Most common types of data integration methods

By Henning Lund - July 08, 2022

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According to Inc.com, up to 73 percent of company data goes unused. How do you make sure that your organization is using the data you collect? 

Often, companies gather data from diverse sources. Moving data from one source to the other in order to get a unified view of the information can be difficult. As a result, many end up having disconnected systems and silos of data. 

Data integration could be the answer to that challenge. This article will investigate the different data integration methods to help you choose the right solution.

So many types of data integration approaches... choose the best way for your organization

Data integration is the process of combining data from many different data sources, typically for analysis, business intelligence, reporting, or loading into an application. Data integration is highly relevant to most organizations of medium to large size because they typically use a wide array of applications to gain efficiency and serve their customers better. 

Most of the time, these applications all have their own databases and data stores. These applications could be on-premise or in the cloud. Regardless, they are only truly useful if they share data between them so data application is a must. 

In order to make qualified business decisions, organizations need to have one unified view of their customer data. Developing processes for consolidating data from multiple applications and creating a unified view of data assets, this is what data integration is all about.

Benefits of data integration

Most organizations are using tons of applications, systems, and data warehouses. They may wish to connect to the systems of their business partners, for example manufacturers, suppliers, logistics companies, customers, etc. 

These data sources are most of the time disparate and siloed, making it close to impossible to make better sense of all the available information. It is vital to connect the data from disparate sources with each other to optimize the value of the gathered insights. 

Only when this information is available in a single place in real-time for all the right stakeholders, will you be able to streamline processes and improve customer service.

The benefits of an integration between an organization’s ERP and CRM systems are plentiful. Sales People put a significant effort into making every prospect or customer satisfied. They want to know all about their needs and requirements.

Turning the vendor-customer relationship into a partnership is probably the most efficient sales approach. However, it can be challenging to give salespeople a true 360-degree view of their clients. 

A CRM system alone can take you a long way in getting to know your customers better. But if you want to go all the way and have a true 360-degree view of your customers, you must integrate your CRM with your ERP. From an operational point of view, you can achieve much greater benefits by integrating the two systems.

  • Integrating ERP and CRM is the only way to get a true 360-degree view of your customers. From prospect, to sales and support, to finance and accounting, together these systems provide complete visibility into your customers’ needs, buying habits, order history, preferences, account standing, etc. you get better insight into your customer base, and you can use it to build lasting relationships with customers and determine where there is potential for future growth.

  • You gain tremendously in efficiency because you have instant access to important information. Always having access to business-critical information in real-time (whichever system you are working in) means that you are able to quickly and accurately respond to your customers’ and other stakeholders’ questions and requests (for example about inventory levels, shipments, customer financials, order history, returns, payments, pricing, etc.) without having to search for answers in multiple systems. You avoid wasting your time finding information and you improve customer experience.

  • You get rid of manual routines that are time-consuming and prone to human error. You eliminate redundant data entry and have a chance to streamline processes and automate workflows, enabling you to increase response time to your customers.

 

What are the different types of data integration methods?

It would not take long to convince any C-level executive about the benefits of integrating these applications. Deciding how to perform the integration can be a more difficult decision to make. This requires a good understanding of what data integration methods and approaches are and which fit one’s organization best. 

There are many types of data integration. The data integration jargon can be overwhelming. One can easily get lost in readings about data migration, data streaming, data models, data virtualization or data federation. It is important to keep it simple. The most common ones can be grouped in five categories.

the most common types of data integration approaches according to RapidiOnline

 

1. Uniform Data Access

With Uniform Data Access, you can access enterprise data from very disparate sets and present it uniformly. Uniform Data Access does this while allowing the data to stay in its original location. 

It leaves the data in the source system and defines a set that can provide a unified view to various customers across a platform. There is zero latency from the source system to the consolidated view. 

If you use this data integration method, a separate store is not required for the consolidated data.

Uniform data access has limitations. You can only use this integration approach on similar data sources (same type of database). Also, data management only allows you to have limited information about the data's history and version management.

2. Common Data Storage

Common Data Storage (or CDS) is a storage space that enables you to manage and securely store data used by multiple applications or programs. What common data storage tends to do is copy the data from the source systems to a new system. 

Also known as Data Warehouse, this technique helps collecting data from various sources, combining them to a central space and management (Database files, mainframes, and flat files).

As opposed to uniform data access, CDS includes data version management and allows you to combine data from very different sources (mainframes, databases, flat files, etc.)

3. Application Based Integration

Application Based Integration solutions are specialized programs that locate, retrieve and integrate your data. Using these, you can transform and integrate data so that information from different sources is made compatible. 

Application Based Integration accesses various data sources and returns integrated results to the user. This method becomes increasingly complex as the number of system interfaces and data formats to homogenize and integrate grows. 

