About the Client
Founded in 1998, the Client have more than 20 years of experience in revenue optimization and successful deployment of revenue management solutions internationally.
Over the years, the client has built a solid customer base delivering products that continue to provide outstanding quantifiable returns for customers. The Client provides exceptional service and results to customers from hospitality & gaming and multifamily housing industries.
The Client provides solutions to hospitality & gaming and multifamily housing industries with an ability to forecast demand accurately and deliver precision pricing in a manner that would enable their customers to control their pricing and occupancy strategies.
Client’s main challenge was to extract the data from its customer’s database, so that it can be exported to the client’s data warehouse, which was handled manually with limited access to large volumes of customer’s data.
In the Data warehouse, these large volumes of data go through multiple levels of data filtering and then they are exported into the Client’s Predictive Analysis tool.
The Predictive Analysis tool runs certain algorithms on these data that accurately forecasts demand, delivers precision pricing and the flexibility to adjust market share growth.
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Silicus was approached for providing solutions to extract the data from its customer’s database for predictive analysis.
Silicus used its expertise and analyzed that there were two approaches for this problem:
- Direct Access to customers Database
- Indirect Access to customers Database
For the first approach, Web application was installed at the client side, SSIS packages were fired which extracted huge volumes of customer’s data and populated data back to the destination databases at the client location.
For the second approach, Web Service was installed at customers side, which was accessed through a VPN connection which would call the Web Service and this in turn will return the huge volumes of customer’s data to a FTP servers. Then SSIS packages are fired to extract data from FTP servers and populate it to the destination databases at the client side.
DatabaseSQL Server 2012
3rd Party InterfacesSQL Server Integration Services (SSIS) PACKAGE
IDEVisual Studio 2013
Large Volumes of Data Transfer
Large volumes of data with different data formats can be transferred from the source database to the destination database over the FTP server in a very less time.
The data are extracted using the incremental data extraction strategy, where the data extracted for first time is of huge volume, but reduces for further increments as it does not include duplicate data.
The client was able to mathematically analysis the data determine how customers will respond to different prices for its products and services through different channels. It is also used to determine the prices that the company determines will best meet its objectives such as maximizing operating profit.
The Client is able to forecast demand at different prices for hospitality, airlines and multifamily housing industries, thereby providing one of the finest revenue management systems to its customers.