August 2021 Summaries

The concept of Schrodinger's Cat is used as an analogy for how modern businesses are dealing with their data. Just like the cat in the box, data can be both alive and dead until it is observed or analyzed. As companies undergo digital transformation, they face challenges managing complex data environments. Data observability tools offer a comprehensive view of data at rest, during processing, and through pipelines, helping to detect potential problems and automate solutions. These tools go beyond traditional performance monitoring, data management, and data pipeline management by providing more powerful, efficient, and intelligent capabilities for modern data operations.

Observability is a crucial aspect of IT management that has evolved over time from mainframe system monitoring tools to modern Application Performance Management (APM) tools. However, Data Observability has emerged as a separate and essential concept in recent years, focusing on managing and optimizing distributed data infrastructure for real-time analytics and AI applications. While both observability and Data Observability share methodologies, they serve different purposes and cater to distinct user groups within enterprise IT. APM tools are application-centric and primarily focus on monitoring monolithic and microservice applications, while Data Observability tools provide holistic insight and control into data pipelines across multiple layers of complex, distributed data systems. Acceldata offers the only true Data Observability solution available today, providing a comprehensive end-to-end platform for managing and optimizing data infrastructure.

Data engineers and analysts have become crucial to businesses due to their ability to provide near real-time analyses and accurate predictions that improve decision making, reduce risks, and boost revenues. However, many data engineers face challenges in their job, primarily revolving around difficulties with data sets, including finding the right ones, dealing with changing data structures, and maintaining high performance. Companies have invested heavily in cutting-edge data platforms but often fail to invest in tools that grant visibility and control over the data itself. Data observability is a 360-degree view into data health, processing, and pipelines, providing predictive and automation capabilities for modern heterogenous data infrastructures. Acceldata Torch offers an automated set of modern data management capabilities to ensure data accuracy, reliability, and completeness throughout the entire data pipeline, helping keep data engineers happy and productive.