172 Business Analysis courses in Cardiff delivered Live Online

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 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Data modelling and visualisation skills are in demand! Create Interactive Reports and Dashboards.

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, and Users. Overview Learn how to create queries in BEx Query DesignerLearn how to use advanced query functionsLearn how to perform OLAP analysis In this course, students obtain the knowledge to create query definitions using the BEx Query Designer and to make them available for OLAP analysis. Data Warehousing Describing Data Warehousing Describing Data Warehouse Architecture Using Reporting Tools Navigation Options in Reports Using the Navigation Options in Reports Saving Analysis Views Simple Queries Creating Simple Queries Finding a Query Filtering Query Definition Data Configuring Query Properties Key Figures and Structures in Queries Creating Restricted Key Figures Creating Calculated Key Figures Creating a New Formula with Boolean Operators Configuring Properties of Key Figures Using Exception and Nested Exception Aggregation Queries with Multiple Structures Creating Structures Resolving Formula Collision Designing Detailed Queries with the Cell Editor Characteristics and Hierarchies in Queries Configuring the Properties of Characteristics Running Display and Navigation Attribute Queries Adding Hierarchies to Reports Adding External Hierarchies to a Report Using Hierarchies and Structures Creating External Hierarchies Variables in Queries Using Variables Creating Characteristic Value and Text Variables in Queries Creating Hierarchy and Hierarchy Node Variables in Queries Creating Formula Variables in Queries Activating Business Content Variables Exceptions and Conditions in Queries Creating Exceptions in Query Design Creating Conditions in Query Design Report-Report Interface Using the Report-Report Interface Query Performance Optimization Optimizing Query Performance Configuring Query Read Mode Use Performance Monitoring Tools Queries Management and Authorizations Overview Managing Query Objects Describing Authorizations Reporting Options Outlining Reporting Options for SAP NetWeaver BW Additional course details: Nexus Humans BW305 SAP Business Warehouse Query Design and 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 BW305 SAP Business Warehouse Query Design and 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.

