63 Business Intelligence (BI) courses in Sheffield delivered Live Online

OVERVIEW Prerequisites—this is a day of supervised revision for anyone who wishes to take the PL-300 exam so we expect you to have attended a PL-300 course, either taught or on your own, before attending this day of revision. We are happy for attendees to join the course if you have taken the PL-300 with us or with another provider. In the morning we look at questions from the PL-300 exam, grouped by subject area. For each question we show you the correct answer and then explain why that is the correct answer. After lunch everyone tries a practice exam under exam conditions and we finish the day with clarification on the subjects or specific questions that the class is finding hard. The cost of the course includes a free voucher to take the exam, so please don’t buy your own separately. If you do so we cannot reimburse you with the cost of the exam. COURSE BENEFITS: Discover the parts of the course on which to focus most attention Become familiar with the styles and formats of the exam questions Alert yourself to some of the particularly tricky questions Familiarise yourself with the style of the 'case study' question Practice an exam under real exam conditions Get a feel for the time you need to devote to the normal questions and to the case study WHO IS THE COURSE FOR? Power BI report developers who need PL-300 Certification to apply for a job Business Intelligence specialists who wish to enhance their career prospects with a PL-300 Certification Anyone who wishes to maximise their chances of passing the PL-300 Power BI Data Analyst exam COURSE OUTLINE Module 1 Structure Of The Exam Registration for the exam and setup of your workspace The percentage of marks devoted to each subject area Types of questions used in the exam Advised timing for the normal questions and for the case study question Module 2 Individual Exam Question Practice The exam questions are divided into subject areas and for each question… We consider the question and try to answer it We view the answer Where necessary, we look at an in-depth explanation of why that is the correct answer Examine case study questions and how to treat these differently from the normal questions Module 3 Practice Exam Under Exam Conditions Attendees take a practice exam Attendees receive a mark, broken down into subject areas Module 4 Exam Question Practice Focussed On Tricky Areas Together, based on the results of attendees’ exam results we decide which areas on which to focus More practice on individual exam questions using the same style as in Module 2

SQL Queries Course, 1-Day. Basic SQL syntax. This course is good for any database, covering standard SQL. Most attendees are in-work IT Professional. Private individuals are also very welcome.

Duration 1 Days 6 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who receive Power BI data visualizations and reports from data analysts or from data visualization engineers. These data report recipients want to use the features and capabilities of Power BI to fully explore the visualizations and initial analyses provided to them in reports, perform additional analysis to ask next-level questions of the data, and to customize and create new visualizations and dashboards in order to share new insights and create compelling reports. Overview Explore Power BI reports. Analyze data to get answers and insights. Sort and group data for analysis and reporting. Filter visualizations. Prepare reports. Troubleshoot, collaborate, and share reports. As data acquisition, access, analysis, and reporting are interwoven with our businesses and lives, more and more data is collected about business and personal activities. This abundance of data and the computing power to analyze it has increased the use of data analysis and data visualization across a broad range of job roles. Decision makers of all types, including managers and executives, must interact with, interpret, and develop reports based on data and analysis provided to them. Microsoft Power BI software is designed for data analysis and the creation of visualizations. Data analysts prepare data, perform initial analysis, and create visualizations that are then passed to business data decision makers. These decision makers can use Power BI's tools to explore the data, perform further analysis to find new insights, make decisions, and create customized reports to share their findings. Prerequisites To ensure your success in this course, you have experience managing data with Microsoft Excel or Google Sheets 1. Exploring Power BI Reports Topic A: Data Analysis Workflow with Power BI Topic B: Explore Reports in the Power BI Service Topic C: Edit Reports 2. Analyzing Data to Get Answers and Insights Topic A: Configure Data Visualizations Topic B: Ask New Questions by Changing Aggregation Topic C: Find Answers with Calculations 3. Sorting and Grouping Data for Analysis and Reporting Topic A: Sort Data Topic B: Group Data 4. Filtering Visualizations Topic A: Filter Data to Refine Analysis Topic B: Create Slicers for Reports 5. Preparing Reports Topic A: Format and Annotate Reports Topic B: Emphasize Data in Reports 6. Troubleshooting, Sharing, and Collaborating Topic A: Troubleshoot Data Issues Topic B: Collaborate in Power BI Topic C: Collaborate with Non-Power BI Users

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