Organizations have many reasons to adopt new technology because of their competitive environment. These include speed, flexibility, and overall performance. It’s time to understand the reasons behind database migration. Let’s take a look at these.If you are looking for a professional organization that takes care of Database Management services in your company, You can indeed contact sureworks. Sureworks is one of the Database Management services providers in India
To save money:
Old databases can lead to overhead costs for the company. Installing other systems or applications to run quickly. They will transfer their database to a platform that best serves their purpose. This will allow them to save on both infrastructure and the manpower and expertise required to support it.
Evernote has, for example, maintained its own servers since inception. They noticed how the infrastructure was limiting their operations over time. It was difficult to scale up, it was time-consuming and costly to maintain. They desired more flexibility and the ability to improve their business.
Upgrade to new technology
This is a common reason for migrating. The company would move from an old or legacy system to one that meets current data requirements.
Adopting efficient storage methods is essential in this age of big data. A company may decide to switch from a legacy SQL database into a data lake, or another flexible system.
To Reduce Redundancy
Companies must consider data migration in order to transfer all company data to one place. This will reduce redundant data. All divisions can access the same data by storing it in one location.
This can happen after an acquisition, when systems must be combined. This can also occur when multiple systems are not interconnected in a company.
Different departments may have their own databases, and they don’t sync. When you have incompatible databases, it can be difficult to get insights from your data.
According to the research, databases are the most susceptible to cyberattacks. Because they are easy to access through networks, this is why they are so vulnerable. Many organizations don’t update their databases as often as they upgrade other systems. Hackerscan then use this gap to steal or reveal information.
Challenges in database migration
Database migration is a complex task that can present many challenges. While many of us are aware of the difficulties involved, very few may know how to overcome them. These are some of the most common problems:
Identification of databases stored at different locations
Every company accumulates data over time. There is a chance that data may be stored in multiple databases at different levels within your organization, especially if the company has been operating for some time. The most difficult part of migrating databases is identifying where they are located in your environment. It is also difficult to determine how to normalize or convert the schemas after identification.
Data analysis at the earliest
Information can sometimes be hidden due to computer system limitations. This is because the fields that can hold all data aren’t available or users might not know the purpose of these fields.
Therefore, information that is transferred during the migration may be incomplete, incorrect, or outdated. This can often be discovered late at night, even after the project is completed. This could be because the outcome may not have enough resources or time to correct these data.
This is one of the Database Migration Best Practices. It allows you to do thorough data analysis as soon as possible. This can help you uncover these hidden errors.
Inadequacy of integrated process
Data migration is a common process that involves many people and multiple technologies. Spreadsheets are used to record data. These spreadsheets are often prone to human error and can be difficult to translate for data analysis or data transformation.
Using different technologies can sometimes cause problems in data transfer and design. This happens between the development, testing, implementation, and analysis phases. Sometimes things can get lost in translation, which ultimately increases costs and wastes time.
Data cleaning and coding
Databases may contain data in various formats, which could have been obtained from different sources. Data from different sources must be cleaned, normalized and transformed. You should do this in a way that makes it possible to combine data from different sources.
You might have to adjust your data model in these cases to accommodate a mixture of structured and unstructured data or discrepancies that may occur when moving between databases.
Failure to evaluate final results promptly
This is only possible during the testing phase. At the end of development and design, the users will see the data that will be loaded into their new system. The incompatibility between the data in the new system and the existing data is the most serious outcome.
Although an organization can work without a solution, it isn’t the best practice. To reduce rework, agile and early testing phases such as Test-driven Development are possible. You can also involve your users in the development of test cases, as they will be able to see the prototypes of data output.
Collaboration is lacking
Data migration is a process that involves many people using different technologies. Sometimes, it might be possible to have a mixture of employees and external engineers work on data migration. Sometimes, some of these people might not be at the same place. The efficiency of working in different places and silos can impact overall efficiency, lead to more data silos and cause misinterpretations. It can be hard to handle situations that go wrong when you work together.
Data analysis is important. Get help from data experts.
Data migration projects are difficult and risky. It is better to have data experts involved in the migration project from the beginning. This will allow them to make sense of different data sources and guide data transformations that are appropriate for the target audience.
Although it makes sense to hire experts, this is often used to manage and implement data migration. These experts are often hidden within businesses and don’t usually appear until
the end of the day. Access to data is often restricted to those who have it. Those without access are sometimes unable to access it because it isn’t ready.