公司规模
Mid-size Company
地区
- America
国家
- United States
产品
- Attunity
- Amazon Redshift
技术栈
- Oracle
- Microsoft SQL Server
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Cost Savings
技术
- 基础设施即服务 (IaaS) - 云计算
适用功能
- 销售与市场营销
服务
- 云规划/设计/实施服务
关于客户
Veritix (now part of AXS) specialized in digital ticketing, event marketing, and relationship management applications for professional sports teams, artists, and entertainment venues around the world. With their analytics reporting, their customers can target demographic groups more effectively, improve season ticket renewal rates, and bring new fans into arenas.
挑战
Veritix’s transactional database was used for both production purposes and reporting. As a result, it wasn’t optimized for analytics and performance was a concern. Running analytics on the production machine would have overwhelmed system resources. Rojas’ team decided to create a separate data warehouse which would store a decade of event data, as well as additional information to enrich analyses such as weather, drive times, and fan income. The project goals were twofold: to develop a high-performance analytics data warehouse and to tune the existing production database for transactions. Veritix was primarily using Oracle, but they also had some Microsoft SQL Server databases. As they looked to expand their data warehouse, they performed a cost analysis of a traditional, on-premises data warehouse and found that it would cost millions to achieve the performance levels that they required.
解决方案
Veritix looked to the cloud for a solution. By doing a series of cluster tests on Amazon Redshift, they found that the cloud-based data warehouse could deliver the performance that the company needed while supporting multiple database vendors. And, Amazon Redshift pricing was an order of magnitude less expensive than the other solutions they looked at. After deciding to move forward with an Amazon Redshift data warehouse, Veritix began exploring ways to replicate data from their on-premises databases to the cloud. Initially, the team assumed that they would need to build custom tools or rely on an off-the-shelf solution like Microsoft SSIS. They did an initial experiment which started with the team creating a backup. Then they moved it to the cloud, restored the backup to a staging database, and tried to move the staging database to Amazon Redshift. Veritix was disappointed to find that it took seven hours to transfer the data, plus an additional 14 hours to restore it to the staging database. This approach was so time consuming that it would only be possible to move information to Amazon Redshift once a day. One of Veritix’s data scientists mentioned the challenges to the team at Amazon Web Services who recommended Attunity for the job.
运营影响
数量效益
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