By Rabia Hatim, Senior Marketing Strategist
Reliable data insights play a significant role in delivering tangible business outcomes, whether to help identify new revenue streams, drive greater business efficiencies, or enhance employee abilities to serve their customers better. Unfortunately, many corporations struggle when it comes to getting a complete picture of their organizational data. According to an ESG research report, over 36% of organizations report data integration as one of the top challenges within data analytics technologies and processes.
Many large and mid-sized organizations typically have their data isolated in different systems instead of integrated within the business. Data integration solves this problem by allowing better availability of information for different departments and business processes. However, data integration is much more than that!
An effective data integration solution must allow organizations to merge different data types, leverage the data, and understand where it came from and how it is relevant to the business’s needs. Whether you are going for the ETL approach or the ELT approach for data integration, the underlying story remains the same – driving intelligent insights by extracting data from its original source, transforming it based on various requirements, and finally, loading it to a data lake or data warehouse for analysis.
The real challenge in this regard is acquiring the right data integration solution. It is important to find out the key features before investing in a software that will handle all your enterprise data. Unfortunately, many businesses fail to do so. They end up struggling because of a missing feature, the lack of scalability, or a complex interface among other issues.
Without further ado, let’s look at some of the essential features in a data integration solution that can help your organization streamline business processes. These features can help the enterprise run smoothly by allowing the business to get the right data at the right time and place.
1. Maintaining Data Integrity and Quality
Maintaining the integrity and quality of data received from disparate sources is essential if the business is to draw accurate insights from it that might give the organization an edge over its competitors.
Most of the time, the data received from source systems has errors and inconsistencies that must be removes before it can be used for analysis. These errors may include…
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