Constructing a Modern Data Architecture

The desire to compete on analytics is driving the adoption of big data and cloud technologies that enable enterprises to inexpensively store and process large volumes of data. But, building a modern data architecture can be confusing and time-consuming.

From NoSQL and in-memory databases, to Hadoop and Spark, technologies are available that offer new and distinct capabilities to the world of enterprise data management.

The growing challenge of delivering information where and when it is needed requires a modern data architecture with governance, security, speed, and flexibility.

This topic was explored recently in a DBTA webinar featuring Danny Sandwell, senior product marketing manager at erwin, Inc.; Bruce Sandell, senior sales engineer, alliances, Looker; and Mark Van de Wiel, CTO at HVR, who talked about the key success factors for building modern data architecture.

Companies should invest in a modern data architecture because it recognizes data as a strategic asset, uses data to define and reshape their competitive advantage, encourages an analytic culture, empowers the business with insights at the point of action, makes insight-driven value a crucial business KPI, and protects and secures business data, according to Sandwell.

A modern enterprise data architecture should be aligned, integrated, agile, assured, understood, governed, and predictable.

The erwin data management platform can capture and document any data anywhere (Any2 ) for a detailed, visual architecture that drives quality, value and efficiency in data management initiatives. The platform can depict enterprise data in the context of business capability, processes and services, organizations, locations, systems and technology. It can also deliver an intuitive yet powerful enterprise model that enables data driven business transformation through the power of collaboration.

Sandell suggests a new way of thinking must take over the enterprise. This new way of seeing data architecture includes:

  • Single purpose data silos = Single Source of Truth
  • Doing more with less = Doing more with more
  • Confining your view = Expanding your world
  • Reactive reporting = Data Democratization
  • data ARCHITECTURE = DATA architecture

According to Van de Wiel, continuous data integration is important because there are more data silos containing more data types while businesses struggle with smaller batch windows and IT teams. HVR enables continuous data integration with its data lake platform.

An archived on-demand replay of this webinar is available here.