May 2023 Summaries

The Acceldata Data Observability Platform offers unique cloud chargeback and budgeting features, enabling tracking, evaluation, and allocation of infrastructure costs across business units and data platforms. These capabilities give data teams more control in managing costs for their cloud data environments and help them navigate the increasingly complex nature of cross-organizational resource and spend allocation. The platform's Chargeback feature allocates funds to different business units within an organization based on previous spending records, while its Budgeting feature allows users to establish budgets according to specific organizational needs. Better visibility into cloud chargeback and budgeting empowers data teams to align cloud usage with business goals, identify cost optimization opportunities, and ensure resources are allocated efficiently.

In a recent TMForum Webinar, experts discussed the importance of scalable and robust data platforms for telecom operators in today's data-driven era. They explored various data platform trends that should be prioritized by data leaders, including data observability to address critical issues faced by data teams. The discussion highlighted how rapidly advancing technology and growing customer demands are leading to a paradigm shift in CSPs, with big data playing a crucial role in this transformation. Data Observability can help CSPs meet the growing data demands by providing deeper insights into operational blind spots present in both on-premises and multi-cloud environments. The Acceldata Data Observability Platform offers features such as cost optimization, data reliability, and real-time insights to optimize cloud data platforms.

The importance of data analytics in business operations has led to an increase in captured data, making data reliability essential for accurate decision-making. Data comes from various sources and is often transformed through complex pipelines. To ensure high-quality data, organizations need to shift left their approach to data reliability by incorporating observability practices early in the data lifecycle. This helps detect and address issues as soon as possible, reducing costs and improving overall data quality. By shifting left, businesses can optimize resources, control costs, and produce better data products, ultimately gaining a competitive advantage.