“Single View”. “360-Degree View”. “Data Hub”.


“Single View”. “360-Degree View”. “Data Hub”. A subset of “Master Data Management”. Call it what you will – and for the purposes of this paper, we will be calling it “single view” – organizations have long seen the value in aggregating data from multiple systems and channels into a single, holistic, real-time representation of a business entity or domain. That entity is often a customer. But the benefits of a single view in enhancing business visibility and operational intelligence go far beyond understanding customers. A single view can apply equally to other business contexts, such as products, supply chains, industrial machinery, cities, financial asset classes, and many more.

However, for many organizations, successfully delivering a single view has been elusive. Technology has  certainly been a limitation – for example, the rigid, tabular data model imposed by traditional relational databases inhibits the schema flexibility necessary to accommodate the diverse data sets contained in source systems. But limitations extend beyond just the technology to include the business processes needed to deliver and maintain a single view.

MongoDB has been used in many single view projects across enterprises of all sizes and industries.

Why Single View?

Today’s modern enterprise is data-driven. How quickly an organization can access and act upon information is a key competitive advantage. So how does a single view of data help? Most organizations have a complicated process for managing their data. It usually involves multiple data sources of variable structure, ingestion and transformation, loading into an operational database, and supporting the business applications that need the data. Often there are also analytics, BI, and reporting that require access to the data, potentially from a separate data warehouse or data lake. Additionally, all of these layers need to comply with security protocols, information governance standards, and other operational requirements.

Inevitably, information ends up stranded in silos. Often systems are built to handle the requirements of the moment, rather than carefully designed to integrate into the existing application estate, or a particular service requires additional attributes to support new functionality. Additionally, new data sources are accumulated due to business mergers and acquisitions. All of a sudden information on a business entity, such as a customer, is in a dozen different and disconnected places.

Single view is relevant to any industry and domain as it addresses the generic problem of managing disconnected and duplicate data. Specifically, a single view solution doesthe following:

  • Gathers and organizes data from multiple, disconnected sources;
  • Aggregates information into a standardized format and joint information model;
  • Provides holistic views for connected applications or services, across any digital channel;
  • Serves as a foundation for analytics – for example, customer cross-sell, upsell, and churn risk.

10 Step Methodology to Delivering a Single View

From scoping to development to operationalization, a successful single view project is founded on a structured approach to solution delivery. In this section of the whitepaper, we identify a repeatable, 10-step methodology and tool chain that can move an enterprise from its current state of siloed data into a real-time single view that improves business visibility.

The timescale for each step shown in Figure 3 is highly project-dependent, governed by such factors as:

  • The number of data sources to merge;
  • The number of consuming systems to modify;
  • The complexity of access patterns querying the single view.

MongoDB’s consulting engineers can assist in estimating project timescales based on the factors above.

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