We offer the most advanced “Certified Six Sigma Green Belt Course” as per the curriculum outline of The ASQ Body of Knowledge and accredited by top international Lean & Six Sigma accreditation bodies. Six Sigma Green Belt Deliverables: 22+ hours of Instructor-led interactive virtual classroom session on the weekend Access to 45+ hours of Module based Six Sigma lectures via LMS 100+ Toolkits and Project Templates for Analysis and Implementation Soft copy of Lean Six Sigma Green Belt Body of Knowledge Live Data-oriented project, with Scenario and Analysis Methodology 20+ Dummy Projects and Case studies for Lean Six Sigma Application Support via subject expert through telephonic discussion on the weekend Sample Questions and Examination Guide for Certification Preparation Pre and Post assignments for process groups and knowledge areas Project implementation support and Data visualization using MINITAB PRO CLSSGB certification examination anytime within the 90 days course duration Certification Validation Tool for third-party credentials validation PARTICULARS Duration (Hours) 1. Define Phase 22 2. Measure Phase 14 3. Analyse Phase 20 4. Improve Phase 7 5. Control Phase 7 Total Duration 70 (Hours) Introduction Become an expert in six sigma methodology by getting hands-on knowledge on DMAIC, Project Charter, Process Capability, FMEA, Sigma calculation, Test of Hypothesis, Control Charts, VSM, JIT using real case scenarios and real-life examples. Lean and DMAIC methodologies using live projects. The Six Sigma Certification is accredited by The Council for Six Sigma Certification. The certification also acknowledges the BOK outline of The American Society for Quality, USA. The course features world-class content with live projects and MINITAB PRO driven data analysis training with end to end support in project implementation by Master Black Belt Experts and Trainers. What is Six Sigma Certification? A person with Six Sigma certification has problem-solving abilities. Someone may gain Green Belt, Black Belt or Master Black Belt certification. The higher certification one attains, the more is the ability to solve complex organizational problems. Six Sigma certification is a process of individual’s knowledge validation using a classification system, generally referred to as "Belts" (Green Belt, Black Belt, Master Black Belt) This verification test individual commands over six sigma methodology and tools. The belt classification shows the position these certified individuals would occupy in an organizational structure and job roles. Six Sigma Green Belt training is especially for the future project leaders of Lean Six Sigma projects. We deliberately mix non-profit with profit participants. There will then be fun, useful discussions and knowledge exchanges during the training sessions. In addition, there are also many self-employed people who follow the LSS Green Belt training to increase their expertise as in a trimmer. What do you do to get the Six Sigma Green Belt certificate? Our Six Sigma Green Belt training consists of a number of components: Training: in an intensive training program you learn the background of Lean and Six Sigma and we put what we have learned into practice with different simulations. Extra: With our Body of Knowledge and whitepapers you place what you have learned in a theoretical framework. The program also contains various homework assignments, in which we focus, among other things, on the use of MINITAB PRO. Follow-up: During the training, you will receive an access code to an e-learning module. You can pass the substance again in an interactive way. Exam: On the last training day you will make the CLSSGB Green Belt exam. If you succeed, you will immediately receive the official Certified Lean Six Sigma Green Belt certification. Global Recognition of Your Certification: Agenda Overview of Six Sigma and the organizationSix Sigma and organizational goalsValue of six sigmaOrganizational goals and six sigma projectsOrganizational drivers and metricsLean principles in the organizationLean conceptsValue-streaming mappingDesign for six sigma (DFSS) methodologiesRoadmaps for DFSSBasic failure mode and effects analysis (FMEA)Design FMEA and process FMEA Define PhaseProject identificationProject SelectionProcess elementsBenchmarkingProcess inputs and outputsOwners and stakeholders Voice of the customer (VOC) Customer identificationCustomer dataCustomer requirements Project Management Basics Project charterProject scopeProject metricsProject planning toolsProject documentationProject risk analysisProject closureManagement and planning toolsBusiness results for projectsProcess performance CommunicationTeam dynamics and performanceTeam stages and dynamicsTeam roles and responsibilitiesTeam toolsTeam Communication Measure PhaseProcess analysis and documentationProbability and statisticsBasic probability conceptsCentral limit theorem, Statistical distributions, Collecting and summarizing dataTypes of data and measurement scalesSampling and data collection methodsDescriptive statisticsGraphical methodsMeasure Phase (contd E. Measurement system analysis (MSA) F. Process and performance capabilityProcess performance vs. process specificationsProcess capability studiesProcess capability (Cp, Cpk) and process performance (Pp, Ppk) indicesShort-term vs. long-term capability and sigma shift Analyze PhaseExploratory data analysisMulti-vari studiesCorrelation and linear regression B, Hypothesis testingBasics Tests for means, variances, and proportionsIntroduction to MINITAB Data analysis Improve Phase of Six SigmaDesign of experiments (DOE)Basic terms, DOE graphs, and plotsThe root cause analysisLean Tools 1. Waste elimination 2. Cycle-time reduction 3. Kaizen and kaizen blitz V1. Control PhaseStatistical process control (SPC)SPC BasicsRational subgroupingControl chartsControl planLean tools for process controlTotal productive maintenance (TPM)Visual factory Project Implementation & SupportMINITAB Practice and guidance for projectProject implementation supportTemplates and Toolkits application for Project workSupport on Data Project, Implementation and project completion BenefitsFrom the course Learn the principles and philosophy behind the Six Sigma technique Learn to apply statistical methods to improve business processes Design and implement Six Sigma projects in a practical scenario Learn the DMAIC process and various tools used in Six Sigma methodology Knowledge of Six Sigma Green Belt Professional enables you to understand real-world business problems, increase an organization's revenue by streamlining the process, and become an asset to an organization According to Villanova University, employers such as United Health Group, Honeywell, GE and Volkswagen have been actively seeking professionals with Six Sigma to fill a variety of positions The Training enhances your skills and enables you to perform roles like Quality Manager, Quality Analyst, Finance Manager, Supervisor, Quality Control, etc. According to Indeed.com, the national average salary for a Six Sigma Green Belt is $72,000 per year in the United States.   From the workshop Instructor LED training by Six Sigma Black Belt and Master Belt experts to make candidate learn the real scenario of six sigma tools and methodology Learn the principles and philosophy behind the Six Sigma method Dummy project by instructors to make candidate get a hands-on six sigma projects Downloadable Six Sigma PPT & Six Sigma PDF Industry Based case studies High-Quality training from an experienced trainer The Program extensively uses Minitab, specialized statistical software. It provides you with a thorough knowledge of Six Sigma philosophies and principles (including supporting systems and tools). Know about six sigma certification cost and six sigma green belt certification cost. Who should attend? The Six Sigma program is designed for professionals and students who want to develop the ability to lead process improvement initiatives. Six Sigma tools and process is widely used in all business processes. Six Sigma is applicable in all industry and in all functional areas. An indicative list of participants in our Green Belt program could include: Financial/business analyst Commodity manager Project manager Quality manager Production manager Production Engineer Business development manager Manufacturing process engineer Continuous improvement director Business managers or consultants Project manager/Program Manager Director or VP of operations CEO, CFO, CTO Certification On successful completion of the course and course requisites, the candidate will receive Internationally recognized Six Sigma Green Belt Certification. This course offers Six Sigma Certification Validation Tool for Employers Your Six Sigma Certification Validation Tool can be used by employers, clients and other stakeholders to validate the authenticity of your Six Sigma Certifications you have received. Using the programming code located on your certified LSSGB certification, one can see all your training and certification details online.

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 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.

In this half-day virtual 1-2-1 session with Dan – you will have your coaching business analysed and dissected by Dan.  After a comprehensive Q&A, which will be completed before the day, Dan will honestly discuss the strengths, weaknesses and opportunities for each of the key ‘business’ aspects of your coaching business.  This includes looking at all your systems (or where there should be systems), operational management, Finances (including cash flow, accounts and budgeting) KPIs, Marketing plans, referral systems and any Sales funnels.  His advice will align with your ambitions and will give you the practical insights, unpleasant truth bombs and encouragement you need to have a healthy, thriving business.

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 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