A data warehouse is essential to a company’s business intelligence strategy. It’s the core of all enterprise data. The data warehouse organizes, stores, analyzes, and manages the enterprise’s data for better business decisions. Optimizing your data warehouse involves maximizing the speed of the database queries, improving query efficiency, and reducing the response time. Here are five hacks to help you optimize your data warehouse.
1. Selection of the Right Platform
The fastest way to optimize a data warehouse is by choosing the right platform. To be successful, you need to compare different platforms and choose one that will support your business requirements of data storing, analysis, and retrieval. For example, you can compare snowflake vs Hadoop based on the available memory space, disk speed, and query speeds. Moreover, you can compare their API and pricing as well. Also, to choose the right platform, it would be best to predict how various users will use the data warehouse.
2. Use the Right Tool for the Job
Different tools are available, and you could use them to perform different operations. For example, an ETL tool is used to manipulate, transform and transfer data into the data warehouse. These tools can be used again to normalize the resulting tables to perform better querying. Similarly, there are different data sources like SQL, NoSQL, and NewSQL databases.
You could use them correctly to interface the external database with your warehouse database. Additionally, you can use data discovery tools and wizards to perform many operations like profiling the database, identifying issues, and setting up database parameters. The right tool can help you understand different database operations, such as how to use database triggers and manage stale records for your business.
3. Segmenting Data
Segmentation is a method of grouping your data into different groups to enable faster querying. It is also used for storing, analyzing, and sharing data. After segmentation, you need to create different tables for each group. For example, if you want to group the customers with similar needs and wants into one table while grouping clients with unrelated details into a separate table, you have achieved segmentation.
It would be best if you also created separate tables for each group. In addition, you need to ensure that the table is stored in its partition or a file system. Furthermore, you should also ensure that the files are kept away from other unwanted data.
4. Data Compression
Data compression helps maintain your data’s integrity while reducing the number of disks required for storage. Data compression enables high performance with efficient usage of disk space. This is because it provides a decent reduction in the size of your files while keeping them intact. It also helps to optimize your data warehouse by reducing the response time and improving query speed.
Data compression works well when the data to be compressed is static or unchanging and has fewer patterns. In addition, you should ensure that you compress only the selected tables and not all the tables in your data warehouse. Also, you should remove the compressed files when they are no longer used for storage because it may lead to security problems.
5. Data Scrubbing
Data scrubbing involves eliminating redundant data that does not benefit the system. For example, if you have a variety of similar products in your warehouse, many of them are probably associated with the same product numbers and codes. You can remove these duplications by using data scrubbing techniques.
In the future, you can reload these codes without sacrificing their quality of information. Removing distinct differences in your data warehouse will make it easier to query and use information properly. Additionally, you can use data scrubbing to remove inconsistent data that may affect the accuracy of your reports.
These five tips can help you implement a process of optimization in your data warehouse. If you follow these hacks, you can improve the overall performance of your data warehouse and make it highly efficient. Make sure to consider all aspects such as memory space, disk speed, and query speeds before choosing the right platform. You should also know how frequently the data warehouse is queried because it could determine how fast it needs to be accessed.
