Now Incorporated in Each 2 Week Training Skills for
Program Specific Job Process Performance, Reviewing Ai Outputs, Trainer of Ai Systems, Interrogating Ai Systems, and Possibly Transforming into a 20 year Experienced Inter-Discipline Domain Expert. Programs Updated to Leverage the Best of Digital Transformation, Data Analytics and Artificial Intelligence Ai.
Each program participant will get 1 year free individual license access to a Program Domain Specific Ai System to Answer his job related queries.
DAI745-2
2 Week Job Process Performance & Productivity Process Skills Training
Data Acquisition & Preparation Processes
for Data Analysis & Artificial Intelligence Applications
Building Hands-on Skills & Competencies in
Collecting Internal & External Data
Preparing Data for use in Business Decision Models
- Data Extraction and Filtering
- Validating & Cleaning Collected Data
- Correcting Collected Data
- Aggregating and Presenting Collected Data
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What is Covered in this Job Process Workshop?
Garbage-in Garbage-out Applies to Data Analytics. Therefore Data Acquisition and Initial Processing is an Important Part of Data Science Knowledge.
This Work Process Skills program provides the participant understanding of the full range of Protocols, Frameworks, Software and methods to analyze and understand Big Data Acquisition, Filtering, Cleaning & Integration needs, technologies, methods, eMethods, key success factors, procedures, processes, forms, checklists, controls, feedback, improvements and strategic alignment.
Develop robust processes for acquiring and preparing data for data analysis and AI applications. Ensure efficient collection of internal and external data for diverse business decision models.
Garbage-in Garbage-out Applies to Data Analytics. Therefore Data Acquisition and Initial Processing is an Important Part of Data Science Knowledge.
This Work Process Skills program provides the participant understanding of the full range of Protocols, Frameworks, Software and methods to analyze and understand Big Data Acquisition, Filtering, Cleaning & Integration needs, technologies, methods, eMethods, key success factors, procedures, processes, forms, checklists, controls, feedback, improvements and strategic alignment.
Develop robust processes for acquiring and preparing data for data analysis and AI applications. Ensure efficient collection of internal and external data for diverse business decision models.
Implement effective data extraction, filtering, validation, and cleaning techniques. Correct data inconsistencies to ensure accuracy and reliability.
Aggregate and present data in formats optimized for business insights and AI applications.
Establish data preparation practices that align with organizational goals and data governance standards.
Aggregate and present data in formats optimized for business insights and AI applications.
Establish data preparation practices that align with organizational goals and data governance standards.
The skills and competencies developed will include understanding the Data Needs of Business Models; Methods and Tools for Data Extraction and Filtering; Methods and Tools for Validating & Cleaning Collected Data; Logic, Need, Methods and Tools for Correcting Collected Data; Logic, Need, Methods and Tools for Aggregating and Presenting Collected Data.
Who Should Attend?
This Work Process Skills program is primarily meant for Data Analytics Data Engineers and Managers.
Program is also recommended for All Data Analytic, Business Intelligence and Artificial Intelligence Team Members so they can understand, guide and verify the Data Presented for Analysis by the Business Decision Models. Program will also be useful for Data Analytics Research & Development Teams and Data Scientists.
Program Content
Processes & Modules
Data Acquisition & Preparation Processes
for Data Analysis & Artificial Intelligence Applications
Data Acquisition, Filtering, Cleaning & IntegrationImportance of data acquisition and preparation for effective AI and business decision-making.
Overview of internal vs. external data sources and their relevance to organizational objectives.
Challenges in preparing data for analytical and AI models, including quality, volume, and consistency.
Data Acquisition & Preparation Strategy Processes
Define objectives for data acquisition aligned with business and AI goals.
Identify key internal and external data sources, including transactional systems, IoT devices, social media, and third-party APIs.
Develop a data preparation roadmap, ensuring scalability and alignment with organizational data governance policies.
Data Acquisition Processes
Collect internal data from operational systems, CRM platforms, ERP systems, and databases.
Acquire external data through APIs, web scraping, surveys, and licensed third-party datasets.
Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) during acquisition processes.
Data Extraction and Filtering Processes
Extract raw data from diverse sources, including structured, semi-structured, and unstructured formats.
Filter out irrelevant or redundant data using predefined criteria to focus on actionable insights.
Use ETL (Extract, Transform, Load) tools to automate the extraction and filtering pipeline.
Data Validation Processes
Validate data against predefined rules and thresholds to ensure consistency and integrity.
Cross-check collected data with known benchmarks or standards to detect anomalies.
Use AI and machine learning tools to identify patterns and flag inconsistencies in data.
Data Cleaning Processes
Identify and correct errors such as duplicate entries, missing values, and outliers.
Standardize data formats, such as date and time conventions or unit measurements.
Remove noise from unstructured data (e.g., removing irrelevant words from text or normalizing images).
Data Correction Processes
Replace or impute missing data using statistical methods or machine learning techniques.
Address outliers through analysis and contextual judgment to maintain data reliability.
Reconcile conflicting data points by tracing them back to the source and applying business rules.
Data Aggregation Processes
Combine data from multiple sources to create unified datasets suitable for analysis.
Group and summarize data into meaningful categories, such as totals, averages, or trends.
Apply dimensionality reduction techniques (e.g., principal component analysis) for complex datasets.
Data Presentation Processes
Format aggregated data for visualization tools such as dashboards and reports.
Use charts, graphs, and tables to communicate data insights effectively to stakeholders.
Ensure data formats are compatible with machine learning algorithms and analytical tools.
Performance Evaluation Processes
Measure the quality of prepared data using metrics such as accuracy, completeness, and timeliness.
Monitor data preparation processes to identify bottlenecks and areas for improvement.
