Build a Data Integration Strategy

Integrate your data or disintegrate your business.

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Not having a data integration strategy can have several drawbacks for businesses:

  • Data inconsistency
  • Inefficient data management
  • Limited analytics
  • Poor collaboration
  • Increased cost

Improving data integration can provide several benefits to businesses:

  • Better data quality
  • Increased efficiency
  • Improved analytics
  • Enhance collaboration
  • Competitive advantage

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Onsite Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn’t enough, we offer low-cost onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.

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Module 1: Collect Data Integration Requirements

The Purpose

The purpose of collecting data integration requirements is to ensure that the data integration strategy aligns with the business needs and priorities. It involves identifying specific business processes and data sources required for integration, enabling businesses to make informed decisions based on accurate and consistent data.

Key Benefits Achieved

The key benefits of collecting data integration requirements include improved data quality and more efficient processes. This leads to better decision-making, increased efficiency, improved analytics, enhanced collaboration, competitive advantage, improved customer experience, and cost savings for businesses.

Activities: Outputs:
1.1 Identify integration pains and needs.
  • Learn about the concepts of data integration and the common integration patterns and use cases.
1.2 Collect business requirements for the integration solutions.
  • Understand what drives the business to need improved data flow and how to collect integration requirements.

Module 2: Analyze Integration Requirements

The Purpose

The purpose of analyzing integration requirements is to determine the best approach to integrating data sources to meet business needs. It involves identifying potential data integration challenges and developing a plan to address them, ensuring a smooth integration process.

Key Benefits Achieved

The key benefits of analyzing integration requirements include the ability to identify potential challenges and address them proactively, leading to a smoother integration process. This results in a more efficient and effective data integration strategy that aligns with business needs and priorities.

Activities: Outputs:
2.1 Determine technical requirements for the integration solution.
  • Capture the functional and non-functional requirements for the integration solution.
2.2 Leverage integration trends to address requirements.
  • Learn about and understand the differences between trends in data integration, as well as how they can benefit your organization.
2.3 Architect the data-centric integration strategy.
  • Determine selection criteria for most appropriate integration patterns.
2.4 Calculate ROI to attach dollar value.

Module 3: Design Data-Centric Integration Solution

The Purpose

The purpose of designing a data-centric integration solution is to create a framework for integrating data from multiple sources and making it available for use across the organization. It involves identifying the most appropriate integration technologies and tools to meet the specific business needs and requirements.

Key Benefits Achieved

The key benefits of designing a data-centric integration solution include improved data quality and consistency, increased efficiency and productivity, and enhanced collaboration and decision-making. It enables businesses to have a more comprehensive and accurate view of their data, leading to better insights and more informed decisions.

Activities: Outputs:
3.1 Validate your data-centric integration pattern.
  • Evaluate if PoC is needed to validate new patterns.
3.2 Design the consolidated data model.
  • Learn about the source to target mapping tool and how to create your own processes.
3.3 Map source to target model.
  • Learn about integration metadata and what metadata to capture.
3.4 Capture integration metadata.
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