Real-time data analytics is the process of collecting and analysing data as it is generated, delivering insights to users at the moment they are needed. DataOps, on the other hand, is a collaborative data management approach designed to accelerate data delivery, maintain data quality and maximise its value. When implemented together, these practices form a formidable force that can significantly enhance business operations, says Nathi Dube, Director of PBT Innovation.
“DataOps brings iterative and continuous improvement to data products, ensuring they remain relevant and up to date. Real-time analytics gives organisations the ability to assess performance and make informed decisions while events are unfolding,” says Dube. “This is a powerful combination that can see a business truly reach data-driven status.”
The right approach
Successfully implementing real-time analytics and DataOps requires several considerations.
Management buy-in
“In my experience, senior management support is essential for organisation-wide data initiatives. It ensures resources are allocated appropriately and projects receive the attention they require. For instance, executives can mandate that all official reporting comes directly from real-time analytics platforms, encouraging teams to prioritise data accuracy and system responsiveness,” says Dube.
Crucially, real-time data requirements must be factored in early, influencing system architecture from the ground up to support timely data processing.
The right tool ecosystem
To fully realise the benefits of DataOps and real-time analytics, organisations must invest in the right tools – particularly those that support event-driven architectures and scalable data streaming capabilities.
“When businesses embark on IT transformation journeys, they must plan for long-term data operational needs. Selecting the right tools from the outset ensures both the architecture and technology stack are aligned with business goals,” adds Dube.
Skills development
Data streaming engineers and DataOps specialists remain in short supply. To mitigate this, organisations must commit to training internal resources across senior and junior levels. “Upskilling teams ensures current tools are used effectively and creates a sustainable talent pipeline,” says Dube.
Competitive advantage through real-time insights
Real-time analytics delivers substantial advantages to organisations aiming to stay ahead in fast-paced environments. It shortens the feedback loop between frontline operations and back-end systems, which significantly improves the customer experience.
By anticipating user behaviour, businesses can proactively suggest next steps and streamline user interfaces to focus on features that customers use most. Tracking key performance indicators (KPIs) in real-time ensures constant visibility into business performance, enabling leaders to take immediate action when metrics deviate from expected outcomes.
Additionally, customer support becomes more responsive, with systems able to provide real-time (yes/no) guidance on relevant issues to assist users more effectively.
The role of DataOps in unlocking real-time value
DataOps enables agility across distributed data architectures, ensuring the full value of real-time analytics can be realised. The methodology fosters close collaboration between analysts and platform teams, promoting a feedback loop where data products are continuously refined.
DataOps supports a culture of experimentation and improvement. It brings platform and client-facing teams together, creating an efficient, responsive delivery ecosystem that evolves with business needs.
“Combining real-time analytics with a DataOps-driven approach positions businesses to unlock the full potential of their data. It is not just about speed, it’s about agility, reliability and staying competitive in a data-driven world,” concludes Dube.
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