The roadblocks of migration


Enterprises all across the globe have been dealing with large volumes of data for solving complex business problems. The traditional migration platforms developed years ago aren’t capable of handling current business issues. Yet, most of the data analytics tasks are still carried out with the help of traditional data warehouses. There has been a massive demand for high-speed business analytics, and legacy data warehouses do not fit the bill. Traditional ETL tools can only process relational data. They often fail to process semi-structured and unstructured data formats resulting in data loss, which, in turn, causes integrity issues. Also, they require manual efforts to build and manage data pipeline, which is why enterprises are resorting to cloud migration services for transforming their ETL workloads from legacy data warehouses.

Many enterprises have been using Ab Initio to solve complex data processing problems. However, = the advent of advanced platforms such as oracle database migration questions the relevance of Ab Initio. Cost reduction is one of the primary motives for enterprises trying to move away from Ab Initio. Modern ETL tools offer a dual advantage by allowing the use of open source technologies and offering more flexible options.

However, migrating from Ab Initio is a difficult process. The task of moving thousands of graphs from your existing Ab Initio implementation can be daunting.  Additionally, factors such as different proprietary languages, lack of standard development languages, and metadata specifications for each tool add to the complications of automated transformation.

It, therefore, becomes important for businesses to identify and allocate the appropriate resources, possessing the expertise to analyze the current ETLs, design them again with the help of modern tools and test everything with absolute ease.  Another pressing issue that weakens the efforts of a dedicated team is the unclear estimation of timelines and the costs.

A lot of data leaders are facing challenges with the volume of the data and the time required to finish the migration task besides the fixed number of resources that will be needed to accomplish the task. It is crucial to have the much-needed clarity to achieve the desired results, and that’s not possible without robust data migration strategies. Therefore, an automated approach to migrating Ab initio to the modern ETL platform coupled with advanced technologies can solve all these challenges.




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