Enterprise data. Whether you’re ready or not, it’s growing more and more important to organizational success every day. Business decisions, business insights, and business intelligence all depend on having the right data at the right time.
One of the reasons data management is so tricky is because data is siloed across a myriad of disparate sources—it might be stored in multiple clouds, enterprise systems, or hybrid environments, and issues with duplicative data sets abound across the board. And as data proliferates, database integration work, including big data integration, just gets more complicated.
This is where data integration solutions come into play. These tools can bring data together from all over for a unified view of your organization, customers, and processes. In this blog we’ll define and explain the different data integration tools available today, plus, we’ll share three critical questions to ask before purchasing a data integration tool.
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Data integration is the process of connecting data from different systems into a central repository for organizational data clarity and continuity. This is a vital step in developing any business application and essential for organizations that want to unlock the full potential of their data and use it to drive better business decisions.
If an enterprise organization has data stored in different systems and formats, bringing it all together is usually difficult. But by integrating data, organizations eliminate data silos, improve data quality and consistency, and streamline data analysis and reporting. So it’s worthwhile to invest in a data integration tool that makes the whole process faster and easier.
Integration tools have traditionally been limited to the likes of enterprise data warehouses and data lakes. These tools extract data and migrate it outside of its current domain. However, modern data integration tools like data fabrics take an interesting new approach.
Data fabric technology virtualizes disparate system data into a centralized platform, complete with the ability to connect, relate, and extend data. With a data fabric, you can unify data architecture and management while keeping data in its current format. Data fabrics can drastically improve the speed, integrity, and security of your data.
[ Want to learn more about how data fabric can transform your organization's data management strategies? Watch the on-demand webinar. ]
Data silos and disparate sources are scattered across every organization, and it’s the role of data integration tools to unify them. Data integration enables organizations to access, analyze, and use data more effectively, which can lead to better decision making, improved operational efficiency, and business growth.
Because organizations stand to gain so much value from data integration, plenty of solutions on the market aim to help. But all solutions are not created equal—you need to be strategic in your investment. Here are three questions you should ask about your current data integration tools and before purchasing new ones to ensure they are a good fit for your organization's needs.
1. What is the purpose of the solution?
You should know the specific purpose of the solution you select. What was the initial reason it was added to your stack, and how is it being used currently? Do your enterprise applications need to access data that originates in a variety of sources across a hybrid environment? Or is it a more niche use case that involves a cloud integration between just a couple of systems? Is it providing real-time data to business users who need actionable information quickly?
The answer to these questions will help you determine if your current setup is helping to connect data or if you are simply adding more steps to collect it. These questions will also help frame what success you can expect from the solution and give you business insight into new opportunities to leverage and extend its integration capabilities.
[ Are you connecting data or just collecting it? Read our related article: Data Fabric vs. Data Mesh vs. Data Lake.]
2. Where is all of the data coming from and ending up?
You need to understand what specific data is being integrated and where that data ends up. Are you taking data out of legacy systems and customer applications and adding it to a business intelligence or analytics platform? Are you taking multiple customer records across cloud environments and adding them to a data lake?
This is where a visualized app integration map can help you see exactly what the flow looks like. Once again, the data integration solution should be breaking down silos and creating unity, not causing more work, migration, and additional lags in latency.
3. How does the solution govern access to data?
This is perhaps the most important question. You need to be absolutely certain that your data integration solution is handling your data appropriately, ethically, and securely. Your tool’s policies, procedures, and controls must be granular enough for you to ensure both internal and external access to data is in compliance with industry standards and any regulatory measures.
To answer this question, you should start by determining your business demands for data. Who needs access to what specific data sets and when? It’s now essential to have a secure approach to data enterprise wide, and your data integration tools should support this effort, not become another security hurdle.
A data integration solution can be the catalyst for creating a data-driven culture that drives great efficiency and growth for your organization. Businesses that unify their data and make informed decisions will be set up to succeed in the age of digital transformation. However, all data integration solutions are not created equal. Use the questions above to ensure your solutions are securely meeting your business demands.
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