How to Choose the Perfect Data Integration Software

Data integration solutions combine data from numerous different sources in order to deliver integrated information that can be used to obtain actionable insights. While numerous enterprises across verticals are adopting data integration software to fulfill their digital needs, choosing this software is not always easy—especially if the needs of the organization are complicated.

What is the data integration software going to be used for?

This question comes with two follow-up questions:

• What will data integration help the user achieve?
• Is there a business need present for data integration?

Data integration software like Informatica PowerCenter has numerous applications, including for one-time projects like data migration, ongoing data operations such as automation, and the transfer of data jobs to non-developers. Vendors offer different features and unique benefits, pricing, service models, and support packages. Deciding on what it wants the result of a successful data integration deployment to look like will help the buying company enormously.

Where is the data located?

Where the data sits greatly influences the features that the integration software needs. Users need to consider the type, number, and nature of the data sources that they are looking to connect. Companies that are working with a single large database will have different requirements than those looking to unify multiple data sources globally. Moving data from in-house storage to the cloud has a different set of requirements as well, which are fulfilled by solutions from companies like IBM. The right solution will ensure that the security, agility, and control of the enterprise over its data does not diminish over the years.

What future data needs does the company have?

Companies need to evaluate potential data integration solutions based on how they meet their needs today. At the same time, these companies should also think about how their data needs are going to change in the future. Flexibility in data needs and business processes is critical, and it is important to ensure that potential solutions are able to scale with the business and provide support for greater complexity as and when needed. Follow-up questions to consider include:

• Will the volume of data to be processed grow or fall, and will the number of data sources being a connected increase or decrease?
• Will there be a use case for faster data processing after a few years?
• Are plans afoot to create a data lake or a data warehouse?

Companies like Microsoft provide advanced long-term data integration solutions.

Who will use the data integration software?

Whether the software is going to be used by business teams or IT teams greatly affects the type of service and solution to be chosen. Different solutions demand different levels of self-service and resources for in-house management. While non-IT teams might be interested in data integration, they might not be technically capable of managing raw data.

Vendors with active online communities and detailed FAQs—such as Oracle—are always a safe bet, especially when non-IT employees are going to use the solution. However, the cost and availability of professional support should also be assessed. Finally, businesses should define their operational expectations from the solutions—which team is going to provide maintenance, and what access levels will they need within the system for smooth upkeep?

What budget does the company have for data integration?

A realistic budget for data integration software should account for license costs, the cost of consultants and developers, and the cost of maintenance, support, and product upgrades. Users must explore all pricing options and ensure that the licensing structure that they choose is well-suited to their business. Big-name vendors like SAP are often expensive but ensure all business needs are catered to, while cheaper vendors might not provide all the services that will be needed in the long run, so this choice needs to be made carefully.

Few Real-World Applications of Data Integration Software.

Retail

Whether a retailer operates online or through a bricks-and-mortar presence, it deals with large volumes of data on a daily basis. In order to track vital business statistics at both micro and macro levels and make local and global business decisions, management teams need to have all their data in a single location regardless of where it was collected from. Data integration solutions like Informatica PowerCenter empower retailers to manage sales, labor hours, inventory, and other key metrics across the business.

Credit Rating

Credit rating companies require accurate data insights in order to function effectively. With data integration tools like IBM InfoSphere DataStage, these companies can collect higher quantities of data from current and new sources in order to ensure that their ratings are as trustworthy as possible. With deeper data, these organizations can also rate new metrics using new methods. By constantly gathering and analyzing information, credit rating organizations can keep their rating systems relevant and increase demand for them.

Banking, Financial Services, and Insurance

Financial fraud is almost as old as finance itself, and as banks and other institutions become more digitalized, fraud it taking on new and more innovative forms. By leveraging data integration software like Microsoft Azure Data Factory, banks and other financial institutions can identify, prevent, and eliminate instances of fraud. Once their customer and financial data is integrated, they can use AI-powered features to continuously monitor this data for outliers and anomalies, allowing them to detect and mitigate the effects of fraud even before it can affect the targeted customer. With siloed or fragmented data, early intervention like this is close to impossible.

Healthcare

The more information healthcare providers have when treating a patient, the more likely it is that a successful outcome will be reached. When patient and other medical data is siloed in numerous different systems, it compromises the quality of care. Healthcare institutions have begun to use data integration tools such as Oracle Data Integrator and Oracle GoldenGate to integrate all relevant medical data into a comprehensive record. This has the potential to transform healthcare by helping control costs, improve outcomes, and elevate health & wellness.

Telecommunications

Customer service is a vital part of the telecommunications industry. By integrating customer, subscription, usage, and other data in a central database, customer service personnel can gain an end-to-end view of the relation that the company holds with each and every client that contacts them. Along with this, solutions like Talend Data Fabric are able to provide accurate insights into issues that generate more customer service contacts or show trends of poor customer satisfaction. Using these insights, management can take measures to identify and correct such situations. With data integration solutions, telecom companies can personalize their services for every customer.

Marketing

Marketing relies strongly on detail—if every aspect of a campaign is not finely-tuned, the message of the outreach effort will not resonate with the target audience like it should. Marketing companies collect data on thousands (and sometimes millions) of consumers, and this can easily become unmanageable. With data integration software like SAP Data Services, marketing teams can avoid wasted budgets and substandard campaigns by keeping their databases accurate, organized, relevant, and up-to-date.