Moving from multiple data sources to a data warehouse solution with a single source of truth is a step in the right direction.
However, data warehouse requirements vary from organization to organization, and service providers sometimes assume that users are already knowledgeable in this area. So, before you start looking for answers, developing a data warehouse strategy that clearly articulates your needs and goals is essential.
How To Proceed?
On this page, you will find a series of questions to help you develop a sound data warehouse strategy.
1. Will The Investment in A Data Warehouse Pay Off?
Depending on the upfront costs, which vary from vendor to vendor, the ROI can begin when the data hits the data warehouse for processing and storage. Once you have the correct data, you can focus on making smart business decisions, increasing revenue, and reducing costs.
To learn more about where your money is going, take a closer look at the cost and performance of cloud data storage.
2. Which Should You Choose – An On-Premises or Cloud Storage Solution?
Data storage was costly in the past due to on-premises infrastructure and other fixed costs. However, the cost of infrastructure, setup, and maintenance from storage-as-a-service (DWaaS) providers is much more affordable.
Whether you choose cloud or on-premises storage, you get the same storage redundancy and security level.
But each option has its pros and cons.
For example, a cloud-based solution offers faster and cheaper scalability.
On the other hand, on-premises solutions offer complete control and freedom of choice regarding technology stack characteristics. Depending on the location of the on-premises infrastructure, network latency issues can also be addressed.
When determining your storage strategy, you must decide what is more important to you and whether an on-premises or cloud-based solution will meet your needs.
3. What Do Data Warehouses Offer Beyond Just Storage?
The difference between a database and a data warehouse.
If a data warehouse were simply a solution for storing data, on-premises infrastructure would be more competitive. On the other hand, data warehouses allow for sophisticated analytics and ETL calculations, as well as reports generated from complex data warehouse search processes that drive business decisions.
- Data warehouses offer the following benefits.
- Discovering patterns or trends in data warehousing from different sources.
- Identifying correlations to improve decision-making.
- Uncovering patterns and patterns in data helps identify patterns and opportunities for analysis.
- A single source of truth for your organization’s structured and unstructured data.
With a data warehouse, these and other capabilities become readily available. For more information on these two topics, see our guide to data warehouses.
4. Can Data Warehouse Technology Automatically Scale Incoming Data?
The best data warehouses scale themselves.
Automatic scalability is necessary for both natural data growth and short-term workload and storage capacity increases.
But beyond simple scalability, you should look for a data warehouse partner that automates data entry, processing, and visualization of analytical insights.
This is essentially a managed data warehouse solution with significant cost savings.
5. Who Owns the Data Warehouse Strategy?
Ownership of the data warehouse strategy depends on your chosen solution.
If you choose a self-managed data warehouse solution, you will need engineers, data analysts, data scientists, and IT managers.
Each of these tasks is critical to the performance of the data warehouse.
- The professionals who build the infrastructure from the ground up and maintain it throughout the life of the data warehouse are managers from various IT disciplines. Think of these teams as managing the physical components of your data warehouse.
- Engineers and data scientists should have experience and expertise appropriate to the data warehouse platform. For example, engineers must be GCP certified if they’ve chosen Google data warehouse resources. The same rules apply to Redshift, Azure, AWS, and other providers.
- Finally, data analysts translate ETL requirements into actual data processes.
Using a managed data warehouse solution does not eliminate the impact of requirements on these teams. On the contrary, automation and consistent management in the background produce the same, if not better, results than a fully active workforce.
6. How Many Data Sources Can We Integrate into Our Data Warehouse Solution?
Data warehouse solutions typically offer an extensive list of data integration options. These range from specialized data warehouse options to standard databases.
The specific solution determines the exact number of sources that can be included. In general, however, here are some of the data sources that can be integrated into a data warehouse system:
- Websites and social media
- ERP and financial tools
- Social media and financial services, financial services, social media, and financial services, e.g., financial services, financial institutions, social media, etc.
- NoSQL, MongoDB, etc.: unstructured databases
- List data (CSV, Google Sheets, etc.).
Unique authorizations and APIs allow for high-performance and low-maintenance data bridging.
You can send data to your repository if a database has an API.
7. Even If We Don’t Have a Central Database, Can We Start with A Data Warehouse?
A data warehouse is the ideal approach to collecting data from all sources in one place. Regardless of the source or format of the data, a data warehouse allows you to combine all of your organization’s data into a single source of truth.
Once entered into the data warehouse, the data will be available in a predictable format and have specific properties. This makes it much easier to analyze the data further or combine other data sources.
8. How To Implement a Data Warehouse Solution?
The optimal use of a data warehouse system depends on familiarity with the system.
Most data warehouse vendors provide product documentation and training materials. This will allow you to utilize the services you need at your own pace.
Customized demonstrations and familiarization events can also be arranged.
9. Does The Formal Data Warehouse Strategy Document Need to Be Revised?
Probably not.
Mapping the development of the data warehouse is of paramount importance. Answering the questions we’ve raised here is a good starting point for defining your approach.
However, an even more critical first step toward success is to talk to professionals about how best to implement a data warehouse development strategy.
The best way to develop a data warehouse for your organization is through face-to-face discussion and real-world data presentation.
Begin the journey to a data warehouse
Whether you choose an on-premises or a cloud-based data warehouse, this article will outline what to expect from a data warehouse solution and how to start developing your data warehouse strategy and solution.
Testing a data warehouse system will yield immediate results once the data is entered.
By answering the questions above, you should better understand what you need from a data warehouse solution. Of course, you may have other questions as you develop your data warehouse plan.
Contact the professional data warehouse experts at Existbi and discuss with them to help you start your data warehousing journey.