Evaluate the impact of data preparation on the performance of business decision models and AI systems.
Best Practices in Data Acquisition & Preparation
Automate repetitive tasks such as data extraction, cleaning, and aggregation to save time and reduce errors.
Use metadata to track data provenance, ensuring transparency in data handling.
Adopt scalable tools and platforms for handling large datasets, such as cloud-based storage and processing systems.
Continuously refine data preparation workflows based on feedback from AI models and decision-makers.
Data Acquisition & Preparation Use Cases
2 Week Job Process Skills Training
Outcomes & Takeaways
Job Process Good & Best Practices Workshop Outcomes and Takeaways
The Work Process Approach to Learning is a methodology that emphasizes learning through understanding the actual work processes.
A work process refers to a set of activities or tasks that are carried out to achieve a specific outcome or result. These processes can be core to the business, such as manufacturing, service delivery, or customer support, or they can be supportive, like HR processes, IT services, or administrative workflows.
The Goal is to closely align training content and methods with the specific processes, tasks, and challenges found in that domain real-world work environments.
What the training achieves is building skills and competencies essential for actual work processes performance. Enabling quick and seamlessly understanding how to perform their processes effectively, efficiently and avoiding the usual mistakes and risks.
This 2 Week Training Workshop participant will typically take away...
Program related Process knowhow, skills, competencies and process knowledge to perform the job work processes
Training that will empower the participant to identify, support and implement work process improvements in his unit, team, section, department, and organization.
The Work Process Approach to Learning is a methodology that emphasizes learning through understanding the actual work processes.
A work process refers to a set of activities or tasks that are carried out to achieve a specific outcome or result. These processes can be core to the business, such as manufacturing, service delivery, or customer support, or they can be supportive, like HR processes, IT services, or administrative workflows.
The Goal is to closely align training content and methods with the specific processes, tasks, and challenges found in that domain real-world work environments.
What the training achieves is building skills and competencies essential for actual work processes performance. Enabling quick and seamlessly understanding how to perform their processes effectively, efficiently and avoiding the usual mistakes and risks.
Program related Process knowhow, skills, competencies and process knowledge to perform the job work processes
Training that will empower the participant to identify, support and implement work process improvements in his unit, team, section, department, and organization.
Benefits to the Organization Sponsoring Participants to this program
(Benefits made possible by Euro Training's above mentioned Planned Outcomes and Takeaways)
This Euro Training programs is different. It develops practical Job Process Skills.
Benefits you may see in participant post program behavior...Inclination to Recognize his Processes Customers and Stakeholders, and their Needs & Expectations.
Higher level of Relevant Multi-discipline Job Process Skills
Taking Initiative to Propose and help implement Process Improvements in his Work Responsibility Area.
How your Participant will Change after attending the program?...
Increased Work Process Performance Knowledge
Awareness to the Need to align process performance to the Needs and Expectations of Stakeholders and Customers (internal & external)
Awareness of the Need to Align Process Performance to Organizational Operational and Strategic Objectives.
Implement Good Management Practices during Process Performance, and, Gain Awareness to meet Requirements and Recommendations of the any Applicable Industry and Professional Standards.
Skill Sets for possible implementation the Program Discussed Action Plan for Process Improvements.
Type of improvements the participant will be trained to analyze and implement include (as relevant)
(a) Productivity Improvements
(b) Product and Service Differentiation
(c) Exceeding Stakeholder & Customer Expectations.Euro Training Instructors often act as mentors for participants (solely subject to instructor approval). Your participants can utilize this free service to ensure effective post program reinforcement and help when apply the ideas and skills acquired during the training.
Participant Individual Career Benefits
Job Satisfaction & Advancement
First, and most important benefit, is the positive self-esteem that will come from being able to do your work processes right first time and meet internal and external customer expectations.
Second, the Program developed Job Process Understanding & Skills will help participant successfully present his professional skills at Job Interviews and Internal Performance Evaluation Reviews.
Participant gains clear direction and insight for analyzing, proposing and implementing improvements in his work processes.
Post program when you take decisions related to your work processes you will automatically consider Multi-discipline aspects (as applicable):
Internal & External Customer Needs and Expectations, Technology Options, Data Analytics and Artificial Intelligence Opportunities, Helpful Tools and Methods, Consider Risks, Mitigate Risks, Take Actions that Increase Productivity, Consider Legal & Contractual Aspects, Consider Intellectual Property Aspects, Pay attention to Safety and Security, Consider future Audit, Weigh Cost Benefit between options, Be Mindful of Key Performance Indicators (KPIs), Consider how Performance will be evaluated, and, Consider need for and Opportunity to Develop a Decision Support Knowledge Base, .... (and, possibly more aspects).
First, and most important benefit, is the positive self-esteem that will come from being able to do your work processes right first time and meet internal and external customer expectations.
Second, the Program developed Job Process Understanding & Skills will help participant successfully present his professional skills at Job Interviews and Internal Performance Evaluation Reviews.
Participant gains clear direction and insight for analyzing, proposing and implementing improvements in his work processes.
Post program when you take decisions related to your work processes you will automatically consider Multi-discipline aspects (as applicable):
Internal & External Customer Needs and Expectations, Technology Options, Data Analytics and Artificial Intelligence Opportunities, Helpful Tools and Methods, Consider Risks, Mitigate Risks, Take Actions that Increase Productivity, Consider Legal & Contractual Aspects, Consider Intellectual Property Aspects, Pay attention to Safety and Security, Consider future Audit, Weigh Cost Benefit between options, Be Mindful of Key Performance Indicators (KPIs), Consider how Performance will be evaluated, and, Consider need for and Opportunity to Develop a Decision Support Knowledge Base, .... (and, possibly more aspects).
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