Recent developments in the digital business ecosystem have transformed customers’ expectations and business models. It has brought a paradigm shift in the way customers think, approach, and engage. To keep up with the shift and deliver the value promised to customers, companies need to integrate and manage data expeditiously. However, in the current disruptive environment, wherein data has become much more complex not only in terms of volume but also in terms of veracity, velocity, and variety, performing data integration is a daunting task for many; it is complex, time-consuming, and vulnerable to security threats.
The problem worsens when traditional data integration methods are used. These methods require IT to write long hours of custom code and execute extensive data mappings for data integration. Because customer data is disparate and complex in nature, implementing coding and data mappings takes weeks or months of calendar time. By the time IT implements customer data integrations, customers feel forced to wait to connect with business workers and receive the promised value. Another problem is those manual methods are vulnerable to security threats. How? Because every IT integrator in the organization has the access to data, which increases the risk of data breaches or thefts.
Companies that reimagine their data integration approach can overcome the challenges and drive value – easily, quickly, and securely. Self-service and automation have a critical role to play here. But before we understand how these modern solutions bring the change, it is important to be wary about the challenges posed by traditional data integration methods. Then, we’ll unravel how automation and self-service can help companies navigate those challenges.
1. Your data isn’t secure
In conventional business environments, all IT integrators have access to customer data. It’s their job to onboard, integrate, and manage data to help companies make informed business decisions and drive value. Now, when everyone in the organization has access to the data, the risk of breaches or theft is high. In other words, traditional data integration methods are more prone to data security risks because of inadequate and improper access control.
By modernizing the approach, companies can mitigate the risks to a large extent. A self-service data integration solution provides an end-to-end encrypted environment that allows only authenticated users to access and use data. That is to say, all users are individually authorized and authenticated when they are registered and logged in to the self-service integration application. Now, because all data transfers take place over encrypted connections, companies can minimize potential security threats.
2. Your data is complex and disparate
Customer data has become even more disparate and complex in the wake of disruption. It is present in a lot of other formats as well: text, CSV, Excel, fixed-length, XML, databases, JSON, and others. Now, it takes a lot of time (weeks or months) for IT to integrate these data streams manually. The complexity of creating codes and running data mapping flows also adds up to the problem.
Features such as pre-built application connectors, shared templates, dashboards & intuitive screens, and AI-data mapping, enable even non-technical users to integrate disparate, highly complex customer data streams easily and quickly. For instance, businesses can leverage modern ETL solutions to migrate data MongoDB To Snowflake efficiently, ensuring seamless data flow across platforms. In fact, users can leverage these next-gen solutions to implement data connections in minutes instead of months. When business users connect with customers faster, surely, they can address the needs and requirements of customers and deliver on them without delay. This delights customers and encourages them to buy more products or services from the company, creating new revenue streams for the business.
3. Your data quality is poor
Owing to multiple reasons, including human errors and inconsistencies, data quality remains poor. Now, data with poor quality can lead to missed insights, which, in turn, can delay the process of value generation. As a result, customers become unhappy and frustrated. Of course, such unhappy customers won’t feel inspired to invest further, ultimately negatively impacting the company’s revenue-making ability.
By using automation and self-service, the quality of data can be restored. Simply because the risks of errors and other inconsistencies are minimal when automation and self-service data integration are used.
4. Your data is late
Some processes need real-time data to function. But unfortunately, traditional data integration methods do not enable companies to collect and analyze data in real-time. In fact, with the amount of generating today, it’s almost impossible for organizations to consolidate and analyze data instantly using traditional data integration methods.
Self-service integration and automation enable non-technical users to reliably curate in real-time (or near real-time). Only a single click is required to retrieve, breakdown, and use complex, multi-dimensional data and stream it in real time to execute modern-day business transactions.
5. Your data can’t be integrated by non-techies
When traditional data integration methods are used, companies require IT to integrate complex customer data streams. That takes weeks or months of calendar time. Also, IT finds it difficult to focus on more strategic tasks.
By using self-service data integration solutions, companies can empower non-techies to consolidate customer data in minutes while freeing IT to focus on more business priorities. This means IT doesn’t need to create codes or mappings. Instead, they can take up the governance role and focus on more high-value tasks.
Final Word
In today’s disruptive environment, companies find it challenging to integrate complex, voluminous customer data streams. But those that rely on automation and self-service integration can overcome these challenges and stay ahead. In other words, companies can leverage these modern approaches to implement data connections sooner, delivering the value promised to customers, improving companies’ ease of doing business, and accelerating revenue growth.