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Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

Executive Summary<br>ChainSys Smart Data Platform<br>Archival Solutions Portfolio<br>In today's data-driven world, managing the ever-growing volume of information is essential for<br>business success. The ChainSys Smart Data Platform for Data Archival and Purging offers a<br>powerful solution to address this need. By seamlessly integrating with existing systems, it ensures<br>that historical data is securely stored, easily accessible, and compliant with regulatory<br>requirements.

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Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

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  1. Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  2. Executive Summary In today's data-driven world, managing the ever-growing volume of information is essential for business success. The ChainSys Smart Data Platform for Data Archival and Purging offers a powerful solution to address this need. By seamlessly integrating with existing systems, it ensures that historical data is securely stored, easily accessible, and compliant with regulatory requirements. As organizations transition from legacy systems to modern cloud environments, the Smart Data Platform plays a critical role in preserving data integrity, reducing storage costs, and enabling future data-driven insights. Additionally, it facilitates the effective removal of obsolete or irrelevant data, optimizing storage resources and enhancing system performance. This solution not only safeguards valuable data assets but also positions businesses to leverage historical data for continued growth and innovation while maintaining a streamlined and efficient data management approach. ChainSys Smart Data Platform Archival Solutions Portfolio Ongoing Archival Solution Data Retirement Solution Purging Solution Data Categorization and Segmentation Data Assessment and Identification Uniformity and Interoperability Retention Rules and Metadata Documentation Retention Criteria and Metadata Descriptive Metadata Version Control End-of-Life Data Tracking Deletion Audit Trails Regular Updates Retirement Scheduling Scheduled Purge Cycles Cloud Storage and Redundancy Secure Archival Storage Redundant Data Elimination Data Transfer to Long-Term Storage Data Migration Data Cleansing Regulatory Compliance in Data Retirement Compliance with Data Deletion Policies Legal and Ethical Compliance I Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  3. The ChainSys’s Smart Data Platform Archival and Purging Solution Approach Data Data Data Data Identification Remediation Governance Visualization Source Systems+ Archival Storage (HDFS) Historical Data Dashboard Data Assessment Data Writing User Screen Data Profiling File Selection SS0 Reports Data Reading Data Trends Dashboard Data Selection User Approval Enquiry Screen Archival History Dashboard Archive Approve Auditing Data Purging The ChainSys Smart Data Archival & Purging Solution provides an advanced, tool-driven approach to managing and optimizing data storage. Covering all aspects from data assessment and classification to archival, purging, and retrieval, it ensures streamlined processes, improved data management, and compliance with regulatory standards. By addressing potential pitfalls and enhancing data accessibility, it effectively reduces risks associated with both archiving and purging. This comprehensive solution supports efficient data lifecycle management at every stage, ensuring that valuable data assets are preserved while obsolete or irrelevant information is securely removed, thus optimizing storage resources and maintaining data integrity. The Transformative Impact of ChainSys Smart Data Platform Archival Solution 80% Reduction in System Load Compliance with 100+ Regulations 99.9% Data Availability 40% Lowered Risk of Data Breaches II Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  4. Data Archival Challenges and ChainSys Solutions Organizations using ChainSys Smart Data Platform for Data Archival have reported a reduction in data integrity issues by approximately 40%. 25% of organizations report encountering data integrity issues during archival processes Data Integrity About 30% of organizations experience significant increases in storage costs due to inefficient data archival practices. By utilizing data compression and deduplication techniques, ChainSys Smart Data Platform can reduce storage costs by up to 30%. Increased Cost Around 20% of companies face compliance issues related to data archival, particularly in Implementation of ChainSys Smart Data Platform for Data Archival can decrease compliance-related issues by around 35%. regulated industries Compliance Issue Smart Data Platform's advanced Indexing and metadata management for Data Archival can improve data retrieval times by up to 50%. Nearly 22% of organizations struggle with retrieving archived data efficiently. Data Retrieval About 18% of companies face challenges with metadata management in their archival ChainSys Smart Data Platform enhances metadata management accuracy by approximately 45% processes. Metadata Management ChainSys: Bespoke Archival Solutions Designed to Fit Your Exact Needs Custom & Pre- Built Rules Custom & Pre- Built Rules Ensure precise data retention by archiving or purging data that meets your business criteria User-Friendly User-Friendly Screens & Reports Screens & Reports Quickly access and manage archived data with minimal effort Scalable Architecture Scalable Architecture Seamlessly expand your archival capacity as your data grows ChainSys’ Smart Archival Oferings Automated Automated Data Management Data Management Eliminate manual intervention, reducing errors and saving time Flexible Pricing Flexible Pricing Optimize costs by paying only for the storage and services you use III Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  5. Table of Contents Executive Summary I The ChainSys’s Smart Data Platform Archival and Purging Solution Approach II The Transformative Impact of ChainSys Smart Data Platform II Data Archival Challenges and ChainSys Solutions III ChainSys: Bespoke Archival Solutions Designed to Fit Your Exact Needs III Chapter 1: Introduction to Data Archival & Purging 1 1.1. What is Data Archival & Purging? 1 1.2. Guardians of Performance and Compliance: The Role of Data Archival 1 1.3. Why Do Organizations Need Data Archival and Purging? 1 1.4. The Importance of Data Quality and System Understanding 2 Chapter 2: Full Archival and Purging Process with ChainSys Smart Data Platform 3 2.1. Introduction to ChainSys Smart Data Platform 3 2.1.1. What is Smart Data Platform? 3 Key Features and Benefits of Using ChainSys Smart Data Platform 3 How the Smart Data Platform Addresses Data Management Challenges 5 The Importance of Integrated Data Management and Governance 6 ChainSys Smart Data Archival Solutions 6 2.1.2. Why is ChainSys Smart Data Platform the Market Leader? 7 2.2. Achieve Seamless Efficiency with ChainSys Smart Data Archival & Purging Solution 10 1. Data Identification 10 1.1 Initial Data Assessment 11 1.2. Defining Archival Criteria 11 1.3. Data Categorization 11 1.4. Data Profiling 12 1.5. Data Identification 12 Final Outcome: Identified Data 12 2. Data Remediation 13 2.1. Data Writing 13 2.2. File Selection 14

  6. 2.3. Data Purging 14 2.4. User Approval 14 2.5. Archive or Purge Approve 15 2.6. Archival Storage (HDFS) and Purged Data 15 Final Outcome of the Data Remediation Process 15 3. Data Governance and Visualization 16 3.1. Data Reading 16 3.2. User Screen 16 3.3. SSO Reports 17 3.4. Enquiry Screen 17 3.5. Auditing 17 3.6. Data Visualization 18 Final Outcome: 18 Chapter 3: Unstoppable Success. Astonishing Metrics. Revolutionary Solutions from ChainSys 19 1. Transforming Data Efficiency: Innovative Archival and Purging Solution for a Leading Canadian Telecom Giant 19 Project Scope 19 Key Outcomes 20 Products and Services Used 20 2. Achieving Data Efficiency: Transforming Archival and Purging for a Global Electronics Manufacturer 21 Project Scope 21 Key Outcomes 21 Products and Services Used 22 3. Revolutionizing Data Management: Accelerated Archival and Migration for Epredia’s Legacy Systems 23 Project Scope 23 Key Outcomes 23 Products and Services Used 24 Chapter 4: Detailed Step-by-Step Process of Data Archival & Purging 25

