - Explore relational database services in Azure Describe Azure SQL services and capabilities Describe Azure services for open-source databases 5 - Explore Azure Storage for non-relational data Explore Azure blob storage Explore Azure DataLake Storage Gen2 Explore Azure Files Explore Azure Tables 6 - Explore fundamentals of Azure Cosmos DB Describe Azure Cosmos DB Identify Azure Cosmos DB APIs 7 - Explore fundamentals of large-scale data warehousing Describe data warehousing architecture Explore data ingestion pipelines Explore analytical data stores 8 - Explore fundamentals of real-time analytics Understand batch and stream processing Explore common elements of stream processing architecture Explore Azure Stream Analytics Explore Apache Spark on Microsoft Azure 9 - Explore fundamentals of data visualization Describe Power BI tools and workflow Describe core concepts of data modeling Describe considerations for data visualization

Duration 2 Days 12 CPD hours This course is intended for Oacle Database Administrators System Administrators Developers Overview Understand the concept, benefits, configuration, and usage of the new features and enhancements in database overall area Understand the concept, benefits, configuration, and usage of the new features and enhancements in the security area Understand the concept, benefits, configuration, and usage of the new features and enhancements in the availability area Understand the concept, benefits, configuration, and usage of the new features and enhancements in the performance area Understand the concept, benefits, configuration, and usage of the new features and enhancements in big data and data warehousing area Understand the concept, benefits, configuration, and usage of the new features and enhancements in diagnosability area Understand the concept, benefits, configuration, and usage of the new features and enhancements in sharding area The course provides the Oracle Database 19c new features and enhancements related to database overall, security, availability, performance, data warehousing, and diagnosability. In the lessons, you learn the new and enhanced features of Oracle Database 19c amongst different areas such as database overall, security, availability, performance, big data and warehousing, and diagnosability. Using General Database Overall EnhancementsUsing Security EnhancementsUsing Availability EnhancementsUsing Performance EnhancementsUsing Big Data and Data Warehousing EnhancementsUsing Diagnosability EnhancementsSharding Enhancements

Duration 2 Days 12 CPD hours This course is intended for This course is intended for experienced Oracle Database Administrators, System Administrators, and Developers. Overview Upon completion of this course, the student should be able to: Understand the concept, benefits, configuration, and usage of the new features and enhancements in database overall area, security area, availability area, performance area, big data and data warehousing area and enhancements in diagnosability area and in sharding area. The course provides the Oracle Database 19c new features and enhancements related to database overall, security, availability, performance, data warehousing, and diagnosability. The course provides the Oracle Database 19c new features and enhancements related to database overall, security, availability, performance, data warehousing, and diagnosability.

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Business Intelligence: Virtual In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Duration 2 Days 12 CPD hours This course is intended for Application Consultant Business Analyst Business Process Architect Business Process Owner / Team Lead / Power User Developer Enterprise Architect Solution Architect Trainer Overview This course will prepare you to: Understand the basic concepts of SAP data warehousing Position the value-added of SAP Data Warehouse Cloud Integrate on-premise SAP Sources Model in SAP Data Warehouse Cloud Consume Data in SAP Analytics Cloud This course will prepare you to:Understand the basic concepts of SAP data warehousingPosition the value-added of SAP Data Warehouse CloudIntegrate on-premise SAP SourcesModel in SAP Data Warehouse CloudConsume Data in SAP Analytics Cloud Course Outline Getting started with data warehousing and the training environment Short introduction in SAP BW Bridge and other sources SAP Data Warehouse Cloud: -Introducing SAP Data Warehouse Cloud -Describing Spaces, integration options, operations and best practices -Introducing modeling in the Data Builder -Introducing modeling the Business Layer Describing consumption options in SAP Analytics Cloud Additional aspects in SAP Data Warehouse Cloud Outlook and roadmap Additional course details: Nexus Humans DSP01 SAP Introduction to SAP Data Warehouse Cloud 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 DSP01 SAP Introduction to SAP Data Warehouse Cloud 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.