Data migration sounds simple enough: just move information from one place to another. However, most organizations today have millions of files and database records. Data migration is often a massive and highly complex project.

A Dimensional Research study found that 62% of data migration projects failed or were much more difficult than expected. Over half (55 percent) of respondents stated that their projects went over budget. Among organizations migrating data to the cloud, 43% expressed that the project would take more than two years.

Often, data migration projects are a component of a larger initiative, such as migrating IT infrastructure to/from the cloud, application modernization, the implementation of new technology such as machine learning or a combination of these. Additionally, it often involves data transformation to prepare the information for consumption by a new system, application or process.

The Cost Factor

Although data is a highly valuable IT asset, many organizations view storage solutions as a cost that they need to minimize. Companies are always looking for ways to save money, and in recent years this involves moving data into the public cloud. 

While Public clouds may initially seem like an economical choice. It eliminates the need to buy and maintain onsite storage, and provides nearly unlimited capacity. However, cloud storage can become a significant expense, and many organizations often find themselves looking to repatriate at least SOME of their cloud data back onto onsite storage to cut down on OpEx costs. Or there may be requirements to retain the data on premises.

If cost is the driver behind data migration, the process begins with a thorough analysis of where the data needs to be to maximize its value. When making that decision, organizations should look beyond cost reduction. The best solution may involve transforming the data so that it can be monetized or used to streamline business processes or enhance the customer experience. 

Driving Value

A prime example is the use of machine learning tools to extract valuable insights from the huge volumes of data that many organizations have accumulated. All too often, that data is just sitting in the data center, or across multiple facilities. So it needs to be consolidated, rationalized and transformed before it can be used to develop a machine learning model.

Machine learning tools use high-quality data to analyze data and put it to work to reduce business risk, create new products/services, or implement new business models. All the major public cloud platforms have machine learning products that handle data preprocessing and model training and evaluation. APIs link outputs to onsite IT infrastructure. This enables organizations to start small and gain experience in machine learning before investing in the infrastructure and skillsets needed to support it onsite.

How Rahi Can Help

Rahi’s experienced team has helped organizations in a wide range of industries extract more value from their data while optimizing storage costs. Our experts understand both on-prem and cloud platforms and know how to optimize a solution that takes the best of both worlds to create an optimal hybrid infrastructure. We can help develop the financial models that clearly present a value proposition that can clearly show, drive and justify data migration decisions.

We can then help craft an effective data migration strategy that encompasses consolidation, rationalization and transformation of multiple data sources. This approach is based upon our proven methodologies and uniquely customized to fit deadlines, scale, sources and type of data. We can leverage low-code and no-code tools that facilitate data transformation with minimal or even no  need for developers to write custom applications or scripts.

A key component of the process is post-migration testing and validation. Our team ensures that the data is a reliable source of truth that drives business processes, ensure accurate machine learning predictions and facilitate decision-making.

Data migration is a complex undertaking that requires extensive upfront planning and careful execution. Let Rahi help ensure the success of your data migration project.

Gill Wichi
Technical Solutions Architect
Gill Wichi is a Technical Solutions Architect at Rahi. With over 25 years of experience in storage, he has worked with almost all aspects of storage – from component, direct attached devices all the way to cloud storage solutions and everything in between. Gill has provided guidance and managed services to some of the largest enterprises in the Bay Area during his tenure as a professional services engineer, eventually graduating to providing design architecture solutions for a number of mission-critical businesses in and around San Francisco Bay.
In his time off, he likes to hike with his two German Shepherd dogs and un-doing the damage to his garden – also caused by his two German Shepherd dogs.
About Rahi
Rahi Australia is a 100% subsidiary of Rahi Systems Holdings, based in Silicon Valley, California, USA. We offers a suite of solutions and services that maximize today’s integrated environment’s performance, scalability, and efficiency. We help ensure users have access to the devices and software they need and provide state-of-the-art equipment that enables effective communication and collaboration.
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