  7. Pre-Archival Setup and Preparation 25 2.3. Data Purging 14 2.4. User Approval 14 Step 1: Data Identification 26 2.5. Archive or Purge Approve 15 Data Assessment 27 2.6. Archival Storage (HDFS) and Purged Data 15 Data Profiling 28 Final Outcome of the Data Remediation Process 15 Data Selection 29 3. Data Governance and Visualization 16 Step 2. Data Remediation 30 3.1. Data Reading 16 Data Writing 31 3.2. User Screen 16 File Selection 32 3.3. SSO Reports 17 User Approval 33 3.4. Enquiry Screen 17 Archive or Purge Approve 34 3.5. Auditing 17 Archival Storage 35 3.6. Data Visualization 18 Step 3. Data Governance 36 Final Outcome: 18 User Screen 37 Chapter 3: Unstoppable Success. Astonishing Metrics. Revolutionary SSO Reports 38 Solutions from ChainSys 19 Enquiry Screen 39 1. Transforming Data Efficiency: Innovative Archival and Purging Solution Auditing 40 for a Leading Canadian Telecom Giant 19 Data Visualization 41 Project Scope 19 Post-Archival Support from ChainSys 42 Key Outcomes 20 Authors 43 Products and Services Used 20 2. Achieving Data Efficiency: Transforming Archival and Purging for a Global Electronics Manufacturer 21 Project Scope 21 Key Outcomes 21 Products and Services Used 22 3. Revolutionizing Data Management: Accelerated Archival and Migration for Epredia’s Legacy Systems 23 Project Scope 23 Key Outcomes 23 Products and Services Used 24 Chapter 4: Detailed Step-by-Step Process of Data Archival & Purging 25

  8. Chapter 1: Introduction to Data Archival & Purging 1.1. What is Data Archival & Purging? Data Archival & Purging are essential processes in data management aimed at optimizing storage, maintaining data integrity, and ensuring compliance with regulatory requirements. Data Archival refers to the process of moving data that is no longer actively used to a separate storage location for long-term preservation. This data is typically retained for historical reference, regulatory compliance, or future analysis. Data Purging involves the systematic deletion of data that is no longer needed or relevant. This process helps in managing storage resources and maintaining system performance. 1.2. Guardians of Performance and Compliance: The Role of Data Archival Data archival and purging are essential for effective data management. Archival preserves valuable historical data for future reference and compliance while optimizing storage by moving infrequently accessed data to secondary systems. Purging, on the other hand, involves the systematic removal of obsolete or irrelevant data, enhancing system performance and reducing storage costs. Together, these processes ensure that important information is retained securely and efficiently, while outdated data is cleared to maintain optimal system functionality and compliance. 1.3. Why Do Organizations Need Data Archival and Purging? Data archiving and purging is an essential process that allows companies to manage their growing data efficiently, ensuring they meet legal obligations, optimize costs, maintain system performance, and protect sensitive information. Here’s why data archival and purging is critical: Storage Cost Reduction Resource Optimization Enhanced Security Disaster Recovery Regulatory Compliance Cost Improved System Perfomance Data Protection & Security Efficiency Audit Readiness Database Optimization Streamlined Operations Legal Requirements 1 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  9. 1.4. The Importance of Data Quality and System Understanding Data archiving is a critical process that ensures long-term storage and accessibility of important data. However, the success of data archival largely depends on two key factors: data quality and system understanding. Both play a crucial role in maintaining the integrity, accessibility, and usability of archived data. Here’s why these factors are essential: 1. Data Quality Accuracy and Completeness Ensuring high data quality is paramount before archival. Data that is inaccurate, incomplete, or inconsistent can lead to significant issues when accessed in the future. Poor data quality can compromise the integrity of reports, analyses, and business decisions made using archived data. Reliable Historical Records Archiving poor-quality data perpetuates errors and inconsistencies, making it difficult to rely on historical records for compliance, audits, or strategic planning. High-quality data ensures that the archived information remains trustworthy and useful over time. Impact on Compliance Many industries, such as finance and healthcare, have strict regulations regarding data accuracy and retention. If the data being archived is of low quality, it can lead to compliance risks, potential fines, and legal consequences. 2. System Understanding Proper Data Mapping A thorough understanding of the systems involved in data archival is essential for correctly mapping and transferring data from active systems to archival storage. Misunderstandings or gaps in system knowledge can lead to data being incorrectly archived, making it difficult or impossible to retrieve or use effectively in the future. Compatibility and Format Preservation Different systems may store and process data in various formats. Understanding these systems is crucial for preserving the integrity and usability of the data during the archival process. Without this understanding, data may be archived in incompatible formats, leading to corruption or loss of information. Efficient Retrieval and Accessibility System understanding ensures that archived data can be easily retrieved and accessed when needed. This involves knowing how the data is structured, indexed, and stored within the archival system. A lack of understanding can result in difficulties during retrieval, causing delays and inefficiencies in accessing critical information. 2 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  10. Chapter 2: Full Archival and Purging Process with ChainSys Smart Data Platform 2.1. Introduction to ChainSys Smart Data Platform 2.1.1. What is Smart Data Platform? The ChainSys Smart Data Platform is an advanced, all-in-one solution designed to manage, integrate, govern, and analyze enterprise data across diverse systems, including Oracle, SAP, and other major ERP platforms. With a suite of intelligent tools and pre-configured templates, the platform empowers organizations to harness the full potential of their data while ensuring compliance, accuracy, and security. Whether it's data quality management, data integration, or advanced analytics, the Smart Data Platform provides a comprehensive and scalable framework to support your enterprise data initiatives. • Comprehensive Data Governance • Top-notch Data Quality Management • Multi-Domain MDM Implementation • Simplified & Rapid ETL/ELT • Smart Migration • Seamless Data Ingestion • Scalable Data Discovery & Cataloging • Customized Visualization • One Platform-> Analytics to Security Key Features and Benefits of Using ChainSys Smart Data Platform: Unified Data Management The platform consolidates data management processes into a single, unified solution. This includes data integration, data quality, master data management (MDM), data governance, and analytics, providing a holistic view and control over your enterprise data. Pre-Built Templates and Adapters With over 9000+ smart data adapters, the Smart Data Platform simplifies complex data management tasks. These templates cover setups, master data, transactions, and analytics, accelerating project timelines and reducing the need for custom development. 