The 6 Biggest Data Integration Challenges (and How to Solve Them)

The technology-driven world has always been in need of a data integration platform that consolidates all their data in a way that helps them develop better business insights. The big data integration tools assist in integrating data generated from numerous applications into a shared space and that, too, after converting a whole lot of information in a single format for an adequate understanding by even non-tech personnel. With marketing data integration, you can efficiently enhance data accessibility, improve collaboration & teamwork, and boost the overall working of an organization.

What is Data Integration?

Data Integration is a process that involves a systematic series of operations used to consolidate data from different organizational systems, converting it into a single format, and then loading into a data warehouse that is accessible to the authorized personnel for framing the best business decisions.

The increasing competition in the data-driven industry is compelling every organization to get hold of an efficient data integration platform that can fetch them all the relevant data in no time. Breaking down the big and complex data is not as easy as it seems. There are various challenges that an enterprise face while managing all the organizational data effectively. The data integration challenges somewhere restrict the enterprises to make the most out of their business and market data.

Sometimes, it becomes complex to handle big data. There can be multiple challenges that can make it difficult for you to use big data sets efficiently. To help you out, we are listing down the biggest data integration challenges and how to solve them.

• Struggling to get the data where you need it: This data integration challenge mainly occurs when an enterprise solely depends on manual ways of consolidating data. Depending on data specialists to curate data from multiple source systems and combining it takes a lot of effort and time, and that often delays the process of analyzing the data and driving useful insights from them. The delay in decision making can cost the enterprise the best business opportunities that have the power to take their business on the top of the competition curve.

So, to cut out the middleman and speed up your integration process, it’s better to implement the use of a reliable and efficient data integration platform. This will do most of the data consolidation work for you. It’s a great way to wave goodbye to your data integration issues.

• Not getting the benefit of real-time accessibility of the data: Every organization has some processes that require the real-time availability of data to make the right decisions at the right time. For example, you are dealing in the e-commerce business and want your site to display customized ads to every customer based on their search history. But without the availability of data in hand at the same time, it becomes impossible for you to implement customized ads option.

One way you can combat this challenge is by enlisting an automated data integration platform in your core process that will fetch you all your relevant data from different platforms in real-time.

• Not getting all your data in a specific format: Consolidating all your data on a single dashboard is useless until it is not precisely formatted. Manual formatting of data involves time and higher chances of errors.

Data transformation tools help you save your developer’s precious time and eliminate the chances of errors in the data formatting process. The tools will analyze the original base language, determine the accurately formatted language, and automatically make the changes. This way, you can boost your transformation pipeline and get properly formatted data in hand within the expected time frame.

• The questionable quality of data: Poor data quality of data leads to poor decisions and cost you a major part of your revenue. This is the reason why many enterprises are creating a separate department for data quality management to ensure the optimum quality of data that will aid them to make more accurate business decisions.

By proactively validating your data at the same time when it is consolidated, you lower the chances of bad data entering your systems. Apart from this, you can also monitor your data pipelines for outliers and automatically spot errors before they become issues that are difficult to handle.

• Data duplication: Fetching the same data twice may not seem a big problem at first, but can cause great harm in the long run. The chances of duplicate data increase when the different teams of your organization lack effective communication.

Investing in an effective data integration platform can help your teams to coordinate more effectively and share and make changes to the relevant data in real-time. The platform will seamlessly eradicate the problem of data duplication as well.

• Cost-effectiveness: Before initiating the data integration process, every enterprise must calculate the cost involved in different data integration solutions and their maintenance. Cost plays a crucial factor in any data-driven organization. Estimating the accurate cost can help you to eliminate the chances of the budget shortfall.

Determining data needs to find an accurate budget and investing the same to implement the best integration platform will help you in meeting the project deadlines within time, efficient contract management, achieving high satisfaction levels among employees, and boosting the overall revenue.

The amount of data generated in an organization daily is increasing at an alarming rate, and its efficient management can help a business person to survive and grow in a highly competitive market.