Data Science, AI, and Advanced Analytics Ireland

Data Preparation and Cleaning Training Course

Most data problems aren’t about analysis. They’re about the mess you have to clean up before you even get started. Sound familiar? When you open a file, you may discover duplicates, typos, inconsistent formats, and missing values, which can lead to spending hours cleaning instead of solving problems.

Are you spending more time fixing data than using it? What if your greatest value wasn’t in the models you run, but in the clarity you bring before the first chart is even built? This course gives you the practical skills to handle raw, messy data like a pro and build the clean, trustworthy datasets your work deserves.

Duration
10 Days
Duration
Certificate
Certificate
Included
Delivery
Instructor-Led
Delivery
Level
Foundation To Intermediate
Level
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Training Options

Reserve Your Spot Today — Pay When You're Ready!

Live Online Training

Join from anywhere with interactive virtual sessions

Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Weekend (8 Wks)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Weekend (8 Wks)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700

Classroom Training

In-person sessions at premier locations

Nairobi Kenya
Mon - Fri
10 Days
USD 2,900
Kigali Rwanda
Mon - Fri
10 Days
USD 3,800
Dubai United Arab Emirates (UAE)
Mon - Fri
10 Days
USD 7,800
Zanzibar Tanzania
Mon - Fri
10 Days
USD 4,300
Customized Content
Team Training
Flexible Dates

In-person training at our premier venues — pick a city and date that works for you.

Location Duration Fee Language
Nairobi, Kenya Mon - Fri (10 Days) USD 2,900 English See dates & reserve →
Kigali, Rwanda Mon - Fri (10 Days) USD 3,800 English See dates & reserve →
Dubai, United Arab Emirates (UAE) Mon - Fri (10 Days) USD 7,800 English See dates & reserve →
Zanzibar, Tanzania Mon - Fri (10 Days) USD 4,300 English See dates & reserve →
Addis Ababa, Ethiopia Mon - Fri (10 Days) USD 4,900 English See dates & reserve →
Mombasa, Kenya Mon - Fri (10 Days) USD 3,200 English See dates & reserve →
Cape Town, South Africa Mon - Fri (10 Days) USD 7,500 English See dates & reserve →
Johannesburg, South Africa Mon - Fri (10 Days) USD 6,000 English See dates & reserve →
Pretoria, South Africa Mon - Fri (10 Days) USD 5,900 English See dates & reserve →
Kampala, Uganda Mon - Fri (10 Days) USD 3,700 English See dates & reserve →
Dar es Salaam, Tanzania Mon - Fri (10 Days) USD 4,200 English See dates & reserve →
Accra, Ghana Mon - Fri (10 Days) USD 7,900 English See dates & reserve →
Nakuru, Kenya Mon - Fri (10 Days) USD 3,200 English See dates & reserve →
Naivasha, Kenya Mon - Fri (10 Days) USD 3,200 English See dates & reserve →
Kisumu, Kenya Mon - Fri (10 Days) USD 3,200 English See dates & reserve →

Live, instructor-led sessions you can join from anywhere — pick the next start date below.

Code Start Date End Date Duration Fee
DCP-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Weekend (8 Weeks) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Weekend (8 Weeks) USD 1,700 Reserve my seat → Reserve team seats →
DCP-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →

Our instructor comes to your office — same curriculum and accredited certificate, with case studies built around the work your team actually does.

Team Training

Train your entire team together in a familiar environment for better collaboration

Fully Customized

Content tailored to your industry, tools, and specific business challenges

Cost Effective

Save on travel & accommodation costs when training multiple employees

Flexible Scheduling

Choose dates that work best for your team's availability and projects

How It Works
1
Request a Quote

Tell us about your team size, preferred dates, and training goals

2
Get a Custom Proposal

Receive a tailored training plan and competitive pricing within 24 hours

3
We Come to You

Our certified trainer arrives ready to deliver impactful, hands-on training

Ready to upskill your team on Data Preparation and Cleaning Training?

No commitment required · Response within 24 hours

About the Course

In a world flooded with data, one truth remains: if it’s not clean, it’s not useful. Most organizations are sitting on piles of potentially valuable data, but poor preparation turns it into a liability. From misaligned formats to inaccurate entries, raw data is rarely ready for analysis. What distinguishes confusion from clarity? This can be achieved through the implementation of intelligent and repeatable cleaning processes.

This training takes you from overwhelmed to in control. You’ll learn how to identify common issues, clean data efficiently, and structure datasets that work across tools, reports, and systems. No fluff. You will acquire the necessary tools, workflows, and practical experience to convert raw data into analysis-ready gold. Whether you're managing survey results, operational metrics, or monthly financials, you'll walk away with the confidence to prep and clean data that delivers.