3 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  11. Advanced-Data Governance The platform includes powerful data governance tools that ensure compliance with industry standards and regulations. Automated workflows, audit trails, and data lineage tracking help maintain data integrity and transparency across all systems. Scalable Data Integration Designed to handle the integration needs of both small businesses and large enterprises, the platform's scalable architecture can manage data from a few thousand records to billions of records. It ensures seamless data flow across multiple applications and platforms, regardless of their complexity. Comprehensive Data Quality Management The Smart Data Platform includes robust data profiling, cleansing, and enrichment tools, ensuring that high-quality data is maintained throughout the organization. By addressing data quality at the source, the platform minimizes errors and inconsistencies, leading to more reliable business insights. Advanced-Data Governance The platform includes powerful data governance tools that ensure compliance with industry standards and regulations. Automated workflows, audit trails, and data lineage tracking help maintain data integrity and transparency across all systems. Real-Time Analytics and Reporting The platform offers real-time analytics and reporting capabilities, providing instant access to actionable insights. Customizable dashboards and reports enable organizations to monitor key performance indicators (KPIs) and make informed decisions based on accurate, up-to-date data. 4 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  12. How the Smart Data Platform Addresses Data Management Challenges: Complex Data Environments Managing data across various systems, applications, and databases can be daunting. The Smart Data Platform’s integration capabilities streamline data flow across diverse environments, reducing complexity and ensuring that all data sources are harmonized. Data Quality Issues Poor data quality can lead to inaccurate reporting and decision-making. The Smart Data Platform’s data quality management tools proactively address data issues, ensuring that only clean, validated data is used in critical business processes. Compliance and Regulatory Requirements Organizations face stringent data governance requirements. The platform’s advanced governance features ensure compliance with industry regulations, offering features such as data masking, role-based access control, and automated audit trails. Advanced-Data Governance The platform includes powerful data governance tools that ensure compliance with industry standards and regulations. Automated workflows, audit trails, and data lineage tracking help maintain data integrity and transparency across all systems. Data Silos Data silos can hinder enterprise-wide data initiatives. The Smart Data Platform breaks down these silos by providing a unified data management approach, enabling seamless data sharing and collaboration across departments. 5 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  13. The Importance of Integrated Data Management and Governance: Integrated data management and governance are crucial for maintaining data integrity and achieving business objectives. The ChainSys Smart Data Platform provides organizations with the tools they need to govern, manage, and utilize their data effectively, resulting in better operational efficiency and strategic decision-making. Data Governance Data Management The platform ensures that data is managed according to established policies and procedures, safeguarding its accuracy, completeness, and consistency. This is essential for maintaining trust in the data and ensuring compliance with regulatory standards. Effective data management involves the entire data lifecycle, from acquisition to archiving. The Smart Data Platform facilitates seamless data integration, transformation, and storage, ensuring that data is always available and accurate when needed. ChainSys Smart Data Archival Solutions Ongoing Archival Solution Data Retirement Solution Purging Solution Data Categorization and Segmentation Data Assessment and Identification Uniformity and Interoperability Retention Rules and Metadata Documentation Retention Criteria and Metadata Descriptive Metadata Version Control End-of-Life Data Tracking Deletion Audit Trails Regular Updates Retirement Scheduling Scheduled Purge Cycles Cloud Storage and Redundancy Secure Archival Storage Redundant Data Elimination Data Transfer to Long-Term Storage Data Migration Data Cleansing Regulatory Compliance in Data Retirement Compliance with Data Deletion Policies Legal and Ethical Compliance 6 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  14. 2.1.2. Why is ChainSys Smart Data Platform the Market Leader? Research underscores the significant challenges associated with ERP and cloud migration projects. Smart Data Platform Key Metrics and Process for the Feature Other Tools Features Data Health Check for various DQ Dimensions providing Valuable insights into Data Quality Data Assessment Out of Box configurable DQ Dashboards for various data domains Enhance data quality through Automated Cleansing and enrichment using 3rd Party service providers Data Preparation Optimize collaboration and resource utilization from Business by leveraging User Friendly Dashboards Data Migration Significant time reduction for application Setup with low-code platform Ready to use Adapters for major ERPs like Oracle Fusion, SAP etc. for extraction and Loading including Setup Migrations Comprehensive Data Reconciliation & Functional Reconciliation Ongoing Data Governance capabilities as Multi-Domain MDM Master Data Governance Integration Capabilities to extract and ingest the data into multiple systems as part of Hub & Spoke architecture Comprehensive Approval Workflow & Audit Capabilities to implement data governance policies 7 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  15. Key Metrics and Process for the Feature Other Tools Smart Data Platform Features Data Archival Data assessment to accurately assess where data volumes are unnecessarily high for effective Archival & Purging Solution Pre-configured templates for archiving the data from major ERPs like Oracle, SAP etc. Data Security & Protection Comprehensive platform for all SOX, GDPR, CCPA, PII & other GRC requirements Ability to mask or scramble PII and other sensitive data for enhanced Data security during Data Movement Centralizing data across legacy and cloud systems, unifying discrete data models & object sets Enterprise Data Management Data cataloging to make data searchable and maintain data lineage, entity relationships, business glossary and data virtualization Ingest the Structured as well Non-Structured Data leveraging OCR Capabilities from various sources Data Visualization Pre-configured dashboards for Spend Analytics, Supplier 360, Customer 360, Product 360, Product Profitability, HR Headcount and C-Suite Analytics Data Profiling on structured and unstructured data along with Data Reporting using visualization 8 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  16. Key Metrics and Process for the Feature Other Tools Smart Data Platform Features Custom Application Build No-Code to Low Code Application Development (iPaaS Solution) with Rapid Application Development (RAD) Framework Prebuilt Integration Data Templates for Major Applications (ERPs) Bulk Data Loading Capabilities with Scaling up to 100 Million records Data Maintenance Pre-validate data in Bulk before load to ensure high data quality Automated regression testing, load testing, and performance testing Distributed Computing Model to support parallel high volume data handling & movement Performance & Scalability Vertical and horizontal scalability of the application based on infrastructure 9 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  17. 2.2. Achieve Seamless Efficiency with ChainSys Smart Data Archival and Purging Solution Data Data Data Data Identification Remediation Governance Visualization Source Systems+ Archival Storage (HDFS) Historical Data Dashboard Data Assessment Data Writing User Screen Data Profiling File Selection SS0 Reports Data Reading Data Trends Dashboard Data Selection User Approval Enquiry Screen Archival History Dashboard Archive Approve Auditing Data Purging To effectively address the challenges associated with data archival and purging, ChainSys advocates for a Smart Data Archival approach. This method ensures a structured and secure archival process, minimizing risks while maximizing efficiency. Below are the key steps involved: 1. Data Identification: Data Profiling Initial Data Assessment Defining Archival Criteria Data Data Categorization Identification Source Systems+ Business Relevance Usage Data Quality Assessment Classification Sensitivity Classification Redundancy & Duplication Check Merge Datasets Understanding the Data Landscapte Data Selection of Archival Data Validation and Approval Inventory Creation Data Dependency Mapping Resolve Conflicts Aging Analysis Identified Data 10 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  18. 