What is Data Integration and Why Does it Matter? 

Data integration involves combining data from different sources into a cohesive, unified whole, and it is vital to keeping your business running efficiently without data silos. Most organizations’ processes depend on accurate, up-to-date data, including daily operations, reporting, analysis, and decision-making.

However, many businesses struggle with integration, with 84% of insurers reporting that integration/adequacy was a common challenge faced in the non-life run-off market. Related issues, like data cleansing and operating model integration/transformation, were not far behind. 

Data integration was once time-consuming, and many companies still rely on manually integrated data to keep all records up to date. However, automation is leading the charge for businesses preparing for a more efficient, connected future. In fact, automation for data integration is transforming the way organizations collect and use their data, eliminating both inefficiency and the potential for human error. 

Integrating and Analyzing Data

Data is the foundation of all business decisions. Every company collects data, but making the most of your information requires integration and analysis. Data integration can be a complex process, but with the right tools and approach, it can be a powerful tool for any business. 

Without proper integration, data quality issues can make accurate analysis impossible. Duplicate, missing, and incorrect data hinder a company’s ability to deliver accurate results. Data analysis is not the only area in which integration matters. Overcoming challenges like data quality issues, data silos, and IT infrastructure issues rely on accurate information. 

While the need for accurate data is universal, many companies fail to appreciate the need for optimized data integration tools. Sticking with “tried-and-true” legacy systems may seem cheaper and more familiar, but these systems cost far more in the long run due to their inefficiencies. Likewise, the potential for errors and unreliable data is far greater with manual processes than with correctly optimized automated tools. 

Tools for Data Integration

Integration can be a complex process, but with the right tools and approach, it can be a powerful tool for businesses. There are many tools available for organizations looking to upgrade their data management. However, the right tool depends on the specific needs of the business. 

Data management tools come in many forms, with both premade and fully customized systems available for any use case. Many data programs are cloud-based rather than being hosted on a local drive or server. Decentralization of data allows it to be collected from sources hosted anywhere. Cloud-based data integration is a popular choice for businesses that frequently collect data from multiple sources in different locations, and cloud-based data platforms offer several advantages, including scalability, flexibility, and cost savings. 

ETL Tools

ETL (extract, transform, load) is a common integration method. These tools are used to extract data from multiple sources, convert it into a format that can be loaded into a target system, and then load it into the target system. Data transformation includes cleansing, filtering, and aggregating data. 

ELT Tools

ELT (extract, load, transform) perform the same basic steps as ETL platforms. However, rather than reformatting before loading into the platform, they transform data after uploading. 

Data Virtualization Platforms

Data virtualization platforms are becoming increasingly popular due to their flexibility and scalability. These platforms provide an abstraction layer between data sources and data consumers. As a result, data virtualization platforms make it possible to access and combine data from multiple disparate data sources without replicating or moving the data. 

Data Lakes 

Data lakes are a type of data repository that store data in its native format. These repositories can be used for data warehousing, data mining, and analytics and provide businesses with a single location to store all their data. 

Data Marts

Data marts are similar to data lakes, but data marts are specialized to support specific business needs. These types of data lakes contain only the subset of data relevant to the business need and are typically used for reporting and analysis. 

Data Integration with Populus

Whichever tools your business chooses, finding the right data management strategy means finding the right integration partner. While many companies rely on outdated systems for managing their data, these systems are often inefficient and inaccurate. Taking the step to automated integration can transform an organization, saving time and money and avoiding costly errors from incomplete data. 

When done correctly, data integration can provide businesses with a 360-degree view of their customers, operations, and performance. As a result, data integration can help enterprises to improve customer service, optimize marketing campaigns, and make better decisions. Data integration is essential to business intelligence and should not be overlooked.

Populus offers various services, from integration and analytics to fully customized applications to manage your business processes. If you’re interested in implementing automated data integration for your business, Populus can help. 

Populus Technology is experienced in providing technology solutions to our partners. We help support their growth by managing partnerships and directing our clients to the best third-party vendors in the industry. We also assist organizations in updating and automating their business processes, even creating custom software solutions for unique workflows.
If you need help transforming your organization’s data processes, Populus has the solutions you need. Contact our team to learn more!

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