facebooklinkedinrsstwitterBlogAsset 1PRDatasheetDatasheetAsset 1DownloadForumGuideLinkWebinarPRPresentationRoad MapVideofacebooklinkedinrsstwitterBlogAsset 1PRDatasheetDatasheetAsset 1DownloadForumGuideLinkWebinarPRPresentationRoad MapVideo
Actian Blog / Why you Should Offload Analytics from your Online Transaction Processing Systems into a Data Warehouse

Why you Should Offload Analytics from your Online Transaction Processing Systems into a Data Warehouse

AV20 A

Modern businesses are fueled by data.  The insights that your data bring are what power decision making, enables you to optimize business processes and respond to changing market conditions.  The organizations that have data and manage it well – excel.  Those that lack data or struggle to harvest actionable insights from their data have a tougher time.

One of the most significant challenges IT has as the stewards of company data is striking a balance between high-performance real-time data processing performance of individual business processes and the deep/enterprise-scale analytics required for solving the company’s biggest problems.   By offloading analytics from Online Transaction Processing (OLTP) systems into a cloud data warehouse like Actian Avalanche, your company can achieve both objectives at the same time.

Sustaining High-Performance in your Business Systems

OLTP systems are your transactional business systems – the tools that your employees, partners, and customers interact within the course of normal day-to-day business activities.  These systems are optimized for real-time data processing (as they should be).  Any impact on performance has a direct impact on your process cycle times and employee productivity.  With each new business transaction, you create more data.

As the size of your OLTP database grows, the applications that run on it begin to slow down. Adding an analytics load on top of the transactional processing makes the problem even worse.  Sustaining a high-performing business system requires continuous active tuning of the OLTP system to eliminate any non-essential activities.  A key technique that IT teams employ is to offload analytics processing into a data warehouse, freeing up compute capacity in the OLTP system, so business software has more system resources from which to draw.

Leveraging Change Data Capture for Real-Time Analytics

Change data capture is an analytics capability available in nearly all databases but is mostly used to populate data warehouses.  What this capability does is to monitor for changes in your transactional data that might correspond with business events that represent opportunities or threats for your business.  Some changes in business transactions are good… an incremental increase in sales transaction values. Other changes are adverse… such as a sudden drop in the number of users logged in to your website.  Change data capture can help you understand when something is awry, so you can assess the impact and determine if any corrective action is required.

Running change data capture operations on OLTP systems can be problematic.  The overhead load it places on the system has to be monitored to minimize the performance impact to your business systems.  Change data capture is most valuable with larger data sets for analyzing trends.  If you have a good log archive management in place, performance overheads can be contained.  So, it makes sense to use change data capture to populate your data warehouse system with near-real-time business operational data.

Extend the Useful Life of Your Business Systems

Business systems like Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Human Resource Management (HRM), IT Service Management (ITSM), and eCommerce systems are costly to install, but disruptive to the business when you need to replace them.  If the systems you are using today run on-premise in your data center, upgrades to hardware infrastructure to add compute capacity may require new capital outlays and/or migration to the cloud.  Offloading analytics from these systems into a data warehouse can help you keep these systems running longer with existing resources – postponing the impacts of system upgrades.

Over the next few years, new business systems offerings that are cloud-native, integrate Artificial Intelligence (AI) capabilities, and have enhanced support for streaming data are poised to come to market, creating a natural time to upgrade.  Extending the useful life of your existing systems gives your company the flexibility to wait for the new features that are “coming soon” and catch the next wave of emerging technology to maximize the return on investment of your upgrade projects.

Offloading analytics from your OLTP system into a data warehouse is a smart IT decision.  It helps keep your business systems running faster, gives you the real-time data insights you need for agile decision making, and extends the useful lifespan of your existing systems, so you capture the next wave of technology innovations that are just over the horizon.  Actian Avalanche can help.  As a hybrid cloud data warehouse solution, Avalanche can run on-premise, in the cloud, or even as a hybrid, split across different environments giving you the analytics capabilities and scale that you will need to manage your company’s data successfully.

To learn more, visit www.actian.com/avalanche

 

About Pradeep Bhanot

Product Marketing professional, author, father and photographer. Born in Kenya. Lived in England through disco, punk and new romance eras. Moved to California just in time for grunge. Worked with Oracle databases at Oracle Corporation for 13 years. Database Administration for mainframe IBM DB2 and its predecessor SQL/DS at British Telecom and Watson Wyatt. Worked with IBM VSAM at CA Technologies and Serena Software. Microsoft SQL Server powered solutions from 1E and BDNA.