1.1. Initial Data Assessment Purpose: To understand the data landscape by creating a data inventory. Actions: • Understanding the Data Landscape: Examining the source systems and the data they contain. • Data Inventory Creation: Compiling and organizing all data assets into a comprehensive inventory. Outcome: A clear picture of the data environment, including what data exists, where it is stored, and how it is structured. 1.2. Defining Archival Criteria Purpose: To establish rules for what data should be archived. Actions: • Business Relevance: Determining the importance of data for current operations. • Merging Datasets: Combining related data sets where necessary. • Resolving Conflicts: Addressing any discrepancies or conflicts in the data. Outcome: A clear picture of the data environment, including what data exists, where it is stored, and how it is structured. 1.3. Data Categorization Purpose: To classify data based on its usage, sensitivity, and age. Actions: • Usage Classification: Categorizing data according to how frequently it is used. • Sensitivity Classification: Identifying sensitive data that requires special handling. • Aging Analysis: Determining the age of data to assess its relevance for archival. Outcome: Data is classified, making it easier to determine what should be archived. 11 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  19. 1.4. Data Profiling Purpose: To assess the quality and dependencies of the data. Actions: • Data Quality Assessment: Evaluating the accuracy, completeness, and reliability of the data. • Redundancy & Duplication Check: Identifying and addressing redundant or duplicate data. • Data Dependency Mapping: Understanding how data elements are interrelated. Outcome: A detailed profile of the data, highlighting any issues that need to be addressed before archival. 1.5. Data Identification Purpose: To select and validate the data that will be archived. Actions: • Data Quality Assessment: Evaluating the accuracy, completeness, and reliability of the data. • Redundancy & Duplication Check: Identifying and addressing redundant or duplicate data. • Data Dependency Mapping: Understanding how data elements are interrelated. Outcome: A detailed profile of the data, highlighting any issues that need to be addressed before archival. Final Outcome: Identified Data The process concludes with a set of data that has been thoroughly assessed, categorized, and validated for archival. This data is then moved to the archival storage, ensuring that only relevant and necessary information is retained long-term, optimizing storage costs, and maintaining system performance. 12 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  20. 2. Data Remediation: Approval Documentation Archival or Purge Confirmation Version Control Documentation Tagging for Remediation Stakeholder Sign-off Validation Feedback Loop Review & Present Data Archive or Purge Readiness Assessment Data Correction Data Profiling Data Purging Stakeholder Identification Identify Data Issues Criteria Definition Final Data Check Identified Data Data Writing File User Approval Archive or Purge Approval Archived Data Selection 2. 1. Data Writing Purpose: To correct and format the identified data. Actions: • Data Correction: Address the identified issues to ensure data accuracy and integrity. • Validation: Validate the corrected data for consistency. • Version Control: Implement version control to track changes. Outcome: Corrected data that is ready for the next step in the process. 13 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  21. 2.2. File Selection Purpose: To choose the files that meet the archival criteria. Actions: • Criteria Definition: Define the specific criteria that data must meet to be selected for archival. • Data Profiling: Profile the selected data to ensure it meets the established criteria. Outcome: Selection of the appropriate files for archival. 2.3. Data Purging Purpose: To remove unnecessary or obsolete data, optimizing storage and system performance. Actions: • Purge Execution: Safely and securely remove the identified data that no longer serves a purpose. Outcome: A cleaner, more efficient dataset with only relevant data retained, ready for archival. 2.4. User Approval Purpose: To ensure that stakeholders validate the selected data. Actions: • Feedback Loop: Incorporate feedback from stakeholders and make necessary adjustments. • Stakeholder Identification: Ensure the relevant stakeholders are involved in the approval process. Outcome: Approved data that is ready for archival. 14 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  22. 2.5. Archive or Purge Approve Purpose: To ensure that stakeholders validate the selected data. Actions: • Approval Documentation: Document all approvals for future reference. • Final Data Check: Perform a final check to ensure all data is accurate and ready for archival. • Archival or Purge Confirmation: Confirm the successful archival or purge of data. Outcome: Data that is fully approved and either moved to the archival storage or purged. 2.6. Archival Storage (HDFS) and Purged Data Purpose: To securely store the approved data and manage the removal of obsolete or unnecessary data. Outcome: The data has undergone thorough remediation, including correction, validation, and approval. The approved data is now securely archived in HDFS, ensuring long-term retention and accessibility. Simultaneously, obsolete data has been efficiently purged, freeing up storage space and maintaining system performance. Final Outcome of the Data Remediation Process: The data remediation process is successfully completed, with all necessary data securely archived in HDFS and unnecessary data purged. This ensures both the preservation of critical data and the optimization of storage resources. 15 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  23. 3. Data Governance and Visualization Feedback & Improvement Review Distribution User Training Reporting & Action Access & Permissions Consistency Check Query Issue Archival History Dashboard Functionality Identification Archival Storage (HDFS) Metrics & Dashboards Data Data Access Control Data Audit Execution Data Trends Dashboard Validation Archived Data Screen Design Report Generation Design & Development Audit Planning Historical Data Dashboard Data Reading User Screen SSO Report Enquiry Screen Auditing Data Visulaization 3.1. Data Reading Purpose: To access and read archived data. Tools: Uses Cloudera Impala and HDFS for data storage and reading. Outcome: Efficiently access and retrieve archived data 3.2. User Screen Purpose: To facilitate user interaction with data. Actions: • Screen Design: Creating user-friendly screens for data interaction. • Metrics & Dashboards: Developing metrics and dashboards for data insights. • Access & Permissions: Ensuring proper access control. • Feedback & Improvement: Continuously improving the user interface based on feedback. Outcome: Provides an intuitive interface for users to interact with data 16 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  24. 3.3. SSO Reports Purpose: To generate and distribute reports securely. Actions: • Report Generation: Creating detailed reports from the data. • Data Validation: Ensuring data accuracy before reporting. • Consistency Check: Maintaining consistency across reports. • Review & Distribution: Reviewing and distributing reports to stakeholders. Outcome: Securely generate and distribute accurate and consistent reports, ensuring that stakeholders receive reliable insights 3.4. Enquiry Screen Purpose: To enable data querying and user support. Actions: • Design & Development: Building and refining the enquiry screen. • Data Access Control: Managing who can access specific data. • Query Functionality: Enabling advanced querying capabilities. • User Training: Providing training on how to use the enquiry screen. Outcome: Facilitates effective data querying and user support, improving the ability to extract and analyze specific information 3.5. Auditing Purpose: To audit data processes and ensure compliance. Actions: • Audit Planning: Preparing for audits by organizing data. • Data Audit Execution: Conducting thorough audits. • Issue Identification: Detecting issues during audits. • Reporting & Action: Reporting findings and taking corrective action. 