169 Business Analytics & Intelligence courses in Whetstone delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 2 Days 12 CPD hours This course is intended for This course is relevant to anyone who needs to work with and understand data including: Business Analysts, Data Analysts, Reporting and BI professionals Marketing and Digital Marketing professionals Digital, Web, e-Commerce, Social media and Mobile channel professionals Business managers who need to interpret analytical output to inform managerial decisions Overview This course will cover the basic theory of data visualization along with practical skills for creating compelling visualizations, reports and dashboards from data using Tableau. Outcome: After attending this course delegates will understand - How to move from business questions to great data visualizations and beyond How to apply the fundamentals of data visualization to create informative charts How to choose the right visualization type for the job at hand How to design and develop basic dashboards in Tableau that people will love to use by doing the following: Reading data sources into Tableau Setting up the roles and data types for your analysis Creating new data fields using a range of calculation types Creating the following types of charts - cross tabs, pie and bar charts, geographic maps, dual axis and combo charts, heat maps, highlight tables, tree maps and scatter plots Creating Dashboards that delight using the all of the features available in Tableau. 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 tourism. From Business Questions to Data Visualisation and Beyond The first step in any data analysis project is to move from a business question to data analysis and then on to a complete solution. This section will examine this conversion emphasizing: The use of data visualization to address a business need The data analytics process ? from business questions to developed dashboards Introduction to Tableau ? Part 1 In this section, the main functionality of Tableau will be explained including: Selecting and loading your data Defining data item properties Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations Creating basic visualizations Creating a basic dashboard Introduction to Tableau ? Part 2 In this section, the main functionality of Tableau will be explained including: Selecting and loading your data Defining data item properties Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations Creating basic visualizations Creating a basic dashboard Key Components of Good Data Visualisation and The Visualisation Zoo In this section the following topics will be covered: Colour theory Graphical perception & communication Choosing the right chart for the right job Data Exploration with Tableau Exploring data to answer business questions is one of the key uses of applying good data visualization techniques within Tableau. In this section we will apply the data visualization theory from the previous section within Tableau to uncover trends within the data to answer specific business questions. The types of charts that will be covered are: Cross Tabs Pie and bar charts Geographic maps Dual axis and combo charts with different mark types Heat maps Highlight tables Tree maps Scatter plots Introduction to Building Dashboards with Tableau In this section, we will implement the full process from business question to final basic dashboard in Tableau: Introduction to good dashboard design Building dashboards in Tableau

Duration 2 Days 12 CPD hours This course is intended for Administrators Overview Please refer to course overview This offering covers the fundamental concepts of installing and configuring IBM Cognos Analytics, and administering servers and content, in a distributed environment. In the course, participants will identify requirements for the installation and configuration of a distributed IBM Cognos Analytics software environment, implement security in the environment, and manage the server components. Students will also monitor and schedule tasks, create data sources, and manage and deploy content in the portal and IBM Cognos Administration. Introduction to IBM Cognos Analytics administration IBM Cognos Analytics components Administration workflow IBM Cognos Administration IBM Cognos Configuration Identify IBM Cognos Analytics architecture Features of the IBM Cognos Analytics architecture Examine the multi-tiered architecture, and identify logging types and files Examine IBM Cognos Analytics servlets Performance and installation planning Balance the request load Configure IBM Cognos Analytics Secure the IBM Cognos Analytics environment Identify the IBM Cognos Analytics security model Define authentication in IBM Cognos Analytics Define authorization in IBM Cognos Analytics Identify security policies Secure the IBM Cognos Analytics environment Administer the IBM Cognos Analytics server environment Administer IBM Cognos Analytics servers Monitor system performance Manage dispatchers and services Tune system performance, and troubleshoot the server Audit logging Dynamic cube data source administration workflow Manage run activities View current, past, and upcoming activities Manage schedules Manage content in IBM Cognos Administration Data sources and packages Manage visualizations in the library Deployment Other content management tasks Examine departmental administration capabilities Create and manage team members Manage activities Create and manage content and data Manage system settings Manage Themes, Extensions, and Views Share services with multiple tenants

