6 Top Challenges in Data Integration Services You Shouldn’t Ignore

Posted by Lily James on December 16th, 2021

Data integration presents a wide range of important information that allows your business to deploy new modern services, but data integration services won’t be successful without overcoming several challenges. Your data can hinder your business intelligence, analytics, and modernization techniques if you don’t work with the right attitude, tools, or strategy. So what will be the result? An inactive organization that lags behind its competitors and fails to satisfy the client\'s demands.

Well, firstly, you need to understand what data integration challenges are and what steps you should follow to avoid them.

What Data Integration Challenge Are There?

A data integration challenge can be anything preventing you from attaining control over the processes and outcome of your data integration. It\'s one of the major obstacles in your way of receiving a single, unified vision of your data.

Data integration includes capturing data from different sources and combining it to generate a single, unified view of complete data. This merged data makes it easier to depict insights from your existing data is processed to deliver faster, more impactful business growth.

Trying to ignore data integration challenges can cost you significantly; therefore, overcoming the top data integration challenges is imperative when you’re processing data integration at scale and maturing your data strategy.

What are the top data integration challenges you shouldn’t ignore?

When you have got a complete overview of what data integration challenge can be ahead, it’s time to explore some more specific common examples. Below are the six challenges your business can encounter while implementing data integration services alongside, possible solutions.

Incorrect Data Availability

You want to keep your data at one centralized place but, you are putting effort into its execution. This data integration challenge is generally an outcome of relying on human resources alone. It takes developers time to collect data from various sources and combine them manually. Here, your organization has to spend time evaluating data insights and executing valuable business best practices.

So, it will be better if you trim down the middleman and consider the assistance of a smart data integration tool and accelerate your innovation objectives. In this way, most of the heavy work is managed for you. Opting for an automatic data integration platform is a great approach to solve your data integration concerns.

Latency in Data Collection

A few processes need immediate and real-time data collection. For example, if you’re a retailer owning an e-commerce business site, it would be preferable to display customized, targeted ads to every customer based on their search history.

But, if your data isn’t gathered at the required time, you won’t be able to meet these demands. Regrettably, depending on your team to assemble data manually in real-time, is clearly impossible. Probably, you don’t have the right resources or manual power to embark on such a hectic task. If you want to drive real-time data ingestion, your only effective approach is the acquisition of a proficient data integration tool.

Incorrect Data Format

Irregular data sets that are jumbled or do not exist in the correct format will not be actionable and therefore will lose their value. While manual formatting, validating, and correction of data is common, it requires a lot of your developer\'s precious time. Data transformation tools remove these concerns by analyzing the original basic language, finding out the correct formatting language, and automatically building the change. This process eliminates the stress out of data integration and restricts the number of errors, particularly when your data team can identify and examine code at any end in the transformation pipeline.

Poor Data Quality

Poor quality of data in your organization can lead to a loss in revenue, missing important insights, and damage to the reputation. That’s why data quality management is a necessary component for empowering modernization, keeping compliance, and driving more precise business decisions. And it is not as tough as you might be thinking.

You can restrict and reduce the amount of bad data flowing into your systems by dynamically validating your data as early as it’s ingested. Above this, you can also examine your data pipelines for outliers and identify errors automatically before they create bigger issues.

Data Duplication

It’s estimated that more than 92 % of businesses have duplicate data in their systems. At first, the existence of duplicates in systems may seem harmless, but they can create severe long time concerns. So, the greater number of duplicates you have, the bigger the risk to your business.

Usually, these duplicates are the outcome of a ‘silo mentality’ issue. The duplication and unnecessary variations become normal in the data integration pipelines if the employees don’t share data and correspond with each other effectively. To restrict the creation of duplicates and eliminate data silos:

• Create a data-sharing culture in your organization and spend time in training colleagues
• Standardize data after validation and make sure that everyone understands it
• Invest in technology that helps in team collaboration
• Keep regulatory reports that encourage transparency and keep an eye on data lineage

Lack of Understanding

The communication between technical and business teams regarding data sharing plays an important role in data integration. But setting up a general vocabulary of data definitions and permissions is equally essential.

You can create a common understanding of data among the users through:

Data governance- This process focuses on the procedures, rules, and regulations that are covering your data strategy.

Data stewardship- A data steward is the person who supervises and coordinates your strategies, executes policies, and aligns the IT department with the business strategists.

Without a managed executing plan and clear ownership of your data, you will continuously struggle during the integration processes.

Defeating the Data Integration Challenges!

Today, the quantity of data generated by businesses each day is growing rapidly and has a critical impact on organizational success. However, until you overcome these six top data integration challenges, you won’t be able to make the most out of your applications, activities, and processes.

With professional Data Integration Services, you can get things right by empowering an automatic data integration platform to use data as a keystone for accelerating the business transformation and ensuring the growth and development of your organization. ExistBI offers Data Integration Service throughout the United States, United Kingdom, and Europe.