17 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  25. Outcome: Ensures compliance with data management standards through thorough auditing processes. 3.6. Data Visualization Purpose: To provide insights through visual representation of data. Actions: • Historical Data Dashboard: Visualizing past data. • Data Trends Dashboard: Identifying and visualizing trends. • Archival History Dashboard: Tracking and displaying archival history. Outcome: Offers clear and actionable insights through visual representation of data Final Outcome: The process ensures that archived data is accessible, secure, well-audited, and effectively visualized for strategic decision-making and operational efficiency. 18 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  26. Chapter 3: Unstoppable Success. Astonishing Metrics. Revolutionary Solutions from ChainSys 1. Transforming Data Efficiency: Innovative Archival and Purging Solution for a Leading Canadian Telecom Giant ChainSys understands that no two organizations are alike. Our Hadoop-based Archival and Purging solution supports a variety of ERP systems, including SAP ECC, BW, and Hybris. With our solution, you get: Leading Canadian Telecom Company: Successful Archival, Purging, and Storage of Critical Data from SAP Applications with ChainSys’s Smart Data Platform Project Scope • SAP Application Archival: Data identification, archiving, and purging for SAP ECC 6.0, SAP BW, and SAP Hybris applications. • Business Focus: Removed obsolete and unused master and transaction data from existing SAP systems to streamline migration to SAP S/4 HANA. • Data Profiling: Conducted comprehensive profiling and analysis of transaction-intensive data to identify candidates for archiving based on company retention policies. • Telecom Industry Focus: Managed high-volume ERP data within Canada’s leading telecom organization, optimizing system performance and reducing operational costs. 19 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  27. Key Outcomes • Cost Savings: Reduced hardware costs and ongoing data maintenance expenses by archiving and purging non-essential data before migrating to SAP S/4 HANA. • Process Efficiency: Achieved significant reductions in backup and restore times, as well as overall data storage needs, leading to improved operational efficiency. • Clear Data Insight: Provided the business with detailed usage analytics and functional dependencies for master data, enabling better decision-making during the archiving process. • Compliance and Governance: Archived data was securely stored on the ChainSys platform, ensuring compliance with retention policies and providing future access when needed. Products and Services Used Delivered detailed data quality metrics and usage analysis, allowing the business to make informed decisions on data archiving based on functional dependencies and deduplication reports. Handled the complete archival and purging process, ensuring that critical data was securely stored on the ChainSys platform for future access and compliance purposes Telecom Data Sources Secure Archival & Storage Data Profiling Archival & Purging Data Storage Smart Data Platform Data Profiling, Archiving & Purging Process Cost Savings Process Efficiency Clear Data Insight Compliance & Governance 20 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  28. 2. Achieving Data Efficiency: Transforming Archival and Purging for a Global Electronics Manufacturer ChainSys understands that no two organizations are alike. Our Archival and Purging solutions streamline database management, offering significant efficiency gains. With our solution, you get: Global Electronics Manufacturer: Successful Database Reduction and System Optimization with ChainSys’s Smart Data Platform Project Scope • Database Volume Reduction: Reduce and maintain the database volume by 50% from its current size of 11TB. • Regular Purge Implementation: Implement purge activities at regular intervals to sustain optimized performance. • Global Operations: Served a global manufacturer with operations in the USA, UK, Denmark, Japan, China, India, Korea, Taiwan, Philippines, and Malaysia. Key Outcomes • Significant Database Reduction: Achieved a 60% reduction in database size through systematic purge activities, preventing uncontrolled growth. • Improved System Performance: Optimized system performance by minimizing the load from unnecessary data, resulting in faster clone activity and reduced application upgrade timelines. • Cost Efficiency: Avoided costly hardware upgrades and processing expenses by maintaining manageable data volumes. • Agile Implementation: Enabled agile execution with the first round of testing completed within 5 weeks, allowing for a smooth transition to production. • Consistent Future Maintenance: Ongoing purge activities now occur with every clone, ensuring long-term database efficiency. 21 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  29. Products and Services Used Leveraged for data analytics, archive, and purge processes. Enabled cloud-based implementation with minimal footprint and virtual teams operating across global locations. Provided future growth predictions and data insights, empowering the business to make informed decisions regarding database management and system upgrades. Pre-Archive Repository Purge Data Report Global Archival & Storage Data Extraction ERP Electronics Data Sources Archiving & Purging Process Smart Data Platform Database Reduction Cost Agile Efficiency Implementation Improved Future System Performance Maintenance 22 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  30. 3. Revolutionizing Data Management: Accelerated Archival and Migration for Epredia’s Legacy Systems ChainSys understands that no two organizations are alike. Our Data Archival and Migration solutions support a wide range of applications, including JDE, DataFlo, and SAP S/4 HANA. With our solution, you get: Global Leader in Cancer Diagnostics: Seamless Historical Data Archival from JDE and DataFlo to Azure Cloud for Regulatory Compliance and Operational Efficiency. Project Scope • Historical Data Archival: Archiving data from legacy systems JDE (JPOR, JKAL) and DataFlo to Microsoft Azure Data Lake. • Comprehensive Data Identification: Over 1,000 objects identified and archived, ensuring compliance with company retention policies. • Visualization and Inquiry: Configured 15 enhanced inquiry screens and delivered 150+ archival dashboards using appBuilder and appVisualize for seamless data access and visualization. • Lift & Shift: Leveraged a lift-and-shift methodology to move data to the Azure Cloud, enabling a smooth transition to SAP S/4 HANA. Key Outcomes • Efficient Archival: Successfully archived 850 million records in just 8 weeks, significantly reducing operational costs and enhancing compliance. • Enhanced Data Access: Provided over 200 dashboards for business users to view historical data directly from the Azure Cloud, ensuring easy data access and visibility. • Custom Inquiry Screens: Delivered more than 15 application inquiry screens, replicating JDE views for future reference and operational continuity. • Scalable Data Exports: Enabled the download of over a million records in a single export, streamlining data retrieval processes. 23 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  31. Products and Services Used Facilitated the extraction and loading of historical data into Azure Data Mart, ensuring data integrity and seamless migration. Enabled detailed data profiling, validation, and reconciliation, as well as providing dashboards and application screens to mirror the legacy JDE environment. Used to replicate forms and reports, ensuring business users could access and interact with historical data as they did in the original systems. Data Extraction Legacy System Lift & Shift Migration to Azure Cloud Data Access & Visualization Custom Inquiry Screens Scalable Data Exports Efficient Archival Enhanced Data Access 24 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  32. Chapter 4: Detailed Step-by-Step Process of Data Archival & Purging B. Data Retention Policies: Define and document data retention policies, specifying the duration for which different types of data should be retained. 5. Backup and Recovery Preparation A. Data Backup: Securely back up all data that is intended for archival to protect against any potential data loss during the process. Smart Data Platform B. Recovery Plan: Develop and document a recovery plan to restore data from the backup if necessary. 