Data Analytics - Pilog group

1. SMART INTEGRAPHICS Establish Data Quality for “RISE with SAP” Data Migration Simplified

2. Smart InteGraphics DATA INTEGRATION Integrating data from various sources such as databases, ERPs, files, and videos boosts organizational efficiency by forming a unified data ecosystem. This integration facilitates seamless access to diverse data types, enhancing insights and decision-making while maintaining data consistency and accuracy across platforms. DATA MIGRATION Data migration enables organizations to upgrade their systems or infrastructure, ensuring access to improved technology and performance. It enhances data quality by cleaning and transforming data during the transfer process DATA ANALYTICS Data analytics enhances decision-making by providing actionable insights derived from data. It improves operational efficiency by identifying trends and inefficiencies, leading to cost savings

3. DATA integration Data integration with various sources, including databases, ERPs, files,and videos, enhances organizational efficiency by creating a cohesive data ecosystem. This integration allows for seamless access to diverse data types, improving insights and decision-making while ensuring data consistency and accuracy across platforms ⯀ Databases: Structured data from relational databases (like MySQL, Oracle, and SQL Server) and NoSQL databases (like MongoDB and Cassandra) that store critical business information. ⯀ Enterprise Resource Planning (ERP) Systems: Comprehensive data from ERP solutions (such as SAP, Oracle ERP, and Microsoft Dynamics) that manage core business processes, including finance, HR, and supply chain. ⯀ Files: Unstructured and semi-structured data from various file formats (like CSV, Excel, JSON, and XML) that contain important information for analysis.

4. ⯀ Image and Videos: Multimedia data from video files and streaming platforms, which can provide insights through visual content analysis and audience engagement metrics. ⯀ APIs and Web Services: Data from external applications and services accessed via APIs (Application Programming Interfaces), allowing integration with third-party systems and cloud services. Data obtained from web services, including social media platforms and online surveys, which can enrich understanding of customer behaviour and market trends. ⯀ Cloud Storage: Data stored in cloud solutions (like AWS, Google Cloud, and Azure) that offers flexibility and scalability for integrating various data sources. ⯀ SOcial media Data extraction from social media platforms like Facebook, YouTube, LinkedIn, and Twitter involves utilizing their APIs to gather relevant user profiles, posts, and engagement metrics

5. Smart InteGraphics accelerates RISE with SAP program with a cloud-ready data transformation solution with embedded Data Quality Pre-defined source and target staging schemas, entities and transformation processes that includes all the preconfigured mappings, rules, business logic required for accelerated transformations for RISE with SAP Programs Pre-validated Transformation jobs are categorized & executed per business area/module e.g, Procure to Pay, Order to Cash, Acquire to Retire, Source to Pay, Plan to Inventory etc. Transformations can include all the objects or a subset. Smart InteGraphics is a SaaS Platform, available as a term license e.g. quarterly or annually [Zero Infrastructure cost], pure OPEX model Optional outsourcing of data standardization work to PiLog Data Refineries Data Quality + RISE with SAP = Successful Business Transformation With PiLog’s Smart InteGraphics business as a service cloud offering, RISE with SAP ensures lower costs, lower risk, lower effort with high data quality and acceleration data transformations with quick realization

6. FASTER TIMES Ready-to-access cloud availability ⯀ Pre-defined data transformation jobs ⯀ Pre-validated data migration groupings ⯀ Pre-defined sequences, scheduling of jobs as per business process interdependencies INNOVATIVE TIME TO VALUE TIMES Cost Effective with Data Quality ⯀ Almost immediate value with readily available cloud instance (no additional infrastructure or environment provisions required) ⯀ Pre-defined ISO aligned data definitions and mappings QUICK START QUALITY IMPROVEMENT ISO 8000, 22745, 14224,29002 and data repositories ⯀ Business Dashboard for RISE with SAP ⯀ Highlight meta mappings not done ⯀ Highlight missing / incorrect transformation errors LOWER RISK LOWER RISK Manageable Processes and accurate estimations ⯀ Highly automated transformation processes with low key resources ⯀ Use of PiLog AI services to improve data quality and remove redundancies ⯀ High confidence in project delivery on time and quality assurance. POWERING ACCELERATION

7. Total Business Value The following Bench markings are derived by comparing with traditional migration programs & tools based on ⯀ Non-automated ETL tools ⯀ Non standard data practices ⯀ Resource & Expertise intensive programs ⯀ Capital investment ⯀ Non-Data Quality outcome EFFORT / COST REDUCTION TIMES ⯀ Highly automated transformation processes with low key resources ⯀ Use of PiLog AI services to improve data quality and remove redundancies FASTER IMPLEMENTATION TIMES ⯀ Pre-defined data transformation jobs ⯀ Pre-validated data migration groupings ⯀ Pre-defined sequences, scheduling of jobs as per business process interdependencies ACCELERATE - TTV TIMES ⯀ Almost immediate value with readily available cloud instance (no additional infrastructure or environment provisions required) ⯀ Pre-defined ISO aligned data definitions and mappings DATA QUALITY IMPROVEMENT ⯀ Business Dashboard for RISE with SAP ⯀ Highlight incomplete meta mappings ⯀ Highlight missing / incorrect transformation errors

