Unlocking quality insights from your hybrid cloud

Product Marketing Manager, IBM

The quality of analytics output or insights depends on the quality of the different data sources that feed into the information supply chain. An organization must manage and control its information supply chain for quality, then integrate and analyze it to make business decisions. This is no different from how things are in a manufacturing setup, wherein the scope of quality control is not limited to the final assembly line. Instead, it spans the supply chain to ensure that the raw materials, components and parts that go into the final product are free of defects.

Unlike a traditional supply chain, an information supply chain has a many-to-many relationship. For example, data about the same person can come from many places. That person may be a customer, an employee and also a partner. Moreover, such information can end up in many reports and applications, and various systems may define the same information in different ways. Moreover, when organizations adopt a hybrid cloud environment, they add another layer of complexity to their information supply chains. Despite the added complexity, organizations still need to ensure the completeness, accuracy and availability of information to promote high-quality insights. To achieve these data attributes in a hybrid environment, organizations must do the following. data

For a hybrid environment, organizations must implement a comprehensive information integration and governance solution that can

  1. Connect to relevant applications and data sources, recognizing and responding to data changes in those sources, whether structured or unstructured, mainframe or distributed, internal or external.
  2. Standardize, merge and correct information to provide authoritative, consistent and complete views of business information and its relationships across the extended enterprise.
  3. Discover, model and govern information structure and content.

Maintain data

Trusted data must be maintained after preparation. One approach to consider is a master data management (MDM) system. Historically, such systems have focused on internal, structured data. Though doing so is highly useful, the hybrid data environment demands that the old view of MDM be broadened to include external, cloud-based data sources.

Monitor data

After investing the time and resources to prepare and maintain data in a hybrid environment, ongoing monitoring is essential to help ensure that data remain trustworthy over time.

Cloud-based data and processing services present too much opportunity for businesses to ignore. Charting a data quality and governance strategy to ensure the completeness, accuracy and availability of information used for analytics is essential to maximizing the benefits from an organization’s cloud and analytics investments.

The complimentary eBook Data quality and master data management in a hybrid environment discusses in detail the capabilities required to prepare, maintain and monitor data in a hybrid environment. Download and read it today.

Read further on this topic in the eBook The truth about information governance and the cloud, and the blog post “Confidently cull information from cloud-based data.