6. Archival Rules Configuration A. Archival Criteria Setup:Define and configure the archival rules within the ChainSys Smart Data Platform, including criteria for data selection, retention periods, and metadata tagging. Pre-Archival Setup and Preparation 1. System Readiness A. Hardware and Software Requirements: Ensure that your hardware and software meet the necessary specifications, including adequate storage, processing power, memory, and compatible operating systems. B. Network Configuration:Confirm that the network infrastructure is optimized, with sufficient bandwidth and security protocols to handle data transfers securely. 2. Platform Installation A. ChainSys Smart Data Platform Installation: Install and configure the ChainSys Smart Data Platform according to your organization’s needs. Set up user roles, permissions, and system parameters specific to the archival process. 3. Data Inventory A. Data Identification: Prepare a comprehensive inventory of all data assets, including databases, files, and unstructured data, to understand the scope and scale of data that will be archived. 4. Compliance and Retention Policy Review A. Legal and Regulatory Compliance: Review and ensure alignment with all relevant legal and regulatory requirements for data retention and archival. 25 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  33. B. Data Retention Policies: Define and document data retention policies, specifying the duration for which different types of data should be retained. 5. Backup and Recovery Preparation A. Data Backup: Securely back up all data that is intended for archival to protect against any potential data loss during the process. B. Recovery Plan: Develop and document a recovery plan to restore data from the backup if necessary. 6. Archival Rules Configuration A. Archival Criteria Setup:Define and configure the archival rules within the ChainSys Smart Data Platform, including criteria for data selection, retention periods, and metadata tagging. Step 1: Data Identification 1. System Readiness A. Hardware and Software Requirements: Ensure that your hardware and software meet the necessary specifications, including adequate storage, processing power, memory, and compatible operating systems. You are Here Smart Data Platform B. Network Configuration:Confirm that the network infrastructure is optimized, with sufficient bandwidth and security protocols to handle data transfers securely. 2. Platform Installation A. ChainSys Smart Data Platform Installation: Install and configure the ChainSys Smart Data Platform according to your organization’s needs. Set up user roles, permissions, and system parameters specific to the archival process. 3. Data Inventory The identification step, as part of the Identify, remedy, govern trio helps organizations identify data elements that are lacking in quality, taking up too much space, or are hardly used. Identification ensures organizations target the right data sets during an archival/purge process. A. Data Identification: Prepare a comprehensive inventory of all data assets, including databases, files, and unstructured data, to understand the scope and scale of data that will be archived. 4. Compliance and Retention Policy Review A. Legal and Regulatory Compliance: Review and ensure alignment with all relevant legal and regulatory requirements for data retention and archival. 26 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  34. Data Assessment: Purpose: Why This Step Exists: The purpose of Data Assessment in Data Archival & Purging is to evaluate the organization's existing data to determine which information should be archived for long-term storage and which should be purged. This step ensures that only relevant, accurate, and compliant data is retained, while obsolete or redundant data is securely removed, optimizing storage and maintaining data integrity. Data Assessment is crucial for making the archival and purging processes efficient and effective. It prevents the unnecessary storage of outdated data, which can clutter systems and increase costs, while also ensuring that irrelevant or redundant data is purged. This process helps organizations maintain the quality, relevance, and compliance of their data management practices. How It Helps: Optimizes Storage Costs By archiving only necessary data and purging what is obsolete, it reduces storage expenses and manages resources more effectively. Enhances Data Quality Ensures that only accurate and important data is preserved in archives, while unnecessary data is removed, maintaining the integrity of both active and historical records. 27 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  35. Ensures Compliance Helps organizations meet legal and regulatory requirements by archiving data according to retention policies and purging data that no longer needs to be retained. Streamlines Data Management Improves the ability to manage data efficiently by categorizing, tagging, archiving, or purging it during the assessment, facilitating easier retrieval and reducing clutter. Data Profiling: Purpose: Why This Step Exists: The purpose of Data Profiling in Data Archival & Purging is to analyze the structure, content, and quality of data before it is archived or purged. This step helps in understanding the characteristics of the data, such as patterns, distributions, and anomalies, ensuring that the data is accurate, consistent, and appropriate for long-term storage or removal. Data Profiling is essential for identifying data issues that could impact the quality and usability of the information being archived or purged. By profiling the data, organizations can detect and address inconsistencies, duplicates, and errors before finalizing the archival or purging process, ensuring that only clean, reliable data is retained or securely removed. 28 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  36. How It Helps: Improves Data Quality: Identifies and resolves issues such as missing values, duplicates, and inconsistencies, ensuring that only high-quality data is archived and irrelevant data is purged effectively. Facilitates Data Standardization: Helps in standardizing data formats and structures, making the management and retrieval of archived data easier and ensuring consistent removal of obsolete data. Supports Compliance: Ensures that data meets regulatory and business standards before it is archived or purged, reducing the risk of non-compliance and legal issues. Enhances Data Understanding: Provides insights into data characteristics, aiding in informed decision-making about what data to archive or purge, and improving overall data management strategies. Data Selection: 29 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  37. Purpose: Why This Step Exists: The purpose of Data Selection in Data Archival is to identify and choose the specific data sets that should be archived based on relevance, importance, and compliance with retention policies. This step ensures that only necessary and valuable data is preserved for long-term storage. Data Selection is crucial to avoid archiving unnecessary or irrelevant data, which can lead to wasted storage resources and cluttered archives. It ensures that only data with ongoing value, legal significance, or historical importance is retained, aligning with organizational goals and regulatory requirements. How It Helps: Optimizes Storage Efficiency: By selecting only the most relevant data, it reduces storage costs and maximizes the efficient use of archival resources. Ensures Compliance: Helps meet legal and regulatory requirements by archiving data that is required to be retained. Improves Data Management: Streamlines data management by keeping archives organized and focused on valuable information. Enhances Retrieval and Usability: Makes it easier to retrieve and use archived data by focusing on what is truly important. Step 2: Data Remediation: You are Here Smart Data Platform 30 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  38. In the Remediation step, targeted data elements identified during the previous phase are addressed to correct any issues or inconsistencies. This involves applying the business rules engine to enforce predefined data quality standards and transformation rules. The engine ensures that data is cleaned, validated, and aligned with business requirements, correcting errors and standardizing formats. This step is crucial for maintaining data integrity and preparing data for accurate and compliant archival. Data Writing: Purpose: Why This Step Exists: The purpose of Data Writing in Data Archival & Purging is to validate and correct selected data before it is either archived or purged. This step ensures that data is accurately and securely handled, whether it is being preserved in archival storage or removed from active systems, maintaining its integrity and compliance throughout the process. Data Writing is essential for ensuring that data is processed correctly, whether for long-term archival or secure purging. Proper validation and correction help prevent issues such as data corruption, loss, or discrepancies that could affect the quality of archived data or the effectiveness of purged data removal. 