It has limitations if you are handling large volumes of data and large numbers of sources because it requires the applications to implement all the integration efforts. Therefore, this technique is mostly suited to integrate a very limited number of applications and for more limited amounts of data from a limited number of sources and applications.

4. Common User Interface

Common User Interface means manually locating the information in each data source and comparing or cross-referencing them yourself in order to get the insight you need. Therefore, it is often called “manual integration”. 

In manual integration, all the relevant information to access from the source system or web page interface is operated by the users. This means that users must deal with different user interfaces and query languages and therefore need to have detailed knowledge on location, logical data representation, and data semantics.

The Common User Interface approach gives no unified view of the data. This method has obvious scaling limitations and it can only be used with a minimal number of sources and a small volume of data.

5. Middleware Data Integration

Middleware is a layer of software that creates a common platform for all interactions internal and external to the organization—system-to-system, system-to-database, human-to-system, web-based, and mobile-device-based interactions. Middleware integration refers to applications that connect two or more applications.

Middleware integration tools are great to connect critical internal and external systems. Middleware technology has helped many companies rationalize legacy IT systems into reusable, general-purpose functionality blocks that facilitate quicker changes to business processes.

Many middleware services are accessed through APIs. APIs are sets of tools, definitions, and protocols that allow applications to communicate with each other. APIs make it possible to connect completely different products and services through a common layer.

 

Which form of data integration should you select?

Data integration methods give you a way to store, analyze, transfer and view your data in a unified way. In order to decide which method suits your organization best, and which data integration tool could be interesting for you, you need to fully understand your business and its processes. 

You need to have a good understanding of the applications that your organization is using, as well as the reason why you are using them. Your needs might be simple and require a simple data migration tool. They could also be very complex, and you might have to invest in a complex data integration platform. 

Retrieving data from various sources can always be a challenging task. Whichever data integration method you choose, to make it simpler, you need to ensure each application contains high data quality.

Data integration is not a simple task – but it does not need to be complex. Designing a good structure and architecture to store your data can be a tremendous task, especially in the age of big data, business intelligence and AI. 

The amount of data collected in organizations can be quite overwhelming. According to CIO.com, enterprises on average can use up to 1000 cloud apps. Generally, it is often a good idea to seek help and advice from professionals.

 

Data integration method example between CRM and ERP

Your organization might not be one that uses 1000 applications, and your application integration needs could be a lot simpler. It does not mean that you have less need for data integration. A very common data integration scenario is that of a CRM-ERP integration. 

Most large companies in the world have invested in both an ERP system and a CRM system – some simultaneously, some step wise. While there is no doubt to the benefits of each system separately, integrating them is what can make the biggest difference to a company’s operations. Combined however, these two systems can help companies take an exponential leap.

RapidiOnline uses the best data integration method to reap the benefits of ERP-CRM integration

Nowadays, there are even very cost-effective cloud-based solutions that allow fast, automated and secure data integration. Integration solutions can run as a service, and implementation time is in most cases limited to 3 to 10 man-days. 

This makes it both possible and affordable to move forward with an integration, simply. This is the case of RapidiOnline, a data integration tool that easily integrates Salesforce CRM application with any of the Microsoft Dynamics ERP solutions using pre-configured transfers/templates.

 

What type of data integration approach does RapidiOnline use?

RapidiOnline was developed to make data integration projects as simple and robust as possible. It is an innovative cloud integration system that comes out of the box with pre-configured, adaptable business processes and templates that support the most common CRM-ERP integration points

RapidiOnline allows you to quickly integrate Salesforce and Microsoft Dynamics ERP. It has been designed to enable direct integration, so your data will never get stuck in-between your two systems. Installation is easy with the programming-free RapidiOnline platform. No programming is required even if you want to extend your Salesforce or Microsoft Dynamics with add-on solutions or customizations.

The underlying technologies in RapidiOnline contain specific features to optimize integration with Salesforce and Microsoft Dynamics ERP. As a result, you don’t even have to go through an extensive testing process. You just need to make sure you have good data quality. 

RapidiOnline runs via the RapidiConnector, a unique technology that ensures data communication between RapidiOnline and your on-site systems is not compromised. The RapidiConnector is a unique technology that ensures data communication between RapidiOnline and your on-site systems is secure. It resides in your network and automatically compresses, and SSL encrypts data before transferring, making it practically impossible to decipher.

RapidiOnline is an innovative software product that is three-fold in its simplicity; in design, on-boarding and use. It is fast, yet flexible, secure and robust.

Secure data integration approach with RapidiOnline and the Rapidi Connector

Learn more

Follow us on LinkedIn to learn more about Rapidi and RapidiOnline, or download this e-book for additional information about the RapidiOnline data integration solutions. 

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About the author

Henning Lund

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With over 25 years’ experience in strategically propelling businesses forward, Henning is considered a business development entrepreneur with a passion for transforming businesses, sales and marketing operations through out-of-the-box thinking, concepts building and process automation to improve overall performance and scalability.
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