The ultimate guide to successful Enterprise Data Integration

Enterprise data integration is the consolidation of data sets from various sources and formats into a single, coherent data store that is available for the corporation.

Enterprise data itself is the data shared across an organization, either across departments or regions. Often, data exists in silos across an enterprise, scattered over ERP and CRM platforms, in databases, legacy systems, in message queues, or flat files. The volume and variety of this data are huge, and the content, quality, and structure of these data vary enormously. However, the democratization of this data exponentially increases data value by aligning, combining, and visualizing data from both external and internal sources.

In contrast, fragmented data poses a substantial risk. If a business cannot rely on enterprise data, they will lack the intelligence they need to operate, compete and grow. Without a consistent, singular view of data, it is exceptionally challenging to develop an organization-wide consensus. In essence, until an enterprise data integration plan is in place, businesses cannot get a positive return on data – which is a company’s most important strategic asset. In this article, we discuss the importance of and approaches to successful data integration.

Why integrated data is important

In order to put enterprise data to work, businesses need to unify their data assets. This will ensure that business decisions are based on trustworthy, timely, and holistic information. Enterprise data integration enables companies to access all of their data to generate an accurate and consistent view of their intelligence assets. From here, they can leverage this information to drive evidence-based business decisions and operations.

Data integration is particularly important in the case of mergers or acquisitions, as it provides a unified view of data assets. As data loss can lead to financial loss, businesses must spend time and resources on thorough and efficient data solutions and storage.

Furthermore, to overcome data architecture obstacles, drive customer acquisition, and streamline operations, enterprises need to leverage data integration solutions. This will enable them to manage and replicate data in real-time, ensuring information is timely and relevant.

As such, IT departments across all major enterprises are leveraging data integration to drive value. Through real-time reporting and analysis, businesses are optimizing minute-to-minute operational and strategic decisions. With these techniques, companies are gaining detailed customer insights, which lead to a meaningful competitive advantage.

Approaches to enterprise data integration

Today, many businesses are adopting a comprehensive, enterprise-wide approach to data integration. These organizations are implementing enterprise data integration technology that works across a spectrum of initiatives. For instance, there are single applications that can migrate, consolidate, synchronize, warehouse, and analyze data. 

By leveraging a unified platform, businesses can rationalize IT infrastructure, which reduces costs and increases agility. Furthermore, this approach helps to ensure compliance with a stricter regulatory landscape. With a more consistent approach to data governance, businesses can ensure they provide reliable evidence to legislators.

However, there is more than one approach to enterprise data integration. A popular method is to build a centralized data warehouse that services various points within the network. Nonetheless, the most important thing to remember is that the most useful data integration initiatives take a holistic view, considering not only the technology but architecture and organizational approaches. Below are the core things to keep in mind when developing a strategy:

1. Centralization. Large organizations are complex networks of varying data sources. If this intelligence is fed into different data lakes, efficiency is compromised. Therefore, establishing a centralized, logical overview allows users to configure better, monitor, and manage data.
2. Integration Competency Centers. Integration Competency Centers (ICC) have emerged as a best practice for enterprise data integration. ICCs are designed to increase agility and reduce costs by establishing conventional processes and standards. ICCs facilitate cross-enterprise collaboration and coordination for global IT teams, incorporating both internal and external resources.

• However, while many companies are migrating to an organization-wide approach to data integration, this process must be rolled out incrementally. Instead of generating a shock to the system, management should focus on delivering urgent tasks now, while laying the foundation for a long-term data integration strategy.

Enterprise data integration platforms

To support multiple projects with consistency and efficiency, businesses need a unified enterprise data integration platform. This system should interoperate with dynamic IT environments to ensure robust data governance and generate maximum value. This system should comprise the following features:

1. Broad access to all enterprise data, irrespective of format, structure, or source.
2. An open, platform-neutral architecture designed for scaling and developing IT environments.
3. A unified architecture that simplifies and accelerates maintenance.
4. Enterprise-standard data security, reliability, and availability
5. A shared services approach based on transparency and flexibility standards.

For instance, many technology-driven companies are adopting service-oriented architecture (SOA). Data integration is a crucial aspect of these initiatives, which enhances business agility through the organization and reusing of data assets, applications, and processes. Through these standardized systems, employees can easily access relevant and timely information, from anywhere, in any form, at any time, with consistency and accuracy. Therefore, to support SOA, businesses need a data integration platform that operates seamlessly with existing IT infrastructure.

Meet modern challenges with cutting-edge technology

Soon, data mobility and real-time integration will be critical to the success of modern enterprises and corporate IT departments. Enterprise data integration empowers an organization to access all its fragmented data, creating a consistent view of core data assets. Traditional data integration tools, such as ETL, are rapidly becoming outmoded. Their structures do not address contemporary challenges as they require manual scripting. Furthermore, they tend to struggle with unwieldy data sets and cannot manage the volume or velocity of big data.

In order to stay competitive, businesses need to move beyond legacy data integration techniques and implement cutting-edge data integration technology. These systems eliminate the weaknesses of traditional data management systems, enabling enterprises to execute efficient and profitable projects. With an enterprise data integration policy that centered on best practice and advanced technologies, business leaders can nurture the evolution of an agile, data-driven enterprise.