Course: Effective Business Decisions Using Data Analysis

Effective Business Decisions Using Data AnalysisID 257Course: Effective Business Decisions Using Data AnalysisThis interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.This course will feature:Discussions on applications of data analytics in managementThe importance of data in data analyticsApplying data analytical methods through worked examplesFocusing on management interpretation of statistical evidenceHow to integrate statistical thinking into the work domainWhat are the Goals?By the end of this course, participants will be able to:Explain the scope and structure of data analytics.Apply a cross-section of useful data analytics.Interpret meaningfully and critically assess statistical evidence.Identify relevant applications of data analytics in practice.Who is this Course for?This course is suitable to a wide range of professionals but will greatly benefit:Professionals in management support rolesAnalysts who typically encounter data / analytical information regularly in their work environmentThose who seek to derive greater decision making value from data analyticsHow will this be Presented?This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands‑on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.The Course ContentDay One :Setting the Statistical Scene in ManagementIntroduction; The quantitative landscape in managementThinking statistically about applications in management (identifying KPIs)The integrative elements of data analyticsData: The raw material of data analytics (types, quality and data preparation)Exploratory data analysis using excel (pivot tables)Using summary tables and visual displays to profile sample dataDay Two :Evidence-based Observational Decision MakingNumeric descriptors to profile numeric sample dataCentral and non-central location measuresExamine the distribution of numeric measures (skewness and bimodal)Exploring relationships between numeric descriptorsBreakdown analysis of numeric measuresDay Three :Statistical Decision Making – Drawing Inferences from Sample DataThe foundations of statistical inferenceQuantifying uncertainty in data – the normal probability distributionThe importance of sampling in inferential analysisSampling methods (random-based sampling techniques)Understanding the sampling distribution conceptDay Four :Statistical Decision Making – Drawing Inferences from Hypotheses TestingThat e r ionale of hypotheses testingThe hypothesis testing process and types of errorsSingle population tests (tests for a single mean)Two independent population tests of meansComparing means across multiple populationsDay Five :Predictive Decision Making - Statistical Modeling and Data MiningExploiting statistical relationships to build prediction-based modelsModel building process – the rationale and evaluation of regression modelsData mining overview – its evolutionDescriptive data mining – applications in managementPredictive (goal-directed) data mining – management applicationsExecutive Dashboarding and Reporting with Power BIAI-Driven Logistics: Enhancing Supply Chain EfficiencyDigital Transformation in the Financial IndustryArtificial Intelligence (AI) in Procurement and Supply Chain ManagementBusiness Data Collection, Analysis and PresentationAt European Quality Training and Management Consultancy, we provide high-quality training and consultancy services to develop future leaders. With a team of skilled experts, we tailor programs to meet the needs of public and private sectors, grounded in quality, ethics, and social responsibility. Our client‑focused approach ensures professionalism and sustainable outcomes.European Quality Training and Management Consultancy FZE#J-18808-Ljbffr