Modern Data Modernization Strategies & Solutions

Slide Note
Embed
Share

In the world of data modernization, Akan Veri Analitiği, led by Kutay Çilingiroğlu, Ph.D., a Sr. Solution Architect, focuses on RDBMS, Big Data, Enterprise Data Integration, and Delivery, among others. Advantages of Change Data Capture (CDC) include enabling smarter decisions, minimizing production impact, and reducing processing requirements. The process involves modern integration steps for real-time, heterogeneous, complete, and automated operations. Technologies like Qlik Replicate and Replicate for Streaming enhance data replication capabilities across diverse sources and targets such as SAP, databases, mainframes, and cloud services.


Uploaded on Sep 16, 2024 | 0 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

E N D

Presentation Transcript


  1. Akan Veri Analitii Kutay ilingiro lu, Ph.D. Sr. Solution Architect kutay.cilingiroglu@onedatalake.com

  2. Data Modernization RDBMS Big Data Enterprise Data Integration & Delivery NoSQL SAP Cloud Mainframe

  3. Data Modernization Steps

  4. Advantages of Change Data Capture Enables smarter and Enables smarter and faster decisions faster decisions Minimizes production Minimizes production impact impact Reduces bandwidth and Reduces bandwidth and processing requirements processing requirements CDC Is the Foundation of Modern Data Architectures

  5. Modern Integration 1. REAL-TIME 2. HETEROGENEOUS 3. COMPLETE & AUTOMATED 4. SCALE & STABILITY

  6. Qlik Replicate

  7. Replicate for Streaming

  8. 1. DL/DW Automation TARGETS SOURCES SAP Database Mainframe Azure Google AWS ECC DB2 z/OS Oracle Cloud SQL (MySQL, Postgres) DBaaS (SQL DB) RDS (MySQL, Postgres, MariaDB, Oracle, SQL Server) ERP IMS/DB SQL Server Cloud Storage DBaaS (MySQL, Postgres) Aurora (MySQL, Postgres) CRM VSAM DB2 iSeries Dataproc ADLS Gen1 & 2 S3 SRM COBOL Copybooks DB2 z/OS Pub/Sub BLOB EMR GTS DB2 LUW BigQuery HDInsight Kinesis MDG MySQL Snowflake Event Hub Redshift SAP ECC - HANA MariaDB Synapse (SQL DW) SAP HANA (database) Percona Snowflake PostrgeSQL Snowflake Cloud Databricks (on Oracle, SQL, DB2 LUW, HANA) Sybase ASE Databricks Database Informix Amazon RDS (SQL Server, Oracle, MySQL, Postgres) Oracle SAP HANA SQL Server ODBC Amazon Aurora MySQL DB2 LUW MongoDB Amazon Aurora PostgreSQL SaaS EDW Data Lake MySQL Amazon Redshift PostgreSQL Salesforce Oracle Autononous DW Hortonworks Azure SQL Server MI Sybase ASE Exadata Cloudera Google Cloud SQL (MySQL, PostgreSQL) Informix EDW Teradata MapR MemSQL Netezza Amazon EMR Vertica Azure HDInsight Flat Files Exadata Sybase IQ Google Dataproc Teradata SAP HANA XML Netezza Microsoft PDW JSON Flat Files Vertica Delimited (e.g., CSV, TSV) Pivotal Delimited (e.g., CSV, TSV) Streaming SAP Kafka Amazon Kinesis SAP HANA (database) Azure Event Hubs 8 MapR Streams

  9. Demo Targets Demo Sources RDBMS DATA LAKE Oracle PostgreSQL EDW Qlik Replicate Oracle PostgreSQL RDBMS In-Memory MSSQL Kafka Log Stream FILE MongoDB MSSQL EDW Transform Filter Databricks Azure Event Hubs FILE SAP STREAMING Azure Storage

Related