Data migration is a necessity for any company that is looking to either update their data storage software, or that is headed into a period of business acquisitions or mergers. For those who are looking into transferring their data in a successful format, Udemy offers a wide selection of courses such as their Basics of Enterprise Data Conversion tutorial, which could help you take this daunting, complicated and execute it with relative ease.
As most companies today are beginning to find their legacy systems as outdated, the need for data migration into newer, more efficient systems has increased. There are even specific Udemy courses that can help you learn how to migrate your data from legacy systems into newer storage software. However, since not all companies use a legacy system, and not all data is the same, the process of data migration and developing an effective strategy is broader than a simple change in your data storage software.
Understanding the Basics of Data Migration
Data migration at its core is simply the transfer of data between storage types, formats, or computer systems, and is critical for further implementation, consolidation, or upgrades within a business. Since there are such goals attached to migrating one’s data, the primary objective is for the total transfer between the source platform to the target platform with complete, efficient accuracy, and without the loss of any data.
Data transfers must also be done according to a business’s policy regarding their information and security, and must not violate any forms of validation within the new target system. With an absence of data requirements, the transfer will be done with a lack of integrity resulting in a migration failure.
Another goal for data migrations is that the process be executed as quickly as possible. As a company runs on its data, the downtime required for its data to migrate must be as little as possible since companies will suffer a great loss should the process take too long to complete. The process must also be cost-effective, as it will require technology and some personnel to operate.
The average process of data migration is:
- Analysis ––The classification of your company’s data – important factors in this process include knowing how your data is stored, backed up, and archived.
- Design ––This step involves taking the classification of your data and requirements defined in the previous stage, and give definition to how this will be accomplished;
- Extraction ––Data is read from the old system before being transferred into the new system;
- Cleansing ––Data is processed for incompletions or inaccuracies and corrected; this improves the data quality while eliminating repetitive or obsolete information as well as matching the data to the new system requirements.
- Load ––Data is transferred into the target system.
- Verification ––Data is checked again for accuracy and inconsistencies after the process is complete.
These steps are the foundational building blocks in developing a data migration system that is right for you and your company.
Some other factors to consider while in the preliminary stages of developing your data migration plan would be the required downtime when your computer systems are not operational. The risks this could bring to the business include technical compatibility issues, performance issues of the application, and even missing or lost data.
However, before planning out a course of action, it is recommended that your data be prepared. For effective data preparation, there are specific data analytics needed to complete this process as well as formulate a successful data migration strategy. Understanding the fundamentals, which you can do with one of Udemy’s great courses on data analysis could potentially help you to further understand the process of data migration and the specific needs for company’s migration strategy.
Common Data Migration Errors to Avoid
Presently, data migrations are now completed through software, which helps free a company’s human resources. However, because of its primary use of technology, there is room for error. The common pitfalls to avoid while strategizing for your company’s new migration system are poor data quality, redefining business rules and how your data correlates, and failure to test the migration process.
The quality of your data is essential before following through with a migration strategy. Poor data quality will inevitably cause more problems down the road, as it will transfer incorrectly. Assessing your company’s data beforehand through thorough data analytics will save your company time and money.
Another mistake company’s face is that of their business rules. Too often, years down the road, business that started out well have fallen into sloppy rhythms, and this causes problems when beginning to migrate your data. Before strategizing, you must not only update your business rules and come to policy agreement, but your data must comply with those said rules. If not, then the data will violate its own verification failing to meeting your company’s own standards.
While you are in your preliminary stages of thinking of a data migration strategy for your company, do not forget to implement a regular testing of the migration process. Failure to do so ––which too often companies are guilty of committing ––could cause errors once you have launched your data migration strategy into full effect. To achieve successful data migration, companies must remember to take the time aligning their testing, validation, and migration cycles so that the process is not counterproductive during the execution process.
Potential Risks of Data Migration
There are always risks when it comes to transferring your data. The most obvious, of course, is the potential loss of your company’s data. To help prevent this, you must first understand:
- What data you are migrating? Ask yourself, “Where does it live in the current system, what is its current form, and what form shall it taken once uploaded into the new system?”
- Be sure to extract, transform, and reduplicate your data according to the data requirements.
- Data policies are also essential here so that your data is moved in an orderly fashion.
- Remember to validate your data through tests to ensure its accuracy.
- Lastly, document and audit the entire process. These steps will help protect your data against potential losses in the migration.
Other common risks are those your team may face. Be sure they are equipped to handle this project, that they have the basic training they need, and it is not being given to employees who are not fully familiar with the practices and tools of data migration. Again, Udemy offers many resources on training for the development of data migrations and their strategies. Be sure to browse their website for more information.
Big Data Migrations
Perhaps you might be a larger business that uses big data, which is any collection of data too large and complex for any traditional data processing application. If so, the necessary steps for you to develop a successful big data strategy––which differs greatly from the average data migration ––are outlined within this Udemy course.
Big data differs in that it is existentially more complicated due to its size and complexity. These data sets are too difficult to process for on-hand databases and other traditional methods. Thankfully, entire systems are now built specifically for big data migration, and the strategies need to ensure a successful transfer build upon the above, listed basics.
Whether you are a small company needing to upgrade from its outdated legacy system, or a much larger business primarily using big data, Udemy offers many courses on the development of successful data migration strategies which can help your business transform to be more efficient, prosperous, and updated for a more technological age.