31 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  39. How It Helps: Ensures Data Integrity: Guarantees that data is accurately validated and corrected before being archived or purged, preventing any loss or corruption during the process. Facilitates Long-Term Preservation: For archived data, ensures that it is recorded in a format and structure that supports its longevity and accessibility for future retrieval. Supports Compliance: Adheres to regulatory and organizational standards for data retention and purging, ensuring that both archival and removal processes meet required guidelines. Enables Efficient Retrieval and Removal: Organizes data in a way that facilitates easy access and retrieval when archived, and ensures that purged data is securely and thoroughly removed from systems. File Selection: Purpose: Why This Step Exists: The purpose of File Selection in Data Archival is to identify and choose specific files that are suitable for long-term storage. This step ensures that only files with ongoing relevance, legal significance, or business value are archived, reducing clutter and optimizing storage. File Selection is crucial to avoid archiving unnecessary or redundant files, which can consume valuable storage space and complicate retrieval processes. It ensures that the archival system remains efficient and focused on preserving important files, aligning with organizational and regulatory requirements. 32 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  40. How It Helps: Optimizes Storage Space: By selecting only necessary files, it minimizes storage costs and prevents the accumulation of irrelevant data. Ensures Compliance: Helps in adhering to legal and regulatory standards by archiving files that must be retained. Enhances Data Management: Keeps the archival system organized, making it easier to manage and retrieve important files. Improves Accessibility: Ensures that only pertinent files are archived, making future retrieval quicker and more efficient. User Approval: Purpose: Why This Step Exists: The purpose of User Approval in Data Archival & Purging is to obtain formal consent from relevant stakeholders, including data owners & business users, before proceeding with the archival or purging of selected data. This step ensures that all parties agree on the data being archived or purged, reducing the risk of disputes or issues later on. User Approval is crucial for confirming that the data selected for archival or purging aligns with business needs, legal requirements, and organizational policies. It serves as a final checkpoint to ensure that the data meets all necessary criteria before it is permanently moved to archival storage or removed from active systems. 33 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  41. How It Helps: Ensures Stakeholder Buy-In: Involves key stakeholders in the decision-making process, securing their agreement and support for the archival or purging actions. Minimizes Errors: Provides an opportunity to identify and correct any potential mistakes or oversights in data selection before finalizing archival or removal. Enhances Accountability: Establishes a clear record of approval, which can be referenced if any questions or issues arise in the future. Supports Compliance: Ensures that the archival or purging process adheres to organizational policies and regulatory requirements by involving the appropriate decision-makers. Archive or Purge Approve: Purpose: Why This Step Exists: The purpose of Archive or Purge Approval is to secure final authorization to proceed with either archiving selected data or purging unnecessary data. This critical step ensures that all preparations are complete, and that the data meets the necessary standards for either long-term storage or removal. Archive or Purge Approval serves as the last verification checkpoint before data is either permanently archived or purged. It confirms that the data is ready for its final action, aligns with retention and deletion policies, and meets quality & compliance requirements. This step helps prevent potential errors, data loss, or compliance issues that could arise from prematurely archiving or purging data. 34 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  42. How It Helps: Ensures Readiness: Verifies that all preceding steps have been correctly completed, ensuring the data is fully prepared for long-term storage or secure removal. Enhances Data Integrity: Confirms that the data is accurate, complete, and in the correct format, ensuring its integrity in the archive or correctness in purging. Supports Compliance: Ensures that the archival or purging process adheres to organizational policies and legal requirements, reducing the risk of non-compliance. Provides a Final Checkpoint: Acts as a final safeguard to catch any last-minute issues or discrepancies before data is permanently archived or purged. Archival Storage: Purpose: Why This Step Exists: The purpose of Archival Storage in Data Archival is to securely store data for long-term retention while ensuring it remains accessible when needed. This step focuses on preserving data integrity and maintaining its availability for future reference or compliance requirements. Archival Storage is essential for safeguarding historical data that must be retained for legal, regulatory, or business purposes. It provides a secure environment where data is protected from loss, degradation, or unauthorized access, ensuring that it remains intact and accessible over time. 35 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  43. How It Helps: Long-Term Preservation: Ensures that data is securely stored in a way that prevents loss, corruption, or degradation, maintaining its integrity over extended periods. Regulatory Compliance: Supports adherence to legal and regulatory requirements by keeping data available and intact for the duration of its required retention period. Cost Efficiency: Optimizes storage costs by moving data to cost-effective storage solutions designed for long-term retention, freeing up more expensive resources for active data. Data Accessibility: Guarantees that archived data can be retrieved when necessary, supporting business needs, audits, and legal inquiries. Step 3. Data Governance: You are Here Smart Data Platform The final step in the data archival process is governance, where a robust workflow ensures precision and compliance. Configurable workflows, built with no-code tools, facilitate seamless oversight and prevent errors. These workflows provide structure, enforce standards, and enable real-time monitoring, ensuring the integrity of the archival and purge processes while maintaining data accuracy and regulatory compliance. 