No matter how smooth the plan may be in theory, practice will certainly make adjustments. Because each real case has its own characteristics, which in the general case cannot be taken into account. Let's see how the world's leading brands have adapted to their needs a well-known way of storing information — data warehousing. If you think this is your case, then arrange a call.
We developed an ETL solution for a manufacturing company that combined all required data sources and made it possible to analyze information and identify bottlenecks of the process.
DATAFOREST has the best data engineering expertise we have seen on the market in recent years.
This is what data warehousing specialists do. To focus on the best performance, it makes sense to consider how high-quality custom assemblies came out of this constructor.
A data warehousing is a digital storage system that integrates and reconciles large amounts of data from different sources. It helps companies turn data into valuable information and make informed decisions based on it. Data warehousing combines current and historical data and acts as a single source of reliable information for business.
After raw data mining (extract, transform, load) info enters the warehouse from operating systems, such as an enterprise data resource planning system or a customer relationship management system. Sources also include databases, partner operational systems, IoT devices, weather apps, and social media. Infrastructure can be on-premises or cloud-based, with the latter option predominating in recent times.
Data warehousing is necessary not only for storing information, but also for processing structured and unstructured data: video, photos, sensor indicators. Some data warehousing options use built-in analytics and in-memory database data technology (info is stored in RAM rather than on a hard drive). This is necessary to access reliable data in real time.
After data is sorted, it is sent to data marts for further analysis by BI or data science.
Consideration of known options for data warehousing is necessary, first of all, in order not to keep making the same mistakes. Based on a working solution, you can improve your own performance. If you want to always be on the cutting edge of technology, book a call.
Blindly repeating other people's decisions is also impossible. Your case is unique and probably requires a custom approach. At best, well-known storage solutions can be taken as a basis. You can do it yourself, or you can contact DATAFOREST specialists for professional services. We have a positive experience and positive customer stories of data warehousing creating and operating.
Amazon is one of the world's largest and most successful companies with a diversified business: cloud computing, digital content, and more. As a company that generates vast amounts of data (including data warehousing services), Amazon needs to manage and analyze its data effectively.
Amazon's data warehousing needs are driven by the company's vast and diverse data sources, which require sophisticated tools and technologies to manage and analyze effectively.
1. One of the main drivers of Amazon's business is its e-commerce platform, which allows customers to purchase a wide range of products through its website and mobile apps. Amazon's data warehousing needs in this area are focused on collecting, storing, and analyzing data related to customer behavior, purchase history, and other metrics. This data is used to optimize Amazon's product recommendations engine, personalize the shopping experience for individual customers, and identify growth strategies.
2. Amazon's other primary business unit is Amazon Web Services (AWS), which offers cloud computing managed services to businesses and individuals. AWS generates significant amounts of data from its cloud data infrastructure, including customer usage and performance data. To manage and analyze this modern data effectively, Amazon relies on data warehousing technologies like Amazon Redshift, which enables AWS to provide real-time analytics and insights to its customers.
3. Beyond these core businesses, Amazon also has significant data warehousing needs in digital content (e.g., video, music, and books). Amazon's advertising business relies on data analysis to identify key demographics and target ads more effectively to specific audiences.
By investing in data warehousing and analytics capabilities, Amazon through digital transformation can maintain its competitive edge and continue to grow and innovate in the years to come.
