DATA INTEGRATION SAVES TIME AND MONEY WHILE MAXIMIZING THE VALUE OF SAAS

The average organization used 110 Software-as-a-Service (SaaS) applications in 2021, according to a new report from Statista. That’s 110 different places where data is entered, processed and stored. Generally, these standalone applications don’t talk to one another, so users end up having to repeat data entry in multiple systems. Manual data re-entry wastes time and increases the risk of errors and inconsistencies. Without a “single version of the truth,” users don’t always have access to the most recent data. Security and data protection become more difficult and comprehensive reporting next to impossible. These complexities also make it challenging to meet data privacy mandates and regulatory compliance requirements.

Data integration can relieve these headaches. It involves the use of software “hooks” into SaaS applications that enable data to be replicated and shared among them automatically. SIEM unifies data from disparate systems and single-purpose security solutions that can only recognize and understand certain data types. All security data can be analyzed and cross-referenced from a single interface, enabling human IT analysts to make better decisions. Alerts and reports are generated automatically so that the IT team can respond quickly to anomalous conditions.

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CONNECTING SAAS APPLICATIONS

Some SaaS applications have open application programming interfaces (APIs) that allow the app to communicate with other software. For applications that don’t have open APIs, or for more complex use cases, developers may have to write an extension to the app and host it on a cloud platform. These are likely the best options for integrating two applications.

For organizations that need to share data among multiple apps, it often makes sense to use the data lake and data factory services offered by leading cloud providers. A data factory service connects to a cloud application via an API or extension and automatically updates the data lake when the application updates. Other data factories can then cross feed the data to their associated SaaS applications.

UNDERSTANDING DATA LAKES AND DATA FACTORIES

Traditional data warehouses are designed to accept data that has been processed, cleansed and transformed to fit into a structured, hierarchical format. Data lakes, in contrast, are large repositories that store structured and unstructured data in its native format. Each data element is assigned a unique identifier and metadata tags to simplify querying and analysis.

Data factories sit around the edge of the lake and transfer data into or out of other applications. Let’s say that you have a CRM application, a customer support application, and a finance and billing application, all connected to a data lake by data factories. If you update the customer contact information in the CRM application, the data factory will put the information into the data lake, which then updates the information in the other data factories that use that field. Each factory understands the data formats used by the application it’s connected to and transforms the data as appropriate before uploading it into the application.

LEVERAGING DESEMA’S DATA INTEGRATION EXPERTISE

DeSeMa has a deep understanding of cloud applications, and development teams who can create custom APIs for SaaS applications. Our experts also have extensive experience in the design and implementation of data lakes and data factories.

As an initial step, we will consult with the customer to determine which SaaS applications are in use and how they might need to be connected. If the customer wants to integrate two applications, we will likely recommend an API. But if the customer has multiple applications or plans to connect additional applications in the future, we will likely recommend a data lake to make the solution more modular and scalable. There will be the ongoing expense of the cloud service and storage, but the time and money saved by data integration will more than offset the cost in most cases.

If a data lake is the best option, the next step is to determine which cloud service to use. Each service has unique strengths and weaknesses. For example, Oracle data lakes work particularly well with Oracle products. If a customer has several different applications that use Oracle databases, we will recommend the Oracle Cloud.

KEY TAKEAWAYS

Siloed SaaS applications require duplicative data input that costs time and money and limits the value of the information. The problem is especially acute in organizations that use a large number of SaaS applications. Data integration can boost productivity, reduce the risk of errors, streamline security, improve data protection and increase regulatory compliance. Let DeSeMa sit down with you (physically or virtually) to whiteboard a solution.