About the Course
Organizations do not need more data for its own sake, they need analysis and information management they can trust, audit, and repeat. In practice, that means you must demonstrate data profiling, data quality control, metadata management, dashboard interpretation, and evidence-backed reporting, often under the expectations of CRISP-DM, COBIT 2019, and ISO/IEC 27001:2022. This course speaks directly to the pressure you face when leaders want fast answers but the underlying dataset is incomplete, duplicated, or poorly governed.
The course turns scattered operational knowledge into a structured working system. You will practice data profiling in Microsoft Excel, build a data quality checklist, map fields into a data dictionary, design a reporting dashboard brief, apply basic descriptive statistics, and draft a governance-ready information workflow using practical templates. You will also be introduced to exploratory data analysis, metadata standards, and automation-aware reporting concepts at an operational level, not as abstract theory. What you will learn: how to clean and structure data, how to analyze it for decision use, and how to package results into clear information products that managers can act on.
This training is built for real constraints such as time pressure, inconsistent source systems, limited analyst capacity, and the need to report across departments with different definitions. It is suitable for professionals who must deliver reliable outputs without waiting for a perfect data environment, and it keeps the focus on methods you can apply immediately in a typical workplace setting.
Target Audience
This course is designed for professionals who manage, analyze, clean, report, or govern data in day-to-day operations.
- Data Analyst responsible for cleaning datasets and producing analysis-ready files
- Information Manager handling data definitions, records, and metadata control
- Business Intelligence Analyst building dashboards and reporting packs from multiple sources
- Reporting Officer validating figures before management or board submission
- Operations Analyst tracking performance metrics and exception trends
- Data Quality Analyst identifying duplicates, gaps, and inconsistent master data
- MIS Specialist maintaining recurring management information reports and data extracts
- Monitoring and Evaluation Officer consolidating survey, program, and performance data
- Records Management Specialist aligning retention, classification, and retrieval practices
- Department Head overseeing evidence-based reporting and data governance priorities
Course Objectives
This course equips you to design, execute, and measure data analysis and information management initiatives that improve reporting reliability, strengthen governance, and support better decisions.
- Assess current data quality using profiling checks, completeness rules, and a data quality scorecard.
- Apply the CRISP-DM workflow to a business dataset for structured analysis and interpretation.
- Design a data dictionary and metadata register for recurring operational reporting.
- Build an Excel-based cleaning workflow for duplicates, missing values, and inconsistent categories.
- Evaluate information controls against COBIT 2019 governance objectives and ISO/IEC 27001:2022 awareness points.
- Navigate cross-functional data ownership, approval paths, and reporting accountability requirements.
- Implement KPI tracking using dashboard logic, descriptive statistics, and automation-aware refresh routines.
- Synthesize findings into an executive-ready insight brief with action points and risk notes.
Requirements & Prerequisites
Prerequisites required: working knowledge of spreadsheets, basic numeracy, and familiarity with everyday reporting or data handling tasks. You should be comfortable opening, filtering, and sorting tabular data in Microsoft Excel or a comparable spreadsheet tool. Coding is not required for completion, although prior exposure to SQL, Power BI, Tableau, or Python for analytics will help you apply the course outputs more quickly. Advanced concepts such as governance design and information architecture are taught at an operational application level, not as technical engineering.
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 data analysis and information management aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on Excel profiling of a real dataset using completeness, uniqueness, and consistency checks.
- Scenario simulation for a month-end reporting delay caused by conflicting source figures.
- Diagnostic review using a data quality checklist and COBIT 2019 governance lens.
- Stakeholder mapping of data owners, approvers, and report consumers across the reporting chain.
- Case study comparison across healthcare, finance, logistics, and public sector reporting environments.
- Group workshop to produce a data dictionary and dashboard brief under time constraints.
- Reflection exercise using benchmark data quality measures and automation-ready reporting practices.
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Data Analysis and Information Management 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 data analysis techniques that top tech companies demand.
- Transform data into actionable insights with real-world case studies.
- Gain proficiency in leading analytical tools to stay ahead in your industry.
Expert Delivery
- Learn from seasoned data scientists with decades of industry experience.
- Interactive sessions ensure you absorb every aspect of data science.
- Small class sizes provide personalized feedback on your progress.
Career Advancement
- Boost your career with a certification recognized by industry leaders.
- Equip yourself with skills that increase your marketability and job security.
- Access exclusive job opportunities through our professional network 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 for dashboarding, KPI tracking, and distributing business reports from cleaned and modeled datasets.
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Tableau SalesforceUsed for visual analysis and interactive reporting when teams need to explore trends and communicate findings clearly.
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Microsoft Excel MicrosoftUsed for data cleaning, reconciliation, ad hoc analysis, and maintaining working data dictionaries in smaller teams.
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SQL Server MicrosoftUsed to query, validate, and join operational data before it is published into reporting layers or dashboards.
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Alteryx Designer AlteryxUsed to automate repeatable data preparation workflows and reduce manual manipulation in recurring reporting processes.
