Oracle has been a leader in database management systems for over 30 years and has made the Data Warehouse design and implementation an integral part of their product line. The Data Warehouse is a web-based framework that provides data storage, data analysis, data mining and the ability to manage the data. The data warehouse is designed to support fast deployment and minimize the complexity of analytics. Oracle Enterprise Database11g provides the foundation for building a data warehouse. Oracle Enterprise Manager gives users the power to build and manage the data warehouse. This concept is called Advanced Analytics or Data Analytics Implementation.
Companies such as call centre providers, e-commerce stores, BPO companies and others have used the data warehousing concept to provide solutions that can better track the performance, user experience and increase productivity. Advanced Analytics enables organizations to better use their data. By utilizing the cloud infrastructure and application development services, data integration and analytical processing become faster and more efficient. This concept is usually implemented when data warehousing is combined with data integration, historical data integration, reporting and other business intelligence tools. These technologies can be used to provide real-time insights and enable users to make informed decisions.
Amazon Web Services (AWS) has made the Data Warehouse design and implementation easier and more effective. It is especially useful for BPO firms that aim at making their data warehouse as elastic as possible. AWS will provide many tools for organizations such as its ECG appliance marketplace, S3, IaaS and PaaS cloud computing platforms, the Data Migration Service and Data Quality Management. This helps organizations to take full advantage of their AWS resources and improve data warehousing efficiencies. AWS can also integrate with other data warehouse tools such as Kinesis and Lucidchart.
Data visualizations are a key to success in the realm of data warehousing and business intelligence. Historical data visualization is essential to the understanding of market trends, business metrics, consumer behaviour and other important information. Data visualizations can be applied not only to the physical data warehouse but also to business intelligence applications such as business intelligence apps or web analytics.
Enterprises that choose to implement an advanced data warehouse in the cloud infrastructure find it easy to collect, manage and analyze enterprise-grade data. They also find it easy to build an app via an easy-to-use interface. The key is in how you manage and connect the data warehouse to your business intelligence platform, specifically your digital dashboards. It is also important to manage the data warehouse efficiently to realize maximum benefits and avoid bottlenecks.
Automation makes it easier to make business decisions and achieve goals. Organizations that rely on internal workers and manual processes are hindered by the absence of critical data warehouse interactions. Business intelligence apps can help you achieve business goals by providing insights that help you make smart decisions. Big data analytics helps you make business decisions based on real-time historical data and future trends and behaviours.
Cloud technology is highly scalable and elastic. It can be used for running any type of data-intensive application. This means that you can easily increase or decrease the size of a data warehouse without having to incur significant additional costs. Cloud businesses are increasingly adopting mobile devices for data collection and analysis. These devices are inherently more mobile than on-premises systems due to the devices' mobility.
Data visualization tools developed for AWS customers prove to be an ideal choice for organizations that are looking to improve their data warehouse management. Data visualization tools powered by AWS's state of the art Eluent and Spot services enable users to map data sets from any source to any format and create custom reports and dashboards. Eluent and Spot also support multi-user data visualization sessions that span multiple locations and time zones. Companies that want to take their business to the next level should consider investing in cloud infrastructure for managing their business intelligence workloads.
