Leverage the Benefits that Data Warehouse Offers – Build an Enterprise Data Warehouse
Overview & Challenge
The Client is a telecommunication provider offering television, internet, and telephone services. They have been operating on the market for more than 30 years. Having a fast and reliable connection, and outstanding personal service have led them to be the second-largest fiber optic provider in their country of operating. Their mission is to ensure that the latest technology developments are accessible to everyone and the services they provide are of top-notch quality.
Establishing efficient mechanisms to extract data from various and heterogeneous enterprise data sources (Oracle, MySQL, SQL Server), perform complex data transformations and calculations, and load the data into Amazon Redshift as a central enterprise data warehouse. BI tools should also use the warehouse to build a wide spectrum of reports that meet the requirements of a diverse set of business users.
The solution quickly ingests, prepares, and delivers big data in Amazon Redshift, consisting of different submodules to more effectively manage the entire lifecycle. The solution is composed of optimized ETL pipelines implemented by using SnapLogic. The common functionalities include complex query logic applicable for all integrated data types from heterogeneous systems, consuming data warehouse dimensional/fact model with highly optimized bulk operations applied.
Data from multiple sources is integrated into the warehouse providing a single view of business entities like customers, products, employees, locations and other assets.
Unified data access increases the value of data through efficient visualization.
Real-time information delivery enables a number of high-value business practices and makes data available for dashboards and other types of operational or management reports, represented using a different set of BI tools.
Data synchronization processes tend to integrate data frequently depending on the needs thus increasing data currency.
Increased productivity by 40% by allowing employees to focus their time on analysis and understanding the data instead of compiling and constructing information.
Ability to automate hourly, daily, weekly reports and keep entities updated based on their performance against key metrics and KPIs.
Gained improvement of precisely calculated time savings in thousands of hours per month.
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