How Log-Based Changed Data Capture Can Support Critical Business Decisions


With virtually every second that passes in today’s world, a piece of vital information is generated somewhere—whether it be an online transaction, a post on social media, an incremental change in climate temperature that is being monitored, or a slight movement on the stock market.

This is the nature of data and communications in the digital age of the 21st century, and never has there been a time when information is generated and exchanged so fast that it is becoming increasingly difficult to observe and capture, much less appreciate. The good news is that computer technology is catching up and providing valuable tools by which real-time data can be monitored as well as analyzed.

Database replication solutions

Database replication software is a necessity for many businesses and organizations these days that need to keep a pulse on the relentless stream of information, especially with the rise of the Internet of Things (IoT)—the interconnectivity among various digital and telecommunications devices.

Such a solution copies generated data into a business intelligence or BI database so that it can be analyzed without disruption at the source. The database is updated almost instantaneously with the help of change data capture or CDC techniques. As the name implies, CDC monitors changes in the data and uses this to update the database.

CDC can be carried out either as a trigger-based or log-based task. The former creates triggers based on conditions in order to carry out the change data capture, which may be potentially time-consuming. The latter is more preferred because it has minimal impact on the database, since it bases actions on log changes only. It is also faster and more responsive, especially when handling large volumes of data.

CDC for real-time business intelligence

Traditionally, ETL or Extract, Transform, and Load (or ELT) tools have been preferred for extracting data directly from data tables. However, due to the increasingly large volumes of data that need to be extracted in its raw state and then moved into the BI database, such procedures are carried out in batch windows. These batch windows usually end up being implemented at night, during typical off-peak operational hours.

As one can imagine, such unwieldy and time-consuming processes may not be relevant or effective for the big data that companies need to deal with these days. Near real-time data replication must be achieved so that data can be fed into analytical systems in order to arrive at usable insights that businesses can use for more effective BI strategies.

Such insights are important in making quick and critical daily business decisions in today’s fast-paced and highly competitive market. For instance, many retailers these days monitor consumer behavior closely, such as browsing activities and purchase histories Using this information, real-time analytics can help determine other products that retailers can push to consumers based on their preferences, thereby increasing sales and improving profitability.

Change data capture complements and augments ETL or ELT technologies in order to make them more efficient and applicable to contemporary business needs. Such end-to-end data integration solutions now allow enterprises to trickle-feed insert, update, and delete operations continuously from multiple sources. These are then consolidated into a data warehouse or enterprise data lake, where the ETL or ELT tool then transforms the data into small batches even within the day—doing away with nightly batch window outputs.

Investing in CDC replication solutions

Some business owners may find migrating to log-based CDC solutions for database replication to be quite a hassle, but it is an investment that brings tangible returns to the bottom line in a very short period of time only. Consider that real-time data replication and analysis through CDC technology enables companies to make quick strategic decisions that lead to more sales, improved customer satisfaction, and more efficient operations.


About Author

Leave A Reply