Duration 2 Days 12 CPD hours This course is intended for Administrators Overview Please refer to course overview This offering covers the fundamental concepts of installing and configuring IBM Cognos Analytics, and administering servers and content, in a distributed environment. In the course, participants will identify requirements for the installation and configuration of a distributed IBM Cognos Analytics software environment, implement security in the environment, and manage the server components. Students will also monitor and schedule tasks, create data sources, and manage and deploy content in the portal and IBM Cognos Administration. Introduction to IBM Cognos Analytics administration IBM Cognos Analytics components Administration workflow IBM Cognos Administration IBM Cognos Configuration Identify IBM Cognos Analytics architecture Features of the IBM Cognos Analytics architecture Examine the multi-tiered architecture, and identify logging types and files Examine IBM Cognos Analytics servlets Performance and installation planning Balance the request load Configure IBM Cognos Analytics Secure the IBM Cognos Analytics environment Identify the IBM Cognos Analytics security model Define authentication in IBM Cognos Analytics Define authorization in IBM Cognos Analytics Identify security policies Secure the IBM Cognos Analytics environment Administer the IBM Cognos Analytics server environment Administer IBM Cognos Analytics servers Monitor system performance Manage dispatchers and services Tune system performance, and troubleshoot the server Audit logging Dynamic cube data source administration workflow Manage run activities View current, past, and upcoming activities Manage schedules Manage content in IBM Cognos Administration Data sources and packages Manage visualizations in the library Deployment Other content management tasks Examine departmental administration capabilities Create and manage team members Manage activities Create and manage content and data Manage system settings Manage Themes, Extensions, and Views Share services with multiple tenants

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?

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Duration 2 Days 12 CPD hours This course is intended for This course is suited to marketeers, business analysts, and researchers who are interested in increasing their statistical knowledge. Overview After attending this course, delegates will understand how statistics can be used to provide valuable insight into their business, and be able to apply statistical methods to solve business problems. On returning to work delegates will immediately be able to make a difference to the way that their organisations make decisions. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Course Outline The course will explore the following topics through a series of lectures and workshops: Summary statistics for both continuous data and categorical data Using and reporting confidence intervals Using hypothesis tests to answer business questions Using correlations to explore data relationships Simple prediction models Analysing categorical data Additional course details: Nexus Humans Data-driven Business Using Statistical Analysis 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 Data-driven Business Using Statistical Analysis 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 This course is primarily for Application Consultants, Business Analysts, Business Process Owners/Team Leaders/Power Users, and Developer Consultants. Overview At course completion students will know- The basic functions and navigation options of BusinessObjects Analysis for Microsoft Office- The special functions and layout design options of BusinessObjects Analysis for Microsoft Office In this course, students learn the basic functions and navigation options of the Analysis edition for Microsoft Office. Students will also learn the special functions and layout design options of Analysis. Components and Data Sources for Analysis Using Analysis Components and Data Sources Customization for Workbook Data Analysis Using the Basic Components of Analysis Sorting and Filtering Workbook Members Filtering Selected Workbook Members by Measure for Enhanced Analysis Using Hierarchies for Data Analysis in Workbooks Using Inserted Components to Add Workbook Functionality Configuring Filter Components Using Formulas to Enhance the Workbook Layout Defining Conditional Formatting Options for Workbooks Using a Prompting Dialog in Workbook Queries Extending Workbook Display Options with Functions and Microsoft Excel VBA Using Styles to Customize Workbook Appearance Setting Preferences to Control Workbook Behavior Publishing Analysis Documents to the BI Platform Server Presentation of Workbook Analysis Data Presenting Analysis Data for Business Users Additional course details: Nexus Humans BOAN10 SAP BusinessObjects Analysis for Microsoft Office 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 BOAN10 SAP BusinessObjects Analysis for Microsoft Office 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 5 Days 30 CPD hours This course is intended for This course is designed for business analysts. Overview After completing this course, you should be able to:Describe the benefits of implementing an Operational Decision Manager solution, and the collaboration that is required between the business and development teamsIdentify the main user roles that are involved in designing and developing an Operational Decision Manager solution, and the tasks that are associated with each roleExplain modeling concepts and the UML notation that is relevant to modeling for business rules and eventsDefine and implement object models for business rulesSet up the rule authoring environment in Designer by working with decision services and synchronizing across development and business environmentsCustomize the vocabulary that is used in rulesDiscover and analyze business rules for implementationUse the Operational Decision Manager rule editors to author business rules and decision tablesRun tests and simulations in the Decision Center Enterprise console to validate decision logic and rule changesExplain governance issues and work with Operational Decision Manager features that support decision governance This course introduces business analysts to IBM Operational Decision Manager V8.7.1. You learn the concepts and skills that are necessary to capture, author, validate, and manage business rules with Operational Decision Manager. Course Outline Course introduction Introducing IBM Operational Decision Manager V8.7.1 Exercise: Operational Decision Manager in action Modeling for business rules Exercise: Building the model on paper Exercise: Implementing the model Understanding decision services Exercise: Setting up a decision service Working with the BOM Exercise: Working with the BOM Introducing Decision Center Exercise: Exploring the Decision Center Business console Exercise: Exploring the Decision Center Enterprise console Introducing rule authoring Exercise: Understanding the case study Discovering and analyzing rules Exercise: Discovering rules Exercise: Analyzing rules Working with conditions in rules Exercise: Working with conditions in rules Working with definitions in rules Exercise: Working with definitions in rules Writing complete rules Exercise: Writing complete rules Authoring decision tables and trees Exercise: Authoring decision tables and trees Exercise: Authoring rules: Putting it all together Running tests and simulations in the Enterprise console Exercise: Running tests and simulations in the Enterprise console Introducing decision governance Exercise: Working with the decision governance framework Course summary

