The owners of the "Left-Hand Store" are frustrated. Yesterday, they sent a discount code to selected customers. Today, they want to find out whether the campaign has paid off. If they discover that sales of left-handed can openers have increased, they will send the discount code to all their other customers. But – the shop owners don't know whether the campaign has worked because they are still waiting for the report. The database is overloaded and is taking much too long; the data marts are late and waiting times for the reporting tool are excessive. Under these circumstances, there is little point carrying out A-B-testing or other time-critical analyses, let alone attempting to create future campaigns based on report findings.
Many companies are familiar with the problem: their database, originally a lean and agile data model, has grown into a data warehouse behemoth. The opportunities that modern data warehouses have to offer, at least in theory, are therefore a long way off. The daily loading time is becoming increasingly tight, not to mention impromptu loading during the day. Quite apart from the slow data processing, it is becoming increasingly complex and expensive to integrate new sources. At some point, every performance optimization reaches its physical limits.
Ideally, scoring models or the data marts upon which they are based will contain more than just data from a CRM system and the current stock levels. Weather data, for example, can help to promote seasonal products; mass data from a dedicated app can be used to tailor products more precisely to customer needs, and a link to Twitter can reveal trends that are relevant to the target group.
In order to make use of all these sources and data, a company needs a performant data warehouse with a good architecture, or at the very least, a modern, scalable technology. Exasol is ideally suited for this purpose and comes as standard with a set of tools to simplify migration.
The first step: deploying Exasol in the cloud
Granted: it can be complex and expensive to migrate a database that has grown over time to include many sources, data and reports. Fortunately, Exasol provides step-by-step support for its users in migrating and adapting their existing data warehouse.
First, select the cloud of your choice. AWS, Azure or the Google Cloud are currently available. For this article we have chosen Azure as an example. It just takes a few clicks to get the Exasol database up and running once you have created your Azure account.