36 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  44. User Screen: Purpose: Why This Step Exists: The purpose of the User Screen in Data Archival is to provide a comprehensive interface for users to interact with and manage the archival process. It ensures that users can efficiently track, validate, and execute data archival tasks while maintaining visibility and control over the data being archived. The User Screen exists to facilitate user engagement in the data archival process, offering a streamlined and intuitive way to manage archival tasks. It ensures that users have access to necessary tools and information, enabling them to make informed decisions & perform tasks accurately. This step helps in minimizing errors, improving user efficiency, & ensuring that the archival process adheres to organizational standards. How It Helps: Improves Usability: Provides a user-friendly interface for interacting with archival tasks, making it easier for users to navigate through the process and perform necessary actions. Enhances Visibility: Displays relevant information about the data being archived, including status, metadata, and compliance details, giving users a clear view of the archival process. Facilitates Monitoring: Allows users to track the progress of archival tasks, identify any issues or discrepancies, and take corrective actions as needed. Supports Decision-Making: Offers tools and features that help users make informed decisions about data archival, such as validation checks, approval workflows, and reporting. 37 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  45. SSO Reports Purpose: Why This Step Exists: The purpose of Single Sign-On (SSO) Reports is to provide comprehensive insights into the usage, performance, and security of the SSO system. These reports help administrators and stakeholders monitor and analyze SSO activities, ensure compliance with access policies, and identify potential issues or improvements needed in the authentication process. SSO Reports are essential for maintaining oversight of authentication activities and ensuring that the SSO system operates effectively. They help in tracking user access patterns, detecting anomalies or security breaches, and verifying that the SSO solution aligns with organizational security and compliance requirements. This step is crucial for maintaining the integrity and efficiency of the SSO system. How It Helps: Monitors Usage: Provides insights into how frequently and effectively users are utilizing SSO, helping to identify trends and usage patterns. Enhances Security: Tracks login attempts, successful and failed authentications, and any suspicious activities to ensure the security of user accounts. Supports Compliance: Ensures that SSO activities comply with organizational policies and regulatory requirements, helping to meet audit and compliance standards. Facilitates Troubleshooting: Helps in diagnosing issues with the SSO system by providing detailed logs and error reports, enabling quick resolution of problems. 38 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  46. Enquiry Screen: Purpose: Why This Step Exists: The purpose of the Enquiry Screen is to provide users with an interactive interface for submitting, tracking, and managing enquiries or requests related to data archival. It serves as a centralized platform for users to initiate enquiries, seek support, and obtain information, ensuring efficient handling of queries and issues. The Enquiry Screen exists to streamline the process of handling user queries and requests, ensuring that they are addressed in a timely and organized manner. It helps in capturing & managing enquiries related to data archival, providing a structured approach to support & communication. This step is crucial for maintaining effective user support and ensuring that all queries are resolved efficiently. How It Helps: Centralizes Requests: Provides a single platform where users can submit and track their enquiries, reducing the risk of missed or overlooked requests. Enhances Communication: Facilitates clear and direct communication between users and support teams, improving the efficiency of query resolution. Improves Tracking: Allows users to monitor the status of their enquiries, including updates and resolutions, ensuring transparency and accountability. Streamlines Support: Helps support teams to manage and prioritize enquiries, ensuring that they are addressed based on urgency and relevance. 39 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  47. Auditing: Purpose: Why This Step Exists: The purpose of Auditing in Data Archival is to systematically review and assess the archival processes, ensuring that they comply with organizational policies, regulatory requirements, and industry best practices. Auditing helps verify the accuracy, completeness, and integrity of archived data, and ensures that archival practices are consistently followed. Auditing is crucial for maintaining the quality and compliance of the data archival process. It provides an objective assessment of archival activities, identifies any discrepancies or issues, and ensures that the archival process adheres to established standards. This step helps in mitigating risks, improving processes, and demonstrating accountability. How It Helps: Verifies Compliance: Ensures that archival processes comply with legal, regulatory, and organizational policies, reducing the risk of non-compliance. Enhances Data Integrity: Confirms that the data archived is accurate, complete, and securely stored, maintaining its integrity over time. Identifies Issues: Detects any discrepancies, errors, or issues in the archival process, allowing for timely corrective actions. Improves Transparency: Provides a clear record of archival activities, facilitating transparency and accountability in the data management process. 40 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  48. Data Visualization: Purpose: Why This Step Exists: The purpose of Data Visualization in Data Archival is to provide a clear and insightful representation of archival data, facilitating the understanding of historical trends, data integrity, & archival activities. Dashboards, help in monitoring, analyzing, & reporting on the status and effectiveness of data archival processes, ensuring transparency & informed decision-making. Data Visualization is essential for translating complex archival data into accessible and actionable insights. It helps stakeholders quickly grasp historical trends, assess data integrity, and track archival activities, ensuring that archival processes are transparent and data is managed effectively. This step enhances decision-making and promotes accountability in data management. How It Helps: Historical Data Dashboard: Provides a comprehensive view of archived data over time, allowing users to analyze historical trends, patterns, and changes. This helps in understanding long-term data management and assessing the impact of archival practices. Data Trends Dashboard: Highlights trends and fluctuations in archival data, helping identify emerging patterns or issues. This dashboard supports proactive decision-making and enables adjustments to archival strategies based on observed trends. Archival History Dashboard: Tracks the details of archival activities, including dates, actions taken, and responsible parties. This dashboard ensures transparency and accountability by providing a clear record of the archival process and facilitating audits. 41 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  49. Post-Archival Support from ChainSys ChainSys provides comprehensive post-archival support to ensure the continued effectiveness and accessibility of your archived data. Our services include: Data Retrieval and Migration: Expertise in retrieving archived data and facilitating its migration to contemporary systems or formats as required. System Maintenance: Ongoing maintenance of archival systems to ensure operational efficiency and accessibility over time. Compliance and Security: Vigilant adherence to regulatory standards and robust protection measures to safeguard archived data from unauthorized access and breaches. Data Integrity Assurance: Regular integrity checks to confirm that archived data remains unaltered and free from corruption. User Support: Dedicated assistance for users needing access to or interaction with archived data, including troubleshooting and training. Technology Upgrades: Implementation of updates to archival technologies and systems to align with advancements and evolving data management practices. 42 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

  50. Authors Amarpal Nanda President of EDM amarpal.nanda@chainsys.com Suresh Rajput VP Data Solutions suresh.rajput@chainsys.com Bhaarath JK Lead Marketing Vishal Sridhar Digital Marketing Executive vishal.sridhar@chainsys.com bhaarath.kothandaraman@chainsys.com Schedule Demo 43 Archive Smart & Save Big Time with ChainSys AI-Powered Smart Data Platform

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