Data Quality Powerpoint Presentation Slides

Slide 1: This slide introduces Data Quality. State your company name and begin.
Slide 2: This slide states Agenda of the presentation.
Slide 3: This slide shows Table of Content for the presentation.
Slide 4: This slide highlights title for topics that are to be covered next in the template.
Slide 5: This slide highlights the introduction to modern data quality in organization which include measurement of dataset with criteria, ensure data driven decisions, etc.
Slide 6: This slide represents the key benefits of good data quality which include enhances decision making and targeting, improves content effectiveness, etc,
Slide 7: This slide outlines the dimensions of data quality which include completeness, uniqueness, validity, timeliness, accuracy, consistency and fitness for purpose.
Slide 8: This slide discusses the methods used to improve data quality which include ensure data adherence, prioritize timeliness, validate data accuracy, etc.
Slide 9: This slide gives an overview of major applications of good data quality which include healthcare, retail, telecommunication, government, education, etc.
Slide 10: This slide represents the use cases of good data quality which include data standardization, data cleaning, geocoding, data governance and data profiling.
Slide 11: This slide highlights the future trends of modern data quality which include systems as data consumers, real time data quality management, governance and compliance, etc.
Slide 12: This slide describes the data quality categories and their dimensions which include intrinsic data quality, contextual data quality, representational data quality, etc.
Slide 13: This slide depicts the good data quality sophistication curve which represents four stages – unaware, reactive, proactive and optimized.
Slide 14: This slide depicts the time plotting of data for data quality analysis. The data include feed gas temperature, feed gas flowrate, feed gas pressure, feed gas dewpoint, etc.
Slide 15: This slide highlights title for topics that are to be covered next in the template.
Slide 16: This slide gives an overview of data quality assessment which is a systematic approach to review quality of data set and helps user know data health, etc.
Slide 17: This slide briefly outlines the step guide to data quality assessment which include select indicators, review available documents, develop DQA matrix, etc.
Slide 18: This slide discusses the steps to perform data quality assessments which include data profiling, data quality rules, data reconciliation rule, data drift detection, etc.
Slide 19: This slide outlines the selection criteria for indicators in data quality assessment which include indicators of high importance, indicators with high targets, etc.
Slide 20: This slide highlights the components of data quality assessment report which include executive summary, project background, data validation, etc.
Slide 21: This slide describes the points to be focused on for assessment of data collection and management system which include check monitoring, review meta data, etc.
Slide 22: This slide highlights title for topics that are to be covered next in the template.
Slide 23: This slide outlines the routine data quality assessment tools which include data quality audit tool, routine data quality assessment tool, single indicator RDQA tool, etc.
Slide 24: This slide highlights title for topics that are to be covered next in the template.
Slide 25: This slide gives an overview of steps to collect high quality data which include implement data collection plan, set data quality standards, plan for data correction, etc.
Slide 26: This slide discusses the key steps to maintain high quality data which include access control, data encryption, audit trails and logs, error handling techniques, etc.
Slide 27: This slide highlights title for topics that are to be covered next in the template.
Slide 28: This slide outlines the technical standards to manage data quality which include ISO 8000 standard, ISO 8000-60, ISO 8000-61, ISO 8000-62, ISO 25012 standard, etc.
Slide 29: This slide represents the data quality management implementation cycle which include data quality planning, information and technology, data quality improvement, etc.
Slide 30: This slide outlines the dimensions of data quality in risk management which include data traceability, data suitability, data consistency, data timeliness, etc.
Slide 31: This slide discusses the data quality management best practices which include set clear metrics, implement reporting for data issues, establish investigation, etc.
Slide 32: This slide highlights title for topics that are to be covered next in the template.
Slide 33: This slide lists out the essential components of data governance frameworks for quality which include communication structures, data requirements, data request process, etc.
Slide 34: This slide highlights the implementation steps for data quality governance which include gain organizational support, promote transparency, create audit trails, etc.
Slide 35: This slide highlights title for topics that are to be covered next in the template.
Slide 36: This slide depicts the six P’s of data quality framework which include perform, purpose, principles, process, people and plan.
Slide 37: This slide lists out the dimensions of data quality assessment framework which include integrity, methodological soundness, serviceability, accessibility, etc.
Slide 38: This slide describes the steps to create and implement robust data quality framework which include data discovery, metadata service, ownership of data quality, etc.
Slide 39: This slide depicts the big data quality framework structure which include exploratory quality profiling, big data sampling and profiling and data quality repository.
Slide 40: This slide highlights title for topics that are to be covered next in the template.
Slide 41: This slide showcases the processes in data quality control framework which include data sourcing, data sampling and profiling, establish data quality standards, etc.
Slide 42: This slide briefly explains the data quality control framework for enterprise data lakes which include data quality capabilities, framework and cloud data platform.
Slide 43: This slide highlights title for topics that are to be covered next in the template.
Slide 44: This slide outlines the comparative analysis of data integrity and quality based on aspects such as focus, mechanisms and scope of data integrity and data quality.
Slide 45: This slide highlights title for topics that are to be covered next in the template.
Slide 46: This slide represents the data checklists for quality assessments in organizations which include data discovery, data quality rules, data reconciliation rules and data drift detection.
Slide 47: This slide describes the data pipelines checklist for quality assessments which include end-to-end visibility, performance analytics, pipeline monitoring, cost benefit analysis, etc.
Slide 48: This slide highlights title for topics that are to be covered next in the template.
Slide 49: This slide represents the training plan for data quality management and includes modules on data quality tools, data profiling, data cleansing, data governance, etc.
Slide 50: This slide highlights the implementation budget for data quality management and includes expenses such as data quality software, training and education, etc.
Slide 51: This slide represents the different roles in data quality and their responsibilities to ensure good data quality and include data owner, data steward and data manager.
Slide 52: This slide highlights title for topics that are to be covered next in the template.
Slide 53: This slide depicts the generic framework for monitoring data quality which include data governance, data quality management, quality assurance and quality control.
Slide 54: This slide describes the data quality metrics monitoring dashboard which include freshness rules, SQL rules, ML freshness monitors, volume rules and field health.
Slide 55: This slide depicts the data quality score monitoring dashboard which include overall data quality score, total rows processed and failed rows.
Slide 56: This slide highlights title for topics that are to be covered next in the template.
Slide 57: This slide describes the impact of data quality in business intelligence and analysis which includes gain competitive advantage by 78% through high quality data, etc.
Slide 58: This slide contains all the icons used in this presentation.
Slide 59: This slide is titled as Additional Slides for moving forward.
Slide 60: This slide presents Bar chart with two products comparison.
Slide 61: This is a Timeline slide. Show data related to time intervals here.
Slide 62: This slide depicts Venn diagram with text boxes.
Slide 63: This is a Financial slide. Show your finance related stuff here.
Slide 64: This slide contains Puzzle with related icons and text.
Slide 65: This is Our Goal slide. State your firm's goals here.
Slide 66: This is an Idea Generation slide to state a new idea or highlight information, specifications etc.
Slide 67: This slide provides 30 60 90 Days Plan with text boxes.
Slide 68: This slide shows Post It Notes. Post your important notes here.
Slide 69: This is a Thank You slide with address, contact numbers and email address.