The traditional form of storing digital data has been disk storage. However, with the rapid advancements in technology, there is a growing need for data storage to evolve and keep up with the changing times. Microsoft SQL Server has undergone a significant overhaul to meet the increasing demands of data storage, and this is where data warehousing comes into play.

For many online applications, there is a need to access not only small amounts of information from disk storage but also large sets of data. SQL Server allows for the sequential access of these data sets, optimizing computer performance. This proprietary technology makes SQL Server the go-to system for fulfilling these computing needs.

SQL Server has also addressed the challenge of transitioning from “data marts” to data warehouses. As companies grow, their digital storage needs change and expand. Previously, transferring a system over to SQL Server meant potentially losing old data during the transfer, leading to data loss and server problems. However, the new versions of SQL Server have built-in systems that facilitate the transfer to larger data storage without sacrificing data integrity.

The costs of data storage and data warehousing are major concerns for both small businesses and corporations. It is a known rule of thumb that the larger the main server, the more expensive it becomes. SQL Server tackles this problem by allowing data warehousing to be run on multiple processors, making it much more cost-effective than relying on a single main data warehousing server. SQL Server utilizes the “hub-and-spoke” system, which enables data warehousing to be distributed across multiple systems without any data loss.

One of the key questions is how SQL Server can store such vast amounts of data. Like any storage system, some data is compressed before being stored. However, other systems may undergo lengthy processes to retrieve this compressed data due to updates and potential loss of information. SQL Server bypasses this updating process, allowing for quick and easy access as well as compression.

The issue of compressing excessive amounts of data is also resolved through parallel processing. In this system, multiple processors are enlisted to assist in storing the data. SQL Server has the technology to divide the data appropriately and access it efficiently upon request. Instead of slowing down a single server, the data can be divided and handled more easily.

SQL Server leverages the computer’s ability to calculate probabilities much faster than a human. It utilizes “Probability of Access” technology to determine which data is “hot” and likely to be accessed frequently, which is moderate, and which is cold with a low probability of access. With these designations, SQL Server can store hot data in high-performance storage for quick retrieval, while cold data is stored elsewhere, freeing up processors to work more efficiently.

SQL Server not only optimizes the storage of static data or individual points of information but also provides a technology to store streaming data. Streaming data involves recording multiple events over a period of time, such as temperature measurements taken thousands of times per minute. Storing this type of data would overwhelm other servers, but SQL Server has developed efficient technology to handle it without slowing down processors. Additionally, the data remains easily accessible due to the data warehousing systems discussed earlier.

Streaming data poses challenges for most servers due to storage limitations. It overwhelms servers, making it difficult to store and retrieve such large amounts of data efficiently, ultimately bogging down the system. While other companies have attempted to create programs for accessing streaming data, it often comes at the cost of processor speed. The usual process involves storing streaming data as historical data and then retrieving it as static data, which slows down all the processors. SQL Server, on the other hand, has created a system that allows for the analysis of streaming data by presenting it in an interactive sector.

In summary, SQL Server is at the forefront of future data warehousing, known as DW 2.0. It can store large amounts of data at a low cost and with maximum efficiency. Microsoft has taken into account the need for multiple processors and an easy way to transfer old data into this new system. The technology behind SQL Server is sure to make data access much more efficient.