The data warehouse is an essential technology for the development of business intelligence solutions. In this blog, we are going to highlight how you can build and automate the whole Data Warehouse Migration process to the cloud in a step-by-step format.
A Data Warehouse is a unified and centralized data warehouse system that allows easy access to stored information.
DW allows for fast response and storage of large amounts of data, mainly due to its multi-dimensional architecture-based modeling. However, to set up this robust data warehouse, we need to follow a few steps that will help us to set it up correctly.
Let’s look at the seven steps to creating a data warehouse:
1. Needs Analysis
First, we need to create an overview of all the information that the user wants. At this first point, we cross-check the dimensions and facts required to achieve the managers’ goals. At this first point, we are concerned with what the data warehouse will contain, not how, so we should not be concerned with the actual existence of the data but with what we want.
2. Data Mapping
In this step, we map the data by identifying the source and its path. This is where we check the feasibility of what we wanted in the first step, i.e., whether there is data that meets the desired requirements.
3. Designing The Storage Area
After mapping, we create a storage area structure, which is the data transfer area. In this area, data is replicated and separated from operational systems (OLTP (online transactional processing)) and prepared appropriately in event and dimension tables for future workloads.
4. Construction Of Dimensions
In this step, the structure of the dimensions part of DW is created. We also define the data history in the dimensions.
5. Create Events
In this step (after creating the dimensions), we design the event structures. Here we evaluate and define the details of the information to be stored in each event. We also assess the usage and storage requirements to be met.
6. Define The Overall Load Process
After completing the previous steps, we need to configure the engine so that everything can be automatically and seamlessly uploaded, updated, and processed. Therefore, the need for the general process of loading is the “brain” of the Data Warehouse.
7. Create Metadata
Finally, we need to create all the metadata documentation, including the creation process and the data dictionary. Metadata is an essential support for knowledge management.
Remember that a Data Mart is the division of a data warehouse into subsets of information organized by specific subjects. Therefore, all these steps, except “needs assessment” (which should preferably be performed once), should be repeated with each new Data Mart created.
It is essential to follow the sequence of these steps, as they are interdependent. In other words, the next step can only start after the previous step has been completed.
A DW construction project’s success is almost guaranteed if all of these activities are given due attention. In this way, we will effectively have a data warehouse that will store the information to assist the organization in decision-making.
How Can Automation Simplify Data Warehouse Migration to the Cloud?
Moving your data warehouse to the cloud is an important step for companies moving parts of their infrastructure to the cloud. It is usually complex and costly. Automation can simplify the process.
The long-term goal of many companies in their digital transformation is to use cloud technologies. However, a closer look at cloud usage data shows that many companies are still a long way from moving part of their infrastructure to the cloud.
Rather than addressing the long-term goal of the cloud, these companies often rely on temporary solutions or shortcuts. Rather than migrating important parts of the infrastructure first, they choose the easiest parts to migrate.
Should The Data Warehouse Be Migrated To The Cloud First?
When it comes to deciding which infrastructure elements are worth migrating to the cloud, the data warehouse rarely tops the list.
However, the business case for adopting a cloud data warehouse strategy is already very compelling. Most companies can gain an advantage over their competitors by leveraging it well and extracting value from it.
In principle, this is much easier if you have a flexible and easily scalable on-premises data warehouse platform. Therefore, it would be desirable for many companies to move data storage to the cloud. However, many companies are putting this project on hold because the task itself is not straightforward.
Moving Traditional Data Warehousing To The Cloud Is Cumbersome
Traditionally, the migration of an entire data warehouse has been entrusted to an entire development team with the time and fault tolerance to move the data warehouse from a fixed infrastructure to a cloud structure.
Such a lengthy, complex, and costly process usually involves the manual migration of various parts of the data infrastructure to the cloud, which is eventually transformed into a hybrid environment.
This process is sometimes frustrating for decision-makers and creates a mental barrier to choosing cloud storage. Many companies recognize the value of moving to cloud storage, but obstacles hamper them.
Automation Can Simplify The Transition From Data Warehousing To The Cloud
The manual journey to the cloud typically consists of repetitive and time-consuming tasks.
Developers must create their solutions for each piece of infrastructure, which means long hours, lengthy implementation, and a general lack of standardization. Automation can significantly reduce these consequences by designing migration processes in a standardized way.
Automation can, therefore, “simplify” the migration process, reduce the cost of the migration project, and help avoid migration errors.
All you need is a data warehousing consulting firm that can automate data processing operations. The migration project will gradually migrate these processes with each automated process in the future.
This kills two birds with one stone: the company will now use automated processes that require almost no manual intervention, while the team will simply migrate its data warehouse to the cloud step by step.
Wrap Up
There is no single migration plan that covers all use cases. We recommend consulting your cloud data warehouse service provider, explaining what your environment is like, and asking them for detailed guidance rather than trying to automate the migration process to the cloud yourself.
