Intelligent data pipeline implementation builds business capabilities

[ComputeExperts]

HPE offers new automated cloud-native data pipelines to help organizations keep up with the pace of data growth, get insights faster, and deliver business outcome effectively.

How do you set a course for business growth and resiliency in an ever-changing economic climate? What about shaping a data culture to streamline data, share data knowledge, and eliminate data silos? Then there’s managing dynamic demand and expectations of rapid growing analytics markets, users, and data volume.

To address these demands, it’s crucial for organizations to formulate a data-driven strategy where gaining insights from data is key to support. A rational starting point is to create and deploy data pipelines to consolidate data and analyze data to deliver that insight.

However, delivering an operational data pipeline is very challenging due to its complexity and the lack of expertise to make it right as shown in this Global Research Study:

Figure 1: The 2021 State of Data and What’s Next

How HPE helps the organizations overcome those challenges

HPE implements an end-to-end intelligent data pipeline framework that offers a data and analytics ecosystem (see Figure 2). Organizations can adopt the validated tools and technologies in the platform to rapidly establish the data pipeline, or they can choose their own tools and technologies to plug-and-play in the framework. The framework provides flexibility for the organizations to compose its business capabilities around its own environment, unique challenges, and business objectives.

Figure 2: High-level intelligent data pipeline architecture

The data pipeline is an AI-enabled, microservices-based solution with modular and flexible architecture from data ingestion, data processing, data analysis, data persistence, and data visualization to model creation, training, and deployment on big data. It enables organizations to manage data holistically, streamline data, and gain insights in real time while improving their organization’s resiliency and decision-making capability.

Our solution cookbook offers a proven, repeated recipe for successful data pipeline production deployment from day 1, while also giving a clear view and migration path to day 2 operations for future growth. It takes out the uncertainty, complexity, and manual work, greatly improving business efficiency and reliability.

Some key takeaways:

• Modularize data and analytics architecture design to compose your business capabilities and helps improve efficiency and reduce cost
• Automate data process and ensure data quality for meaningful data insights
• Bear in mind the entire ecosystem when selecting technologies or tools for data pipeline implementation

Finally, I’d like to stress that our clients don’t have to do it all alone. HPE has highly experienced resources to consult, support and hold hands to ensure the flawless data pipeline deployment the first time and every time in their data journey. All in all, as a trusted business partner, HPE empowers our clients to build their business capabilities where and how needed.

Contact us for more information and ask for a POC to operationalize business value through data pipeline implementation and help organizations to achieve business outcome.

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Meet Compute Experts blogger Jing Li, Workload Solutions PM for Mainstream Compute

Jing Li is the workload solutions PM for Mainstream Compute focused primarily on data management and big data analytics solution development.

Compute Experts
Hewlett Packard Enterprise

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