Target Audience

This course is designed for professionals who work with data and need it to be accurate, structured, and ready to use:

  • Data analysts cleaning up messy files before analysis
  • Researchers managing survey or study data
  • NGO staff organizing field or program data
  • Public sector teams standardizing service or census data
  • Project managers wrangling inputs from multiple teams
  • Marketing teams preparing campaign and CRM data
  • Finance professionals consolidating reports and spreadsheets
  • Operations managers tracking workflow data
  • HR professionals analyzing workforce metrics
  • Anyone who turns raw data into decisions

Course Objectives

This course helps you clean with confidence so your data works for you, not against you.

By the end of this training, you’ll be able to:

  • Identify and correct common data quality issues
  • Standardize formats, entries, and data types
  • Handle missing, inconsistent, or duplicate values
  • Prepare datasets for reporting, dashboards, and analysis
  • Validate data through summaries and checks
  • Automate repetitive cleaning steps
  • Document your cleaning process for clarity and collaboration
  • Build workflows that save time and prevent future messes

Local Application and Business Return

How participants can apply the training in local operating conditions, and the return their organisation can plan for.

How participants apply this

In Ireland, data professionals apply these skills to meet the 'Accuracy' principle of the Data Protection Act 2018, ensuring personal data is kept up-to-date and error-free. Participants often work on reconciling disparate datasets from EU and US headquarters, requiring advanced deduplication and format standardisation. In the public sector, these skills are critical for implementing the 'Once-Only' principle of the Public Service Data Strategy, where data must be cleaned once to be reused across multiple agencies. Additionally, analysts in the IFSC use these techniques to prepare regulatory reports for the Central Bank of Ireland, where data integrity is a mandatory compliance requirement.

Expected ROI

Within 6–12 months, organisations typically see a 30–50% reduction in the time spent on manual data fixes in Excel, allowing analysts to focus on higher-value predictive modelling. Business units report higher confidence in BI dashboards, leading to faster decision-making cycles during quarterly reviews. For firms regulated by the Central Bank or DPC, the primary ROI is a significant reduction in 'data debt' and the mitigation of legal risks associated with inaccurate data processing. Furthermore, clean datasets enable more successful AI and machine learning pilots, which often fail in the Irish market due to poor initial data quality.

Training Methodology

This is a hands-on, problem-solving course built around real data challenges, not theory.

  • Here’s what makes this training practical and effective:
  • Walkthroughs of messy datasets
  • Practice cleaning using Excel and Python
  • Structured exercises for spotting and fixing common issues
  • Peer review and feedback sessions
  • Case studies from multiple industries
  • Templates and checklists for repeatable processes
  • Guided documentation and validation techniques
  • Optional breakout tracks for advanced tools or sector-specific datasets

Upcoming Sessions

Next available dates worldwide

Virtual

(Zoom) Training
USD 1,700
22nd Jun-3rd Jul 2026

Nairobi

Kenya
USD 2,900
29th Jun-10th Jul 2026

Kigali

Rwanda
USD 3,800
29th Jun-10th Jul 2026

Dubai

United Arab Emirates (UAE)
USD 7,800
29th Jun-10th Jul 2026

Addis Ababa

Ethiopia
USD 4,900
22nd Jun-3rd Jul 2026

Zanzibar

Tanzania
USD 4,300
29th Jun-10th Jul 2026

Mombasa

Kenya
USD 3,200
27th Jul-7th Aug 2026

Cape Town

South Africa
USD 7,500
29th Jun-10th Jul 2026

Johannesburg

South Africa
USD 6,000
27th Jul-7th Aug 2026

Pretoria

South Africa
USD 5,900
29th Jun-10th Jul 2026

Kampala

Uganda
USD 3,700
29th Jun-10th Jul 2026

Dar es Salaam

Tanzania
USD 4,200
27th Jul-7th Aug 2026

Accra

Ghana
USD 7,900
29th Jun-10th Jul 2026

Certification

Recognized credentials that advance your career

Participants who complete the Data Preparation and Cleaning 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 the art of data cleaning, essential for cutting-edge data science projects.
  • Learn techniques to enhance data integrity, boosting analytical accuracy and insights.
  • Acquire practical skills in Python and R for real-world data preparation tasks.

Career Advancement

  • Position yourself as a data-cleaning expert, crucial for high-stakes decision-making roles.
  • Enhance your resume with advanced data manipulation skills, desired by top tech employers.
  • Unlock new career opportunities in data science and analytics through specialized training.

Expert Delivery

  • Taught by industry leaders with years of experience in big data and analytics.
  • Benefit from personalized feedback on real-world case studies and data sets.
  • Access to exclusive webinars and Q&A sessions with data science professionals.

