From sharing account log-in information with family members to integrating systems in a company, moving data from one place to the next is a complex task.
Data in the workplace often doesn’t flow effortlessly between different systems or across different departments. Because of this, different parts of the same company may experience frustration and confusion when sharing or using information. The process of getting these systems to “talk to one another” in a pinch can be costly and time-consuming, which is why a foundation for seamless system integration is one of the best things you can do for your business. Read on for insight into achieving seamless data integration.
System integration is necessary when information from one context needs to be transferred and used in another context. Multiple systems are required for many organizations to operate well, and the more complex system integrations are, the higher the cost will be to your company.
Most companies recognize that as the marginal cost of compute moves to zero, the effective digitization of workflows will yield market winners. As Marc Andreessen, the progenitor of the modern browser, explains in his article “Why Software is Eating the World,” this mega-trend started developing back in 2011.
A lot has changed since 2011, and manual processes such as spreadsheets have been fully replaced by the cloud ecosystem. Now the growing data and analytics space includes major players like Snowflake, Microsoft Azure, AWS, DataBricks, and Google Cloud.
According to Gartner, 89% of board directors say digital business is now embedded in all business growth strategies. Still, a mere 35% of board directors report that they have achieved or are on track to achieving digital transformation goals. This means that while complex systems and data are used daily in business, the management of this data puts an expensive, clunky strain on business owners.
The good news is that infrastructure constantly evolves in the cloud, which means mistakes can be contained and remediated rather quickly. Instead of brushing over this information integration challenge and getting more and more overwhelmed, it’s time to approach it head-on and create proper integrations.
It can be overwhelming to know where to begin with system integration. Let’s narrow down your information architecture choices a bit by walking through the four main types of system integration.
This is a high-level type of integration made to accommodate and connect different types of software used by large enterprises, such as POS, CRM, and HR systems.
This type of integration occurs when systems from across the company that are used at the same stage in the business’s order of operations are made compatible with one another.
Vertical integration is used to make systems compatible that are located in the same location within a company but are needed at different steps in the business process.
Point-to-point integration uses an API to take away all barriers between two systems, so they can directly communicate.
Two main types of data are valuable to an organization:
It is largely transactional and event-based data, produced by internal business processes such as purchase orders in the ERP, accounting data from the financial systems, and events in the CRM. Integrating operational data requires maintaining consistent data points in multiple systems or triggering downstream workflows in a coordinated way.
Bringing data into the analytical plane and integrating data from different sources helps organizations extract insights and model data for applied use cases like predictive analysis.
Activities supported by operational data may include scheduling services or ordering products and shipping materials. For example, integrated operational data allows e-commerce orders to make it to the ERP system for fulfillment, where tracking numbers can be accessed by the customer through Amazon.
These operational systems are important for customers and your company’s back-end data, but this data can be difficult to work with if it doesn’t integrate well between systems.
CRM systems don’t care about bank account numbers, and financial systems don’t care about how many candidates the HR team might be recruiting. The more disparate these systems become, the more important seamless system integration is, because while these systems “don’t care” about one another, there is a good chance that they will eventually need to be used in conversation with one another. When that day comes, your organization needs to be prepared with proper integration.
Finding the right tools for operational data integration depends on your data architecture, cloud footprint, and application landscape.
Here are some technologies & patterns to consider:
Analytical data provides an understanding of operational processes. Generally represented and accessed in schemas, models, and views using database technology, it requires high-quality data applied in the correct context to accurately represent the state of any business.
Analytical data helps companies “map the terrain” of their business with up-to-date analytical frameworks.
Effective analytical integration tools implemented at Kenway are:
Kenway offers a flexible and tailored approach to system and data integration by guiding clients with a data strategy that aligns with corporate objectives and drives long-term value. Based on our experience with a wide array of system integration projects, we keep the following in mind when handling data in the analytical plane:
If you’re looking for data integration solutions for your organization, connect with us to discover how to complement your business objectives and maximize return on investment while minimizing operational overhead.
