Data is considered the most valuable resource in today’s world, as all industries and businesses rely on various forms of data. However, for data to be usable, it must undergo processing, as raw data is often unreadable by humans or even machines. The quality of these processing steps is crucial for effective industrial and business operations, but can be challenging to maintain, especially with unexpected events such as a surge in data volume or lack of computing resources. In addition, errors in data processing scripts can have serious consequences. To address these challenges, Cloud computing and DevOps have emerged as promising technologies. Cloud computing provides fast, flexible, scalable, and cost-effective computing resources, while DevOps offers automated software development and deployment to reduce human error. By combining these technologies, the data processing process can be optimized and streamlined, giving rise to the term DataOps.

In addition to giving you a clear understanding of DataOps, we will also provide a comprehensive explanation of how to implement DataOps and the benefits of using it as a technology solution for your company.Rapid Results: By gradually implementing your company’s analytics platform, you can significantly shorten the data collection process from months to weeks. Data can be processed through your pipeline in a matter of minutes or hours instead of taking weeks or months. Greater Precision: Leverage data stewardship services to proactively identify data quality issues before they become visible on your executive dashboards, and receive guidance on how to resolve them. Ongoing Monitoring: Monitor your progress towards achieving your data quality improvement goals. Cost Savings: Cut down on development and support costs by up to 300% by using fewer resources to create and maintain code. Enhanced Security: Ensure secure data transmission to dedicated databases by encrypting it.

In this webinar, we aim to provide you with a thorough understanding and guidance on the concept of DataOps. • Introduce the speakers and the company • Concept of DataOps • Use Case: image and video data type processing • Use case: ETL • DataOps in different industries: Automotive; Healthcare & Banking • Q&A