Today it seems that everything is moving to the cloud. Even data warehouses that were thought would never leave the on-premise data centers migrate to the cloud. No weird considering the benefits of today’s cloud technologies. In this blog post, we will guide you through what a cloud is a data warehouse, the advantages, and challenges of data warehousing in the cloud.
What is Data Warehouse and Its Benefits for the Cloud
Data warehouse is a type of data management system designed to enable support of business intelligence activities, especially data analytics. Data warehouses are designed solely for request execution and data analysis. They often contain large volumes of historical data – usually obtained from vast data sources such as application log files and transaction applications. Because data warehouses allow for secure storage of large data volumes, there are several benefits they carry for their users.
Increased Collaboration: Cloud data is available anywhere there is an internet connection. This promotes seamless communication and data sharing for remote teams, resulting in increased insight and better data-driven decisions.
The Ease of Scalability: On-premises data storage often requires huge upfront financial investments and power capacity. With cloud storage, businesses can easily scale up and down their resources without long-term commitments.
Reduced Costs: Companies can often lower the cost of ownership with cloud data warehouses because there are no expensive upfront investments in hardware and infrastructure. This also means companies don’t have to make a commitment to a fixed capacity — they only pay for what they use.
Challenges of Data Warehousing in the Cloud
Let’s take a closer look at the challenges organizations may face as they set up data warehouse systems for operations.
Adjusting to Non-Tech Users
Non-tech users may sometimes find it complex to use “traditional” data warehouses. Even though everyone can master data analysis on a basic level to request data from any source and know how to use it in a workflow. The reality is quite different, though.
Non-tech users often need to interact with company data which may get inefficient if you use a “traditional” data warehouse – submitting a request to a data team, waiting for a response, and using the data. This process might work in small teams but for larger ones, it’s not the smartest method. Data teams may get oversaturated with data which often leads to frustration and bottlenecks.
Data Quality
Maintaining the quality of data may get challenging in the traditional data warehouse where manual errors and missed updates may result in damaged or outdated data. This inevitably leads to inaccurate data processing and impacts business decisions. Since companies tend to implement digital initiatives into their workflow, they often face the problem of unintended data silos. This happens when departments heavily rely on cloud tools and are likely to be responsible for purchasing and developing technologies for their use.
Data Management and Optimization
As more information gets added to the data warehouse, data management systems find it harder to structure, find and analyze it which slows down the ETL (extract, transform, load) process. In addition, management systems may struggle to qualify the data for advanced analytics. As the data volume increases, the performance of the data warehouse decreases, which inevitably leads to reduced speed and efficiency.
To sum up, data warehousing in the cloud carries a range of benefits that come along with a few challenges to face. This is an efficient, scalable, and cost-saving method for data storage that, however, may question the quality of data stored and ease of use by non-tech teams.
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