There is no business immune to data generation. The rate of data generation is incredible, and companies must find a way to manage data streams in real time, almost as they are generated. Furthermore, in every business there are different systems used for everyday operations, which means that it can be very difficult to manage it all and get the right data in one click.
Signs for integration
Usually, different business software/applications can't communicate directly with each other. Since every software solution has its own data formats and schemas, data compatibility and consistency often present a challenge.
When dealing with different systems, there are some signs that integration could improve business operations.
Sign #1 - Data silos. Inefficient workflows, lack of collaboration, lack of insight into operational affairs is a result of siloed systems and applications that don’t communicate with each other in a proper way. The more different data sources ingesting, the less efficient the processing.
Sign #2 – Data volume. As data volume grows, it is getting harder to manage it, to find the right information at the right moment, the communication between different systems is becoming more and more complex, the delivery of information slows down, and the integration itself is becoming more and more complex.
Sign #3 – Data processing time. Time is money, and so is real-time data processing. High-performance data processing that can handle a huge number of events in a second is key for real-time data processing which then can support business operations in the right way and in a timely manner.
Benefits of the real-time data stream
A reliable tool for managing real-time data streams can help companies to solve the issues described above. Apache Kafka is one of them. Kafka provides a solution that can help optimize and speed up data processing from different systems. As an open-source distributed streaming platform, it has gained popularity in recent years. That’s why we are going to describe some of the main benefits of using Kafka.
Efficiency. Because Kafka enables real-time data processing and delivery, it provides data streams in real time and decision making is faster and based on better information. Different systems are connected, and data generated in each of them are processed and delivered as soon as they are generated. By implementing Kafka and thanks to its architecture, data are processed in real time which is a very valuable tool for applications processing high volumes of data. This leads us to the fact that the applications are always up-to-date, and you can access the latest data in real time and therefore the efficiency is improved as delays are minimal and bottlenecks in data processing are eliminated. Kafka simplifies the overall system architecture by reducing number of point-to-point integrations.
Scalability and Flexibility. Kafka can be integrated with other applications and platforms made using popular programming languages like Java, Python and Node.js. Based on this, Kafka is a flexible tool by itself, which means that it enables your business to be more flexible because it's easy to scale up or down. In addition, Kafka’s architecture allows easy scaling and therefore handling huge volumes of data without significant hardware upgrades. By integrating with various systems and technologies, businesses can process data from various sources regardless of data format.
Data integrity. The Kafka architecture itself is designed in order to minimize data loss, making it a reliable tool for companies dealing with real-time processing and delivery of huge data volumes. Even if a node in the cluster fails, data will not be lost thanks to data replication on multiple nodes in the cluster. Reliability and fault tolerance are ensured through data replication, data backups and storage on multiple nodes, so they are always available. It also ensures data insights and improves data-driven decisions. By accessing information, up-to-date decisions can be made faster, which is important for quick response to changing market conditions, customer needs as well as to other business events.
Challenges that may occur
There is no doubt that the integration of different systems with Kafka will bring benefits. But integration has to be conducted in a way that eliminates usual challenges that may occur.
Complexity. Although the aim is to simplify data processing, the path can be very complex depending on the systems that need to be integrated. So, it is important to have the required expertise overall, as well as expertise in system architecture and data integration since it can be very challenging to ensure data compatibility and consistency.
Quality. Integration alone isn’t enough. Data governance policies and practices that will ensure data quality are also crucial. Having in mind that different systems may use different data formats and schemas, this can also be very challenging.
Security. The integration of different systems can increase the risk of cyber-attacks. So, it is very important to implement adequate security measures that will protect data and ensure compliance with data protection regulations.
For companies looking for solutions that will manage real-time data streams, Kafka is one of the tools. It is a great tool for companies that want to have real-time data streams and processing without compromising on scalability, flexibility and fault tolerance. By leveraging Kafka’s capabilities, companies can have always-up-to-date data and information-based decision-making. If you are one of them, please feel free to reach out to us, we will be glad to discuss if we can help. If you're wondering how we are doing that, feel free to read case study about integration of crucial data hubs.