8. Data MIGRATION ⯀Data Extraction Extract Data: Pull data from the source systems using methods like SQL queries, APIs, or file imports. Loading to Staging Area: Load extracted data into a staging area for further processing and validation. ⯀Data Validation Perform Quality Checks: Validate data for accuracy, completeness, and consistency (e.g., type validation, null checks). Conduct Sample Testing: Review a subset of data to ensure its quality and correctness.processing and validation. Automate Validation: Use automated tools for faster validation of larger datasets.

9. ⯀ Data Transformation Apply Mapping: Pull data from the source systems using methods like SQL queries, APIs, or file imports. Cleanse Data: Load extracted data into a staging area for further processing & validation. Enrich Data: Enhance data by adding missing information or deriving new values.

10. ⯀ data consolidation and merging Consolidate Sources: If migrating from multiple systems, merge data into a unified dataset. Resolve Conflicts: Address discrepancies during merging by applying defined rules. Integrate Data: Ensure the merged data fits the target schema and maintains integrity. ⯀ Data Loading Load to Target System: Transfer the validated and transformed data into the production environment. Monitor the Loading Process: Track the process for any errors or issues that may arise.

11. ⯀ Reconciliation Post-Migration Validation: Perform comprehensive checks to verify data completeness and accuracy in the target system. Create Audit Trails: oDocument the migration process, including discrepancies and resolutions. Stakeholder Review: oEngage stakeholders to review the final data and ensure it meets business requirements.

12. ⯀ Case Study 1 Data Migration, Transformation & Orchestration A PiLog Onboarding May’21 Total Business Areas 10 Total Extraction Jobs 405 Total Generation Jobs 287 Feb’22 Mch’22 B Go-live area 1 Apr’22 May’22 Total Entities Processed 152 Volume Records Extracted Volume Records Generated TIMELINE Jun’22 C Go-live area 2 Jul’22 589 472 146 30 600 426 Aug’22 D Go-live area 3 Sep’22 E Go-live area 4 Total Mapping files jobs 68 Max Job Records Extracted Max Job Records Generated F Apr’23 Go-live area 5 76 338 938 1 370 397 Aug’23 Go-live area 6 G Large player in Food & Beverages Industry. Scope: ⯀ Multi ERP to ERP Migration ⯀ On-premise to private Cloud ⯀ Multiple Business Units with multiple go-lives

13. ⯀ Case Study 2 Data Migration & Transformation Total Business Entities 9 Total Extraction Jobs 1000+ Total Transformation Jobs 300+ Data Entities Processed Volume Records Extracted 20M Volume Records Transformed 20M 2000+ Total Mapping files jobs 100+ Max Job Records Extracted 1M Max Job Records Transformed 1M Large player in Oil & Gas Industry Project Duration: 18 Months Scope: ⯀ SAP ERP to S4 Migration ⯀ 10+ Business Units ⯀ On-Premise

14. ⯀ Case Study 3 Data Migration & Transformation Total Business Entities 9 Total Extraction Jobs 1000+ Total 2018 Contract Signed with all associates Transformation Jobs 300+ Implementation and Transformation of data Data Entities Processed Volume Records Extracted 20M Volume Records Transformed 20M Data cleansing and category unification TIMELINE Transactional Data Structuring 2000+ Business Rules, validations, conversions, mapping and loading. Total Mapping files jobs 100+ Max Job Records Extracted 1M Max Job Records Transformed 1M Data Governance Solution Implementation Large player in Mining and Refinery Industry. Project Duration: 24 Months Scope: ⯀ Master Data (MM, SM, PM, Finance Objects, HR Objects ⯀ Transactional Data (S2P, R2R, P2P, H2R, EAM, P2I Processes

15. ⯀ Data Analytics Data analytics streamlines data migration, ensuring accuracy and quality. It identifies inconsistencies, minimizes errors, and reduces downtime.This results in efficient, secure, and cost-effective migrations. Actionable insights into data trends and usage are also unlocked MIRAI iMirAI leverages cutting-edge artificial intelligence to deliver advanced analytics, intuitive insights, and natural language processing (NLP) capabilities. This innovative platform allows users to interact effortlessly with data through NLP-driven questionnaires, enabling them to extract meaningful information

16. CONTACT US Dubai Silicon Oasis, Mirpur 2 DDP,Building A2, United Arab Emirates +971 568421293 info@integraldataanalytics.com