Data Cleaning and Preparation for High-Impact Business Intelligence Systems Training Course

Introduction

In the world of business intelligence, data quality is the foundation of reliable insights and informed decision-making. Raw data collected from diverse sources often contains errors, inconsistencies, duplicates, and missing values that can distort analysis and weaken business outcomes. Data cleaning and preparation ensure that information used in business intelligence systems is accurate, consistent, and ready for advanced analytics.

This training course equips professionals with practical skills and best practices for preparing high-quality datasets tailored for business intelligence applications. Participants will learn methods for identifying and correcting data issues, handling missing values, standardizing formats, and integrating datasets from multiple systems. By mastering these techniques, professionals will be able to deliver trusted insights, reduce risks of poor decision-making, and enhance the performance of business intelligence platforms.

Duration: 10 Days

Target Audience

  • Business intelligence analysts and data professionals
  • Data scientists and engineers
  • IT and database administrators
  • Reporting and analytics specialists
  • Professionals seeking to strengthen data preparation skills

10 Objectives

  1. Understand the role of data cleaning in business intelligence
  2. Identify common data quality issues in BI environments
  3. Learn techniques for handling missing, inconsistent, and duplicate data
  4. Standardize and normalize datasets for BI use
  5. Apply data transformation and enrichment methods
  6. Explore tools and platforms for data preparation
  7. Integrate data from multiple sources into BI systems
  8. Develop workflows for repeatable data cleaning processes
  9. Ensure compliance, accuracy, and integrity of data
  10. Prepare datasets for visualization, reporting, and advanced analytics

15 Course Modules

Module 1: Introduction to Data Cleaning for BI

  • Importance of clean data in business intelligence
  • Common challenges in raw datasets
  • Impact of poor data quality on decision-making
  • Data preparation workflows overview
  • Course roadmap

Module 2: Fundamentals of Data Quality

  • Key dimensions of data quality
  • Accuracy, completeness, consistency, timeliness
  • Identifying quality gaps in BI data
  • Assessing data sources
  • Metrics for measuring data quality

Module 3: Handling Missing Data

  • Causes of missing data in BI systems
  • Detection methods for missing values
  • Imputation techniques (mean, median, regression)
  • Deletion vs. replacement strategies
  • Impact on BI insights

Module 4: Removing Duplicates and Redundancies

  • Identifying duplicate records
  • Deduplication techniques and algorithms
  • Merging duplicate data entries
  • Data consolidation practices
  • Tools for deduplication in BI pipelines

Module 5: Standardization and Normalization

  • Standardizing data formats and units
  • Normalizing text and categorical variables
  • Currency and date standardization
  • Address and name formatting
  • Best practices for consistency

Module 6: Data Transformation Techniques

  • Aggregation and summarization
  • Pivoting and reshaping data
  • Encoding categorical data
  • Feature engineering basics
  • Transformation workflows for BI

Module 7: Data Validation and Verification

  • Rules-based validation
  • Integrity checks in BI datasets
  • Referential integrity enforcement
  • Automated validation methods
  • Data auditing and monitoring

Module 8: Handling Outliers and Inconsistencies

  • Identifying outliers in datasets
  • Statistical vs. business rule approaches
  • Outlier correction techniques
  • Addressing inconsistent data entries
  • Maintaining data accuracy

Module 9: Data Integration and Consolidation

  • Combining datasets from multiple sources
  • ETL processes for BI preparation
  • Data warehousing considerations
  • Schema alignment and mapping
  • Challenges in data integration

Module 10: Data Enrichment Methods

  • Adding external datasets for deeper insights
  • Enhancing data with demographic and market data
  • Enriching unstructured data for BI use
  • Linking internal and external sources
  • Examples of enrichment use cases

Module 11: Tools for Data Cleaning and Preparation

  • Overview of BI data preparation tools
  • Excel, Power Query, and SQL
  • Python and R libraries for data cleaning
  • ETL platforms and data integration tools
  • Criteria for tool selection

Module 12: Automation in Data Preparation

  • Automated workflows for repeatable tasks
  • Scheduling data preparation pipelines
  • AI and ML-assisted data cleaning
  • Benefits of automation in BI environments
  • Case examples of automated solutions

Module 13: Ensuring Compliance and Governance

  • Data governance principles
  • Regulatory requirements for data handling
  • Metadata management practices
  • Privacy and security considerations
  • Compliance in BI workflows

Module 14: Preparing Data for Visualization and Reporting

  • Structuring datasets for dashboards
  • Aggregating and filtering data
  • Aligning datasets with KPI frameworks
  • Preparing inputs for advanced analytics
  • Visualization readiness checks

Module 15: Future of Data Preparation in BI

  • Trends in self-service data preparation
  • Cloud-based preparation tools
  • Real-time data preparation approaches
  • Integration with AI-driven BI platforms
  • Preparing for next-generation BI systems

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

 

Data Cleaning And Preparation For High-impact Business Intelligence Systems Training Course in Eswatini
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