Reflect on Future Trends in Data Warehousing Management Essay

Future Trends in Data Warehousing: Cloud Data Warehousing
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Future Trends in Data Warehousing: Cloud Data Warehousing
Data warehousing refers to a method that is used to collect and manage data from a variety of sources to provide essential business insights. It is the electronic storage of a significant volume of information by an organization (Devlin, 2018). It is an important aspect of business intelligence which employs analytical techniques on the data of an organization. There are quite a few future trends in data warehousing. This paper discusses one particular trend in data warehousing that merits further research. The impact of the trend and why the trend exists are also explained. The selected trend is cloud-based data warehousing.
Users doing data warehousing mainly in the cloud
Today, there is an explosion of data all over the globe. As such, the number of systems for capturing this data has also increased. Scalable systems for storing these varied data sets have also emerged. One specific trend that merits more research is users doing data warehousing largely in the cloud. In today’s business environment, enterprise data warehouses are very relevant. With an increase in new data pouring in at a more and more rapid rate, however, the conventional data warehouse is not up to the task (Khan, 2017). For companies to be able to sustain their competitive advantage, they have to take action now aimed at modernizing the conventional data warehouse. One way of modernizing their traditional on-premise data warehouses is doing data warehouse principally in the cloud. Examples of cloud data warehouse providers include Amazon S3, Microsoft Azure, Amazon Redshift, Amazon Glacier, Snowflake, and HDInsight among others.
Figure 1: Customers are gradually moving data to the cloud (Bertolucci, 2017)


As illustrated in Figure 1 above, Cloud is increasingly becoming more important than ever before. Clients are gradually transferring their data to the cloud. For example, some customers are shifting their data from Teradata to Cloud such as Azure Data Warehouse, and from NoSQL and operational systems to Cloud such as Amazon Redshift or Snowflake (Bertolucci, 2017). Recently, Wikibon has carried out a survey aimed at determining the Future of Cloud and found out that nearly sixty-percent of business organizations in the United States is investing in the Cloud for analytics (Bertolucci, 2017). This shows that companies are increasingly looking to move their data warehouses to the Cloud, which will enable them to save costs and extend their on-premises ecosystem.
The Cloud is ever more becoming the ideal approach for obtaining data warehousing capabilities. According to Collupy (2017), cloud-based data warehouses are a growingly important aspect of the application infrastructures of many organizations. Users are looking to manage their data warehouses using licensed software on commodity hardware within their data centers. Furthermore, more businesses are starting to deploy cloud data warehouses as convergence platforms for various operational data applications (Collupy, 2017). It is important to mention that cloud data warehouses support data acquisition, processing, storage, and aggregation in various formats and from a variety of sources. Also, cloud data warehouses support optimized deployments as transactional computing platforms, analytic data marts, business-intelligence back-ends, and multi-structured information refineries (Heaven, 2018).
Impact of the trend
The impact of this trend is that it would result in the modernizing of data warehouses. As an enterprise hub for various use cases such as data governance, advanced analytics, and operational decision support, the data warehouse would be able to perform its job more cost-effectively, more scalable, and faster within a cloud environment (Bass, 2016). A cloud-based data warehouse is essentially a central repository of data that makes use of the cloud infrastructure. In the cloud, Khan (2017) pointed out that a network of computing resources and remote servers are utilized in providing a data warehouse, rather than local servers hosted on-premise. A data warehouse is of great importance for the success of data analytics efforts. Some firms offer cloud-based data warehouse services, including Azure SQL Data Warehouse, Google BigQuery, Amazon Redshift, and Snowflake.
An example of the trend in action is customers using Amazon Redshift, which is a scalable and quick cloud-based data warehouse which makes it cost-effective and easy for businesses to analyze all their data throughout their data warehouse and data lake. It is a petabyte-scale, fully managed data warehouse service in the cloud (Amazon, 2018). Amazon Redshift serves clients in va...