About the Course
Modern business operations generate vast amounts of data, yet many organizations struggle to extract meaningful insights from their ERP and CRM systems. This course addresses the core challenge of data silos and fragmented reporting by teaching you how to build a unified operations analytics framework. You will learn to navigate the complexities of data cleaning, exploratory data analysis, and statistical modeling within the context of daily business functions. We focus on five critical domain capabilities: demand forecasting accuracy, inventory optimization, lead-time reduction, quality control through statistical process monitoring, and resource utilization mapping. By integrating tools like Microsoft Power BI® and SQL-based querying into your workflow, you move from reactive troubleshooting to proactive strategic management.
The curriculum is structured to take you from foundational data literacy to intermediate predictive modeling. You will practice hands-on data manipulation using real-world operational datasets, while being introduced to advanced concepts like machine learning for anomaly detection at an overview level. This course teaches you how to design scalable reporting systems using the Balanced Scorecard approach and ISO 9001:2015 quality data requirements. We acknowledge the real-world constraints you face, such as legacy system interoperability and data quality issues, and provide specific strategies to maintain analytical integrity under these conditions. You will leave with a toolkit of templates and frameworks that can be immediately applied to improve throughput and reduce operational expenditure.
Target Audience
This program is essential for professionals who manage, analyze, or oversee the physical and digital workflows of a modern enterprise.
This course is designed for:
- Operations Managers responsible for daily throughput and resource allocation
- Supply Chain Analysts optimizing logistics and inventory levels
- Process Improvement Specialists implementing Lean Six Sigma® initiatives
- Production Planners managing manufacturing schedules and capacity
- Quality Assurance Leads monitoring statistical process control metrics
- Business Intelligence Coordinators bridging the gap between IT and operations
- Logistics Supervisors tracking fleet performance and delivery lead times
- Inventory Control Officers reducing carrying costs and stockouts
- Facility Managers overseeing predictive maintenance and utility efficiency
- Operational Excellence Leads driving enterprise-wide digital transformation
Course Objectives
This course equips you to design, execute, and report operations analytics initiatives that improve efficiency, ensure compliance, and support strategic growth.
By the end of this course, you'll be able to:
- Assess operational data maturity using the SCOR® Model framework
- Apply SQL-based querying to extract insights from operational databases
- Build automated KPI dashboards using Microsoft Power BI® or Tableau®
- Calculate safety stock levels using probabilistic demand forecasting models
- Design a statistical process control system to monitor quality variance
- Map end-to-end value streams using data-driven process mining techniques
- Implement a predictive maintenance schedule based on equipment failure data
- Synthesize complex operational findings into executive-level performance reports
Requirements & Prerequisites
Participants should have a foundational understanding of business operations or supply chain management. Proficiency in Microsoft Excel (vlookups, pivot tables) is required. No prior experience with SQL or Power BI® is necessary, as introductory modules are included.
Local Application and Business Return in your market
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn operations data into measurable action and credible reporting.
Methodology includes:
- Hands-on inventory optimization exercise using probabilistic demand datasets
- Scenario simulation requiring resource reallocation during a supply disruption
- Process audit using a Lean Six Sigma® DMAIC checklist
- Stakeholder mapping exercise for cross-functional KPI alignment
- Case study analysis from manufacturing, retail, and logistics sectors
- Group workshop building a live dashboard in Power BI®
- Reflection exercise benchmarking current operations against ISO standards
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Data Analytics for Business Operations Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Skills Relevance
- Master cutting-edge tools to transform data into actionable insights.
- Learn from real-world case studies relevant to today's industries.
- Acquire skills in data visualization and predictive analytics for immediate application.
Expert Delivery
- Courses taught by seasoned data scientists with industry experience.
- Benefit from personalized mentorship and expert-led live sessions.
- Gain insider knowledge from guest lectures by top business analysts.
Career Advancement
- Enhance your resume with certifications recognized by leading companies.
- Equip yourself for roles like Data Analyst, increasing your marketability.
- Access to exclusive job boards and networking groups post-certification.
Tools and platforms relevant to this field
Examples local teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
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Microsoft Power BI MicrosoftUsed to build automated dashboards that track KPIs, compare sites or business units, and refresh operational performance reporting from connected data sources.
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Tableau SalesforceUsed for interactive visual analysis of operational and supply chain data, helping managers spot bottlenecks, trends, and exceptions quickly.
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Alteryx AlteryxUsed to prepare, blend, and automate recurring analytics workflows so analysts can spend less time on manual data wrangling.
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Microsoft Excel MicrosoftUsed for ad hoc analysis, reporting, variance checks, and lightweight forecasting when teams need fast operational decisions.
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SQL Server MicrosoftUsed to query enterprise operational databases and extract trusted data sets for reporting, dashboarding, and analysis.
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Python Python Software FoundationUsed for repeatable analysis, forecasting, and process automation when teams need more flexibility than spreadsheets or BI tools provide.