Tools and platforms relevant to this field

Examples Ireland teams may encounter, and that may be featured in training where they support the confirmed course scope.

5

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.

  • Alteryx Alteryx, Inc.
    Widely adopted by Irish financial services and 'Big Four' consultancies in Dublin for automating complex data blending and cleaning workflows without deep coding.
  • Power BI (Power Query) Microsoft
    The dominant business intelligence tool in the Irish market; its Power Query engine is the primary method for data transformation in local SMEs and government bodies.
  • Tableau Prep Salesforce
    Used extensively by Dublin's tech sector (Silicon Docks) to visually clean and shape data before building executive dashboards.
  • Python (Pandas) Open Source
    The standard for data science teams in Ireland's multinational tech and pharma hubs for programmatic data cleaning and handling large-scale datasets.
  • SQL Server Integration Services (SSIS) Microsoft
    Commonly used in legacy data warehousing environments within Irish retail banking and insurance sectors for ETL processes.

Real-World Case Studies from Ireland

Real organisations putting these methods into practice — what they did, what changed, and the measurable outcome. No hypothetical scenarios.

1
  • Implementation of the Quality Management Framework (QMF) 2018
    Central Statistics Office (CSO)

    The CSO implemented a comprehensive Quality Management Framework based on the Generic Statistical Business Process Model (GSBPM). This framework formalised the 'Process' phase of statistical production, which focuses heavily on data cleaning, editing, and imputation of raw administrative data.

    Improved the reliability and integrity of official Irish statistics by standardising how data from various government departments is cleaned and validated before publication.

    View source

Real Results from Real Professionals

Thousands of professionals have transformed their careers through our training programs. Now, it's your turn.

Local market advisory

Course relevance for Ireland

A country-specific view of market pressure, regulatory context, and practical business return behind this training.

  • Market context
  • Regulatory fit
  • Business application

Regulatory context in Ireland

The local regulators, laws, and frameworks shaping this discipline, with the curriculum mapped to what teams need to know.

3

Regulators

  • DPC Enforces the Accuracy principle of GDPR, making data cleaning a legal necessity for any organisation handling personal data in Ireland.
  • CSO Sets the national standards for data quality and statistical methodology used across the Irish public sector.
  • HIQA Develops standards and reviews data quality practices within the Irish health and social care services.

Frameworks the course aligns with

  • 01 Data Protection Act 2018 · 2018
  • 02 Data Sharing and Governance Act 2019 · 2019
  • 03 Statistics Act 1993 · 1993

Frequently Asked Questions

Got questions? We've gathered the answers to common queries to help you feel confident and informed.

Who else has attended this training course?

Join global leaders and experts from top-tier organizations who have already benefited from this training. Here are just a few of our past participants:

Designation Organization
Practioner Amnesty International, NIGERIA
Project manager UNDP Togo, Togo
Practioner undp, Togo
Cyber security Big data analysis using public training course, Nigeria
PRINCIPAL LECTURER KENYA UTALII COLLEGE, Kenya

Your seat is waiting.

Join these industry leaders and take the next step in your career.

The course directly addresses the 'Accuracy' principle (Article 5) of the GDPR and the Data Protection Act 2018. By learning systematic cleaning techniques, you ensure your organisation can demonstrate that personal data is accurate and, where necessary, kept up to date.

Yes, the skills taught align with the strategy's goal of improving data governance and re-use. It provides the practical tools needed to clean administrative data so it can be safely shared between public bodies under the Data Sharing and Governance Act 2019.

Absolutely. The course focuses on the logic of data preparation that applies across tools, moving participants from manual Excel 'find-and-replace' to more robust, repeatable workflows in SQL, Power Query, or Python.

Trusted by 100+ organizations across 40+ countries

Premier Bank
Amnesty International
UNDT SACCO
UNFPA
USAID
AMREF Health Africa
KENTRADE
CPF
UFIA
UNICEF
Central Bank of Kenya
UNDP
GIZ
Premier Bank
Amnesty International
UNDT SACCO
UNFPA
USAID
AMREF Health Africa
KENTRADE
CPF
UFIA
UNICEF
Central Bank of Kenya
UNDP
GIZ
Barbours
Bank of Rwanda
RFA
Dahabshil Bank
Dorcas Aid
Finn Church Aid
KCB Foundation
Ministry of Education Saudi Arabia
NSSF Uganda
RBA
Reserve Bank of Malawi
WASREB Kenya
Virginia Commonwealth University
Barbours
Bank of Rwanda
RFA
Dahabshil Bank
Dorcas Aid
Finn Church Aid
KCB Foundation
Ministry of Education Saudi Arabia
NSSF Uganda
RBA
Reserve Bank of Malawi
WASREB Kenya
Virginia Commonwealth University