Real-Time Software-Based Data Replication
The upcoming 5G technology “revolution” strengthens the use of data from many different databases (including not heterogeneous ones) in real time and becomes a critical business requirement.
A key requirement is access to data (with different geolocations and technologies), their transformation “on the go” and instant feeding data to business applications.
The only solution that eliminates various errors, including qualitative and communication errors, is software-based replication at the database level in real time.
The use of data-level real-time replication is useful and applied in many ways
- real-time applications, such as e-banking, CRM, call center, portals that use various data found in many applications and databases of different suppliers;
- anti-fraud and authorisation systems (electronic payments, transfer of funds);
- access to management data (sales, risk, analytics) or mandatory reporting in real time;
- on-line feed of the data warehouse;
- seamless migration, upgrade of databases for (business) critical applications;
- seamless infrastructure replacement (servers, matrices);
- building high-availability DRC centres that enable practical work-load balancing between DC and DRC.
Real-time data replication
Configurations support rapidly changing business practices such as operational business analysis and just-in-time stocktaking. Data replication is an important part of business continuity, and cases of replication use include operational and analytical applications as well as secure and uninterrupted migration to new software versions and new platforms.
Below are some scenarios for real time replication of data:
Operational business intelligence
This is the most common BI practice. Operational BI retrieves raw data from operational databases and applications and then presents them as metrics or Key Performance Indicators (KPIs) on the management dashboard or scoreboard.
Although many types of tools can retrieve operational data, the ideal solution in this case is replication, as it is relatively non-invasive for applications, has interfaces to for most application data and works in real time.
Reporting has accelerated to include real time data (as evidenced by operational BI), and analytics is now experiencing the same acceleration. As a result, there is a growing demand for real-time data to support time-sensitive analyses such as customer profiling, sales forecasting, pricing optimisation, production efficiency, fraud detection and risk calculation. As with operational BI, real-time analytics can be enabled through replication.
Uninterrupted migrations and technological upgrades
Software version upgrades or hardware platform changes are common in every IT environment. In most cases, such an operation is associated with shutting off applications for the time of migration. Thanks to the use of real-time data replication tools, any migration or technological upgrade can be carried out without system downtime. This is very important for critical production systems, the stoppage of which involves high costs as well as corporate image issues.
Real-time data warehousing
The real-time data warehouse supports time series data to provide a historical context for real-time data. To this end, it integrates, aggregates and refreshes on-demand or at short time intervals data that will be transferred to reports and other BI products.
The key to real-time data warehouse is real-time or near real-time data integration technology, usually involving federation, messaging, micro-batch ETL or replication.
High database availability (HA)
A database management system (DBMS) or a data warehouse may not make data available or operate in real time, only when they are highly accessible. Why is this so important? High database availability is required for any application with real-time data or 360 degree views.
In addition, this is necessary for any time-sensitive or mission-critical application. Data replication is currently the most common mechanism for ensuring high availability of databases.
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