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The 5 Most Common Problems of Data Integration

Five Most Common Problems of Data Integration You Need to Know

Business leaders and CIOs face a number of challenges related to data integration, stemming partly from growth in the value and disparity of data coming into corporate systems. These challenges include keeping up with growing data volumes, streaming data sources, using legacy data integration approaches, and more. 

In this blog post, we’ll examine these challenges and how modern data integration platforms can help companies overcome them.

1. Keeping up with data volumes

As per Mitch Gibbs, a cloud consultant at Atlanta-based Candid Partners, the biggest data integration challenge is the exponential growth of data from multiple sources. This triggers problems with the available capacity for data retention, and, more importantly, efforts to gain insights from all the data being collected and integrated. 

According to Gibbs, companies need to adopt a strategy to manage and integrate emerging data volumes, which must in turn be balanced with the cost of storing all that data.

The use of modern data integration solutions with AI and large file data ingestion capabilities helps companies handle large volumes of data with ease and precision. These next-generation solutions enable non-technical business users to integrate and use highly complex, voluminous data streams much more quickly, easily, and securely. 

2. Multiple streaming data sources 

Many companies find it difficult to consolidate data from multiple sources. For example, according to Farnaz Amin, principal digital product manager for GE Digital’s grid analytics platform, consolidation is a major issue in the power industry, where utilities have to ingest data from different systems to create a unified, seamless data flow.

Consequently, a utility may have services offered by multiple vendors that function as silos and have little or no integration between them. Along with tackling integration, that utility needs to ensure that all the data is integrated and stored safely to address risks associated with security, reliability, and financial fines from regulatory authorities, Amin said.

Companies must spend time evaluating the types of data they’re capturing and how those different data sets need to be integrated. Another point to consider is how to make the data integration process simpler and faster. 

Self-service-powered data integration platforms enable non-techie business users to implement data connections. Users can rely on pre-built application connectors, shared templates, dashboards, intuitive screens, and end-to-end encrypted environments to create data connections much more securely, easily, and quickly. 

3. Legacy data integration approaches

When legacy data integration solutions are used, all the responsibility of onboarding, ingesting, integrating, and using the data falls on the shoulders of IT. Many weeks or even months are spent on implementing custom codes and performing extensive data mappings to onboard and integrate complex data streams. During that time, customers are forced to wait to connect with business workers and receive the value they’ve been promised. 

With a self-service data integration solution in place, companies can complete data integration and related steps much more quickly than they can using legacy approaches. What’s more, business workers can connect with customers and deliver on their emerging needs and requirements much sooner.

4. IT burdening

Traditional data integration solutions put tremendous pressure on IT teams as they devote their time to finish data-driven tasks, such as onboarding and integration, while struggling to perform more high-value strategic tasks. By using self-service data integration solutions, companies can free up the IT burden and empower non-technical business users to implement data connections. Meanwhile, IT can focus on other strategic business priorities. 

5. Slow onboarding

IT teams take weeks or months of calendar time to onboard customers. Such a long wait period frustrates customers and fills them with dissatisfaction. Under these constraints, such unhappy customers decide to either not invest in other products or services offered by the company or switch to a new provider. In such situations, companies are bound to witness a steep rise in business costs because the cost of acquiring a new customer is way more than retaining an existing one.

Self-service data integration solutions can solve this problem. They empower non-technical business users to onboard customers 80 percent faster, thus enabling companies to connect, transact, and deliver value to customers more quickly than ever.