Business Analytics: Data and Decisions

This DIXONTECH course bridges the gap between data analysis and strategic business decision-making. Participants will explore analytical models, business data interpretation, and quantitative decision tools that enhance performance and innovation. The course integrates key elements of business intelligence, data-driven management, and predictive decision-making, ensuring professionals can turn data insights into measurable organizational outcomes.

TRAINING TOPICS:

• Fundamentals of Business Analytics

• Data Analysis for Strategic Decisions

• Quantitative and Statistical Decision Models

• Business Intelligence Tools and Dashboards

• Applying Analytics for Organizational Growth

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

By the end of this DIXONTECH training, participants will:

• Understand business analytics processes and frameworks

• Use analytical tools for decision-making and forecasting

• Build quantitative models for business problems

• Interpret and visualize business data effectively

• Integrate analytics into strategic planning

• Improve decision accuracy using data insights

• Develop a data-driven culture within their organization

TRAINING IS TAILORED TO:

This course is designed for:

• Business and data analysts

• Department heads and decision-makers

• Financial and operations managers

• Strategy and planning professionals

• Project and process improvement leaders

• Consultants and business advisors

• Anyone seeking to use data for better decisions

TRAINING METHODOLOGY:

DIXONTECH uses a practical, application-focused methodology. The course combines instructor-led sessions, case studies, and real-world data simulations. Participants engage in modeling exercises, dashboard creation, and decision analysis labs to build tangible business analytics capabilities applicable in any organizational context.

DAY 1: Fundamentals of Business Analytics

• Understanding the role of business analytics

• Linking data analysis to organizational objectives

• Key components of the analytics process

• Analytical thinking for business professionals

• Types of business analytics (descriptive, predictive, prescriptive)

• Data sources and business data structures

• Building the foundation for data-based decisions

DAY 2: Data Analysis for Strategic Decisions

• Gathering and preparing business data

• Statistical techniques for data analysis

• Data interpretation and insight extraction

• Identifying business performance indicators

• Using Excel and Power BI for analysis

• Data correlation and trend evaluation

• Translating data findings into business strategy

DAY 3: Quantitative and Statistical Decision Models

• Decision-making under uncertainty and risk

• Linear programming and optimization basics

• Cost-benefit and sensitivity analysis methods

• Scenario planning using analytical models

• Simulation models for business forecasting

• Regression and time-series analysis applications

• Practical modeling exercise: resource allocation case

DAY 4: Business Intelligence Tools and Dashboards

• Overview of BI tools and platforms

• Designing and implementing dashboards

• Data visualization for business storytelling

• Integrating analytics with KPIs and scorecards

• Using Power BI, Tableau, and Excel dashboards

• Real-time reporting and automation concepts

• Case study: executive performance dashboard design

DAY 5: Applying Analytics for Organizational Growth

• Embedding analytics into business processes

• Developing data-driven decision cultures

• Measuring performance and forecasting outcomes

• Predictive analytics for business strategy

• Ethics, data privacy, and compliance issues

• Presenting analytical recommendations to executives

• Final project: business decision analytics case study