A modern data and analytics strategy is key to maximizing cloud investments

Over the last 30 years, organizations have wrestled with how best to organize, manage and analyze their data in a high-impact but cost-effective way. Cloud-native platforms and tools like Microsoft Azure Snowflake, Amazon Web Services (AWS), Google Cloud Platform and Snowflake Data Cloud make cumbersome and costly infrastructures obsolete. They free up funding and resources for organizations to pursue more aggressive, effective and more widespread use of business and advanced analytics.

The move to the cloud is happening faster than anyone predicted, driven in large part by the need to replace or modernize legacy technology assets that are reaching the end of their lifecycle. Access to the cloud and cloud services can help organizations speed time to delivery, increase flexibility and reduce total cost of ownership. Add to these advantages a never-ending stream of data sources and easier-to-implement technologies. You can see why leading companies are pursuing cloud-powered advanced analytics that help them understand customer behaviors, rapidly iterate products, hyper-personalize marketing and increase sales.

Better than a silver bullet: A modern data and analytics strategy

While it may be tempting to move to the cloud as fast as you can, realizing its full potential for your organization requires a modern and comprehensive data and analytics strategy. What do we mean by modern and comprehensive?

• It’s built on best-of-breed technology and industry standards.
• It provides organizations with a scalable framework to collect, process, transform, structure and deliver information.
• It creates an environment for analytics products to be developed, automated and propagated across an enterprise based on the organization’s business drivers.

In the face of rapid change, a strategic framework that is grounded in your organization’s stated analytics priorities will enable smarter, faster decision-making about how to invest in and assemble the necessary components and capabilities. Without the framework’s guardrails, organizations tend to revert to siloed processes, which ultimately leads to duplication of efforts, higher costs and mistrust of the data.

Build your strategy on these three pillars

Based on our experience working with large companies across different industries, NTT DATA has developed a reference architecture that enables and sustains a successful analytics journey and flexes to meet future needs. It’s built on three pillars.

• Data foundation
  Organizing your data into raw, curated and analytic layers enables your organization to blend disparate data sources and unlock the value of all your data. It’s also important to determine the proper ingestion, transformation and analytical integration patterns for the data your organization gathers and uses. Having a roadmap that lays out the needs for the next 18–36 months can help you determine the best way to organize the different elements into your ideal future state.
• Visualization and advanced analytics
  Properly designed data layers also reduce overhead for visualization developers and data scientists. They also provide accurate and synthesized data from various sources. Deployed on a strong data foundation, visualization tools help automate and distribute analytical products to the organization. They help business users understand complex data via easy-to-interpret visualized data points and become empowered decision-makers. Advanced analytics can deliver business understanding by uncovering and predicting the drivers of critical decision-making. Identifying how the organization is going to consume these insights is key to selecting the right visualization and analytics tools and maximizing their value.
• Operationalization
  To make sure your strategy delivers on its promise, it’s critical to establish a robust data governance program with a steering committee to set and enforce data standards and policies. Without effective data governance, your data and analytics strategy could be derailed by unresolved data quality issues that cause integration and accuracy issues in your analytics efforts. Performing data audits to track data usage patterns helps organizations manage the costs of cloud platforms — whether the platform uses a consumption-based or traditional subscription model.

Cloud-native platforms and tools have opened pathways for companies to organize and use data without the burden of on-premises infrastructure. It’s never been easier to deploy these platforms, but taking the time to implement a modern data and analytics strategy will help you make smarter, faster decisions about how to invest in and assemble the right components and capabilities. Think of this strategy as both a map and a set of guardrails for your path forward. Following it will help you meet today’s goals and flex to meet your future needs as well.

— By
David Mobley, Vice President, Data & Artificial Intelligence
Greg Stuhlman, Managing Director, Data & Artificial Intelligence
Shan-Ming Chiu, Senior Manager, Data & Artificial Intelligence