For enterprises these days, taking real-time data and harnessing them for valuable insights is a key process. Data replication tools and software make this possible without disrupting business operations and the incoming flow of fresh data. It is a different way of dealing with data compared to traditional methods.
Consider that your business has a mobile application whose community of users is exponentially growing. The wise thing to do is to collect as much available data as you can in order to come up with actionable points for improving your service and growing the business further.
However, analyzing such data could be time-consuming and complicated, and you wouldn’t want to utilize your master database for such processes so as not to disrupt the application’s performance. Coming up with a separate business intelligence (BI) database is an ideal solution, where the application data is copied and made ready for analysis.
Usually, data is merely “dumped” into this dedicated BI database. This means exporting data from the master database and importing it into the BI database periodically, i.e. every 24 hours or so. This is the practice of many companies, and unsurprisingly so because it is the easiest method.
However, as the volume of data grows, this technique becomes unwieldy and more time-consuming as the amount of data that needs to be moved from the master database into the BI database grows. This takes longer and longer time, defeating the the purpose of being able to analyze such data to make quick business decisions.
This sort of “big data” is what many companies deal with today, in a data-hungry economy that is constantly online for activities like e-commerce, Internet-based entertainment, and social media. The data generated in such activities is immense and fast-moving, and is increasingly difficult to manage and analyze.
Change Data Capture
A more effective and viable data replication approach is change data capture (CDC). Here, instead of dumping whole databases to update information, only the data changes are tracked and captured from the master database. These changes are then applied to the BI database to keep everything in sync.
As you can imagine, this technique is much faster and is able to cope with the influx of information in near real-time capability. Since data changes are the only ones being tracked, the processes involved are much less, and the system can adapt to growing volumes of data.
There are many ways to identify database changes, such as looking at the time of modifications or the general differences between the main database and the BI database. Database triggers can also be utilized, where certain changes in the main database sets off replication.
There are many pros and cons to these different methods, but these days, most companies favor a log-based CDC approach where the databases are kept in sync through transaction logs or a history of changes made to the data. This technique is beneficial especially for big data or systems where a lot of transactions are made.
Tracking database changes
So just how can your organization benefit from understanding the changes happening in your database?
- It provides you valuable insight into aspects such as consumer behavior, customer satisfaction, sales processes, and the like. These enable your business to quickly adapt to trends or anticipate change.
- It enables you to review the previous state of your data, and learn from errors or incorrect processes. You can also backtrack to analyze and diagnose certain issues.
- Keeping data history is usually mandatory in many industries today, such as banking, finance, healthcare, etc.
Data replication solutions and data analysis are truly indispensable for business owners today for the wealth of information that real-time, big data provides. Be sure to find the right data solutions that are tailor-fit for your organization’s needs and requirements.