Build an Automated, Optimized, Self-Healing Data Ecosystem with Hitachi Data Reliability Engineering Services
In today’s data-driven landscape, organizations heavily rely on accurate and high-quality data to make informed business decisions. Experts predict that a staggering 2.5 quintillion bytes of data are generated daily, with this number projected to double every two years1.
Traditional data observability and quality management approaches often focus on periodic checks and audits, providing only a snapshot of data quality at specific intervals. Without real-time access to data pipelines and systems, chief data officers and their data teams can’t react promptly to issues as they occur. The gap between data observability and quality inhibit organizations’ ability to react promptly to emerging issues compromising the accuracy and timeliness of data-driven decision-making.
Data and analytics leaders must take pragmatic and targeted actions to improve their enterprise data quality if they want to accelerate their organizations’ digital transformation”, says Gartner, whose recent research estimates that poor data quality costs organizations an annual average $12.9 million.
Modern organizations require a modern approach to data observability and quality management. With data reliability engineering organizations can accelerate your path to self-healing data ecosystem and data democratization.
Demystifying Data Management with an Emphasis on Data Quality, Trust and Reliability
Without data reliability engineering resources to support mission-critical needs, data stewards can’t detect and mitigate data anomalies that lead to suboptimal decision making, operational inefficiencies, and compromised customer experiences.
Unfortunately, not all organizations have a dedicated data engineering function to manage mission-critical processes and applications. According to 451 Research’s Data-Driven Practices 2022 Survey3, only a slight majority (65.4%) of respondents report their organization had a dedicated data engineering team. That number drops to 46.8% for organizations that report only “some” or “few” of their strategic decisions are based on data.
It’s clear that there is now a greater focus on the maintenance and consistency of supporting data systems and data pipelines, shifting data quality responsibilities upstream to emergent technical roles such as the data engineering function.
Introducing Hitachi Data Reliability Engineering Services, an end-to-end suite of professional services, methodology, tools, and frameworks that helps organizations unlock the full potential of their enterprise data. As an integral part of the Hitachi Application Reliability Center (HARC), Hitachi Data Reliability Engineering Services helps modern data teams deliver high quality, consistent, and trustworthy data. Essentially, our data reliability engineering services enable organizations to automate and scale data operations by balancing speed, data reliability, and data integrity.
How Important Is Data Reliability?
Organizations today must harness the immense power of data to enhance customer service, operational effectiveness, and regulatory compliance. However, without effective data management, costly issues arise, causing organizations to lose an average of $12.9 million annually. Surprisingly, more than half of these organizations are unaware of the true cost of unreliable data and more than half aren’t even aware of what unreliable data is costing them.
Reliable, timely, and accessible data is essential for organizations. Without it, support chatbots, inventory management systems, and financial planning tools may falter, resulting in lost revenue, diminished business credibility, and a negative customer experience. Unreliable data pipelines can disrupt downstream service computations and machine learning models. Moreover, delays in resolving data issues can hinder enterprise performance and prevent timely data-driven insights from reaching decision-makers.
Transforming missed opportunities into realized potential is where Hitachi excels. Our proactive maintenance of data pipelines and observability services address data quality and origin issues. With Hitachi Data Reliability Engineering Services, organizations gain an automated and optimized data ecosystem that enhances business efficiency, accelerates operational excellence, bolsters data resiliency, and scales data reliability. This fosters increased data trust and transparency, enabling data teams to conquer modern data management challenges and ensure the consistent reliability, security, and availability of data when it matters most.
