10 Things to Remember When Doing Data Integration

According to the 2020 Data Pipelines Market Study, 67% of businesses rely on data integration to support their analytics and BI platforms, and 65% prefer to deploy this solution from a hybrid cloud. These figures show the critical role of data integration, so companies have to consider some factors affecting its implementation. 

When dealing with data integration and choosing the most appropriate technologies for your business processes, you must consider the scalability and accessibility of your solution, regulatory compliance, data security, infrastructure location, user access, data types, business value, and more. 

The solution is not a new concept and has been around for decades. However, today's digital age has become more relevant than ever before because of the still-developing distributed systems on top of various platforms. Read further to know the things you need to consider in data integration. 

10 Things to Consider in Data Integration

Data integration refers to the process of combining data from separate sources into a single integrated dataset. It can be as simple as ingesting your company's Twitter feed and analyzing it for insights about customer sentiment or as complex as merging weather station readings with financial market information to make stock predictions. 

There are two types of it: upstream and downstream. Upstream data integration involves taking data from one system, transforming it to suit another system's needs, and then sending it back. Downstream data integration refers to importing new information into an existing database or application. 

In addition, it involves many technical challenges that must be considered when designing data ingestion processes and choosing the right technologies. Here are ten things to think carefully before embarking on a data integration project of any size or complexity: 

Scalability of Your Solution

Data integration strategy needs a scalable approach that can handle daily needs and future data loads. An effective way to execute it is to be aware of real-time events and have resource allocation automation based on integration activities. 

Infrastructure Location

Most solutions and applications are starting to move to the cloud. However, infrastructure on-premises has its strengths too. Take in all deployment options available, so your actions are not limited in the future. At the same time, you can make decisions based on a specific solution.

User Access and Data Types

Defining the specific data for integration will help you choose solutions that support your needs and future requirements. In addressing this, a data audit is necessary to discover data types that need replacement and have to be accounted for. Then, you need to identify who needs to access the data to maintain security. 

Data Security 

One of the costly concerns of enterprises is data breaches, but you can void it with the right strategy. The common vulnerabilities in organizations include internal malicious actors, attack opportunities during data transfer, social engineering, and phishing. Having a multi-layered and proactive approach can spare you from attacks and threats. 

Talent and Resources

Data integration implementation requires specialists and sufficient resources because you need support for its successful deployment across your company. You may also require in-house and outsourced staff to manage some critical parts of data integration.

Accessibility

The pandemic’s remote work setup has increased the need to create highly accessible data integration resources. Routine integration, ad hoc data requests, and other uses cases may occur with remote employees outside the business location. 

From the security required to the infrastructure, you have to consider support for remote access. Staff on this setup may upgrade their equipment to avoid accessibility pitfalls linked with slow internet speed, obsolete hardware, and unsecured networks. 

Adaptability and Compatibility

A data integration strategy becomes flexible if it uses a framework that can accommodate the latest technology without massive resources. With this, you can quickly bring in new solutions ahead of your competitors and reduce the workload needed for them to work with your data integration processes.

Standards Compliance

Evolving data regulations and falling out of compliance is costly because of data management and privacy. Having granular control on data integration may help you adapt to new regulations. Moreover, revisiting data governance policies may help in addressing issues unique to data integration. 

Interoperability and Ease of Use 

Your strategy in data integration should move you closer to a silo-free enterprise environment, supporting massive data transformation and movement. In this regard, consider the origin and destination of your data, your current storage options, the new types emerging, and the API you can still leverage. 

Business Value

Identifying key metrics and how they affect your organization positively will increase buy-in for your strategy. You can also highlight better visibility into your company’s data, greater productivity and efficiency, and possible bottom-line effects coming from data integration. 

Conclusion

Businesses need an efficient way to bring together all the different types and sources of relevant data into a shared repository to be analyzed and interpreted to generate new insights. Taking into account these ten factors in data integration may benefit your organization. 

Got a few questions about data integration? Message me, and we can talk more about it.