Top 5 Reasons To Modernize Legacy Applications In The Cloud
Today it would never occur to anyone to manually create complex blueprints for a nuclear power plant project. Few people give up comfortable laptops in favor of bulky old-style system units or use Nokia push-button instead of a smartphone.
In business, the situation is the same: those who have managed to master new things become leaders. Outdated equipment and obsolete data warehouses hinder the development of the company. Why do many persistently continue to use legacy modernization services and what does this threaten in the near future?
5 reasons to replace outdated data warehouses with new ones
Outdated storage models do not meet modern needs when you have to work with terabytes and petabytes of information. Business processes begin to slow down due to slow data loading, reporting, analytics and other tasks that are performed with delay, rather than in real time.
The fault here is outdated, low-bandwidth interfaces. Although SCSI is reliable and proven for decades, it is gradually being replaced by faster alternative interfaces like:
The types of storage systems are also changing: if earlier they were DAS, today they are faster than NAS and SAN based on Fiber Channel and Ethernet.
Storage hard drives also do not compete with fast SSDs, but they have a right to exist in systems with cold and hot data. Slow cold data can be stored on HDD, while hot data can be stored on fast SSDs, in which the transfer speed is very close to the bandwidth of the latest versions of SAS and SATA interfaces.
Google Cloud notes that in companies with old-style storage, IT departments spend only 15% of their time servicing database queries, and everything else on technical work. Companies continue to hire specialists to administer obsolete storage facilities, spend money on their repair and modernization, but these investments do not match the effect they get on the way out.
Actian surveyed more than 300 IT professionals who make strategic decisions and found that 94% of them understand the importance of information systems that guarantee real-time data processing. But only 58% of respondents work with such systems.
Legacy repositories do not have predictive analytics solutions. Their performance is just enough for the application systems that access the database to prepare the mandatory daily reports for the finance and sales departments.
Companies with outdated storage are depriving their business of additional opportunities. With new storage tools and top python company you can identify hidden patterns in your data to cut costs / maximize profits. The system could:
· form personal offers to customers;
· suggest ways to reduce marketing and logistics costs;
· optimize resources.
In our realities, storages are often divided into many local areas in different departments. This complicates the preparation of consolidated financial statements, leads to inconsistent data in the analysis and does not allow cross-analysis. A single repository, in which data is transformed to meet the requirements of all departments, will help to solve the problem.
Legacy datastores are typically 95-100% full, necessitating cloud expansion. However, the hardware does not allow to download streaming and batch data in real time, to support concurrent requests. This makes it difficult to scale and work with cloud services.