Data is the lifeblood of every successful business — but you can’t get the quality analytics and business value your company needs without a solid foundation for healthy data. Contrary to common practice, it’s not enough to collect and connect data through a data warehouse or data lake. The data management lifecycle does not stop at improving data access for analytics.
A complete digital transformation goes far beyond simple data integration and data storage, delivering real-time data-driven insights to every part of the business and informing every decision you make. Many organizations are turning to 360° customer data hubs to keep the value of their data flowing, so it can reach its full potential.
What is a data hub?
A data hub is a data exchange with frictionless data flow at its core. What does that mean? Picture a bike wheel with hubs radiating out from a central hub to dozens of points along the rim. Those endpoints — which can be applications, processes, people, or algorithms — interact with the hub to contribute data to the hub or receive data from it. All this happens continuously, potentially even in real-time. When data enters the data hub, it gets connected to other data points and reconciled into a 360° view. This unified hub helps to break down data silos, giving the entire organization a single, shared source of truth for all relevant data.
The enterprise data hub also provides a single point of access and reference for sensitive data. Knowing that there is a single location to access personal identifiable information (PII) dramatically simplifies governance for the data. By correctly provisioning access to the data hub — and exposing sensitive or masked data only to those users or applications who require that access — you can improve data security, provide oversight into data sharing, and expand visibility into how the data is flowing throughout the business. Ultimately, trustworthy data can be consumed and reused in an easy and consistent way by anyone or any application that can benefit. This is how customer data becomes a true asset for your business.
How data hubs promote trusted data
A customer 360 data hub provides a set of rules for data sharing, mediation, and governance that provides a number of benefits for organizations, allowing them to do the following:
- Expand and speed up the sharing of information between their own on-premises, cloud, and hybrid cloud applications, employees, and external customers and partners
- Create a trusted, continuously evolving “golden record” of their customers, vendors, and partners
- Drive business outcomes with data across operations, resulting in improved customer experiences, streamlined operations, and superior risk management or mitigation
Tangible data hub benefits
Customer 360 data hubs connect data providers and data consumers, while allowing data controllers to orchestrate data flows in a governed way. The result, as we mentioned above, is trusted data for the entire organization. Once you can provide actionable, trustworthy data and overcome the challenge of delivering trusted data in real-time, you can reap the business benefits that a customer 360 data hub can offer:
- Sales can grow through personalized offers and recommendations
- Marketing can develop tailored communications that deliver a high-impact customer experience
- Products can get smarter and adapt to their usage context
- Compliance can be controlled in a holistic way
- Employees can constantly learn and boost efficiency with smart guidance
Data hub vs. data lake
Most data architectures are designed to operate as centralized data stores. This design pattern has proven success in data analytics, for delivering structured analytics to the various users who rely on it (the data warehouses) or to discover hidden insights within big data and continuously learn from it (the data lakes). But when the goal is data exchange — that is, building smarter data flows rather than simply storing the data so that it can be available on request — a 360° customer data hub should be at the core of the architecture. This is because the data hub is more agile and flexible than legacy architectures.
A data hub is designed for the rapid exchange of information needed by today’s organizations. It captures any data — including metadata, master data, operational data, and analytical data — and reconciles it. Then it delivers the data in multiple desired formats without necessarily storing it physically in a central place. Using search-based applications and API services, data consumers can easily discover and get instant access to data they can trust. A data hub also establishes a single point of trust for data flows, with end-to-end visibility and lineage
6 steps to build a customer 360 Data Hub
Any data hub must be designed and customized to fit the needs of a specific organization. There are some common principles of data management and architecture, however, that all successful data hubs share. Our six-step approach combines the most common disciplines of data modeling, data integration, application integration, and data governance:
- The first step is to connect the data sources and data services that need to be shared with the data hub. At this stage, depending on an organization’s needs, the data in its raw format could be stored in the hub, or it could simply pass through the hub.
- The incoming data flows are then put into a canonical data model so that they can easily be connected. This ensures that data can be easily identified and used.
- The data sets then get inventoried in a data catalog and organized for tasks like data categorization, curation, protection, and remediation. The data catalog should include tools for search and discovery, helping to manage data pipelines and accelerate the ETL processes.
- Data quality techniques, such as matching, survivorship, and deduplication can be applied either in-flight as the data is integrated into the data hub, or after the data has been integrated to create a golden record. The golden record is stored in the data hub using the data store that best meets the context.
- Analytics are deployed to augment the data for segmentation, forecasting, predictive behavior, recommendations, etc. This can initially be done manually by data stewards or, over time, can be automated by machine learning algorithms trained on the manual data steward inputs.
- Finally, the data can be shared with data consumers, including applications, systems, business users, data professionals, and third parties.
Use cases for your customer 360 data hub
Armed with data-driven customer insights that the entire organization can trust and act upon, any business will be well positioned to get real value from their customer 360 initiatives. Businesses that prioritize data health will quickly see quantifiable returns on their investment in customer data:
- Improvement in cost of acquisition (CAC): With more targeted engagement based on deep customer insights, marketing and sales will see increased pipeline and reduced CAC.
- Increase in sales velocity: Shrinking the time it takes to convert a lead to a sale translates directly to annual revenue.
- Improvement in retention, upsell, and cross-sell: More relevant and timely customer communications have an outsized impact on the value of that customer over time.
- Product innovation: Data-driven product innovation can help drive improved market share, customer satisfaction, pricing leverage, and more.
- Opportunity cost of time to market: By putting trusted data in the hands of decision-makers, you give them the power to make faster and better business decisions.
- Risk mitigation: Technology that supports data health lets you control how customer data is captured, stored, and accessed, all while maintaining compliance with security and privacy regulations.
The foundation for a successful customer 360 data hub implementation
Talend Data Fabric provides all the tools you need to simplify the process of building a comprehensive customer data hub. This unified platform offers data ingestion, integration, governance, and sharing, and Talend Data Fabric helps organizations collect, govern, transform, and share any data pipeline as part of a data hub:
- Collect: 1,000+ built-in components and connectors make it easy to capture, standardize, and clean datasets from a diverse range of sources
- Govern: Data governance features facilitate data ownership, data certification, data stewardship, and data remediation
- Transform: Talend Data Fabric can create a golden record for reconciling and cross-referencing your data using data quality, matching, and survivorship
- Share: Because they have been automatically documented in a data catalog, datasets can be easily discovered and consumed by anyone — from data engineers to business users and application developers
Get started with the industry-leading cloud integration solution today: Try Talend Data Fabric