Duration 2 Days 12 CPD hours This course is intended for It is appropriate for Managers, Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, managers; supervisors, team leaders, and process operators. Overview Describe business process improvement (BPI) business drivers.Plan, manage and close requirements for a Business Process Improvement project Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Apply a methodology to business process improvement projects. This 2-day course aims at introducing its attendees to the core values, principles, and practices of Business Process Improvement. Introduction - A Business Process Improvement (BPI) Overview Why are we here today? What is BPI? Benefits of BPI Specific challenges/obstacles and successes Process improvement examples: Industry specific examples Famous debacles to avoid and successes to emulate Your role in helping to identify problems Overview of the Joiner 7-Step Method What is the Joiner 7-Step Method? Walkthrough of the Joiner 7-Step Method Template: Introduce and review Process Improvement Template Case Study Exercise: Read and discuss introduction to the Case Study Step #1: Initiate the Project Types of business problems typically encountered at insurance companies and banks How to recognize a business-related problem Identifying the gaps (delta between current and future states) Ownership of the project and the business problem Defining measurable success criteria Case Study Exercise: Complete the Problem Statement section (Step #1) of the template Step #2: Define Current Situation What are symptoms of a problem? Looking for symptoms of the problem Performing Stakeholder Analysis Technique: View a RACI Matrix Defining the impacts caused by the problem Technique: Business Process Modeling (As-Is) Understand how to draw an As-Is Business Process Model Case Study Exercise: Complete the Define Current Situation section (Step #2) of the template Step #3: Identify Root Causes What are root causes? Performing Root Cause Analysis Technique: Fishbone Diagram using the cafeteria example Case Study Exercise: Discuss a Fishbone Diagram Technique: Pareto Chart (discuss and show example) Case Study Exercise: Complete the Identify Root Causes section (Step #3) of the template Step #4: Develop Solutions Identifying options for problem resolution Avoid jumping to conclusions Technique: Brainstorming Case Study Exercise: Conduct a Brainstorming Session Recognizing pros and cons for each option Technique: Kempner-Tregoe (?Must-Have? vs. ?Nice-to-Have?) Case Study Exercise: Determine best solution using a ?simple? Kempner-Tregoe model Case Study Exercise: Complete the Develop Solutions section (Step #4) of the template Step #5: Define Measurable Results Prototyping the solution Technique: Business Process Modeling (To-Be) Measuring results against the success criteria (Step #1) Case Study Exercise: Review changes to an As-Is Business Process Model Case Study Exercise: Complete the Define Measurable Results section (Step #5) of the template Step #6: Standardize Process Defining how the process will be documented Plan and understand organizational readiness Discuss how employees are empowered to identify and act upon their ideas Identifying follow-up needs (i.e., training) for the staff that will be impacted Technique: Communication Plan Case Study Exercise: Complete the Standardize Process section (Step #6) of the template Step #7: Determine Future Plans Monitoring the process for Continuous Process Improvement (The ?Plan-Do-Check-Act? Cycle) Understand how to sustain the improvements made by the Joiner 7-Step Method Technique: PDCA form Case Study Exercise: Complete the Determine Future Plans section (Step #7) of the template Going Forward with a Plan of Action Identifying process problems in your organization Individual Exercise: Name three (3) possible areas for improvement Prioritize and define the next steps Individual Exercise: Using a new template complete Step 2 & Step 3 for one possible area for improvement you have identified