4 Features Data Integration Tools Can't Live Without

4 Features All Data Integration Tools Should Have

Data integration uses technical and business processes to combine data from different sources in order to supply a unified view. Unfortunately, data integration is also widely considered incredibly challenging, even for high performance companies. In fact, 36% of organizations report data integration as a top business challenge alongside data analytics and technologies. Data integration tools perform a variety of crucial data integration functions. Crucial data integration functions range from data transformation to mapping.

Data management can be difficult with many different sources of data storage available. A data lake and data warehouse are both commonly utilized data storage reciprocals. Data lakes and data warehouses have different data applications which the best data integration tools recognize. A data lake contains large volumes of raw data in its original format until it is needed. A data warehouse contains many different sources of data for defined purposes.

Data warehouses are commonly utilized for data analytics and data driven decision making. While data warehousing and databases only store structured data, unstructured data can be stored in data lakes. There are also different types of data ranging from structured vs. unstructured data and big data vs. small data. Simply considering some of the components of data integration and data management is enough to overwhelm many people. Thankfully, data management best practices and the best data integration tools simplify and streamline these processes. 7 features all data integration tools should have include-

1. Scalability

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The technology of data integration tools and integration software is constantly evolving. Likewise, the tools data professionals use are largely dependent on their own needs and wants. The best data integration tool for a specific business may not be the best data integration tool option for another. Additionally, the best data integration tool will ultimately be updated and outperformed by another tool in the future. As such, businesses must make sure that their data integration tool is compatible with future tools. Compatibility necessitates scalability for business growth including future investments in additional data tools and software.

Application Programming Interface, abbreviated as API, is an example of scalable software that allows 2 or more applications to interact. A common API example that many people regularly interact with is social media instant messaging. API permits businesses to automate business processes and facilitates data sharing. Cloud data from cloud based applications is much easier to manage with an API. Additionally, API integration tools and integration platforms make sure businesses can extract enterprise data from older databases and servers. Ultimately, an API is an excellent scalable integration solution for cloud based data and applications.

2. Timeliness

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Real time data is an invaluable business resource that heavily influences both data driven decision making and business intelligence initiatives. The ability to satisfy real time business needs necessitates real time high quality data access availability. Unsurprisingly, best practices for data based processes universally stress the need for real time data accessibility.

With more high performance professional services available to customers than ever before, real time data access is essential, not optional. The best data integration solution recognizes the data pipeline to avoid harmful silos and continue high performance operations. The ability to access large volumes of relevant data in real time can even supply businesses with a competitive advantage. The best data integration tools not only help professional services to meet customer expectations, but to exceed them.

3. Accessibility

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With increased technology, workers are more often geographically distant from one another than ever before. However, professionals still regularly collaborate on tasks that necessitate exceptional master data and enterprise data access. The best data integration tools make sure that professionals can access data from a self service portal in real time. The best data integration tools supply not only self service portals but also make sure cloud based accessibility is satisfied.

A cloud based self service portal allows workers to access a unified view of data regardless of their geographical location. With so many different sources of data, the unified view that the best data integration tools provide is essential. The best data integration tools also make sure that information is relevant with real time data updates. Without the accessibility that the best data integration tools provide, accomplishing high performance business operations is unlikely.

4. Quality

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The best data integration tools are integrable with data quality and data governance tools. High quality data is absolutely essential for high performance business operations. The best data integration tools do not sacrifice data quality for real time remote data access. Businesses should steer clear of any integration tool that compromises data quality in any way. Unfortunately, low quality data can measurably decrease business intelligence intergration.

Not only businesses benefit from the high quality data that the best data integration tools supply. High quality data also significantly positively impact customer satisfaction and the overall customer experience. The high quality data that the best data integration tools afford benefit both a business and its customers.

Key Takeaways for Data Integration Tools

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  • The data integration process is a top business priority that includes careful consideration regarding the tools data integration professionals use.
  • Tools data integration professionals utilize should be scalable, timely, accessible, and high quality.

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