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LEGACY DATA WAREHOUSE MIGRATION

Do you need help moving digital assets, services, databases, IT resources, and applications to the cloud? Do you want to achieve real-time data insights and updated performance and efficiency? Get in touch!

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How DataMastery can help you

If you have a Legacy Data Warehouse Migration that you wish to migrate to the cloud, our experts at Data Mastery have the necessary skills, training, and experience to plan, implement, and execute your migration project from beginning to end.

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Data Mastery will work with you to fully understand your data flows, data lineage, complex workload translation techniques, data migration, and cut-over procedures as these factors can have a significant impact on project timelines and costs. We can then tailor our specially developed fast-track, ready-to-deploy frameworks to your requirements, accelerating and streamlining your journey to the cloud. 

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Working with the experts at Data Mastery you can reduce your risk, get there without disruption and ensure security, compliance and governance. Let us help get you there.  

Informational Interview

WHY CHOOSE DATAMASTERY

EXTENSION EXPERIENCE

During the past few years, we have been employed by a diverse range of companies across retail, commercial, private and public to deliver their data warehouse migration projects.

PROVEN FRAMEWORKS

We have numerous frameworks in place with leading Data and AI suppliers. We can supply you with documentation relating to all aspects of data.

PROVEN ABILITY TO DELIVER

Our ethos is ‘selling things that don’t come back to people who do’. We provide excellent experience to ensure every customer will share a great story about us.

What is legacy data warehouse or cloud migration?

Legacy Data Warehouse Migration or cloud migration is the process of moving a company’s digital assets, services, databases, IT resources, and applications either partially, or wholly, into the cloud. Cloud migration is also about moving from one cloud to another. 

Simply put, legacy database migration is the process of moving legacy data from an obsolete storage system to an up-to-date environment while keeping its value and dependencies intact.

But let’s take a closer look:

  • Legacy data. The term “legacy data” means that information is historical or, in other words, was accumulated during the organization’s past activities. Besides being buried in old software, legacy data is often poorly structured and has out-of-date formats. However, none of these means that this data is useless; on the contrary, it’s vital for a business and, thus, worth storing.

  • Obsolete storage. Basically, this is a database environment that can no longer ensure the effective use of data. Why? Most often, it’s because this environment relies on technologies that are past their prime or third-party IT infrastructures that a vendor has ceased to support (for example, a software system based on MS-DOS).

  • An up-to-date environment. This environment represents an advanced modern system that meets the growing needs of today’s businesses (e.g., a cloud platform).

 

Depending on the business case, a legacy database migration process can also include data conversion or data integration. Data conversion happens when the original data is translated into a different format, while data integration means that the data from different sources is combined into a single database.

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The top five reasons to move to a cloud data warehouse are:

  1. Cost Reduction: Moving to a cloud data warehouse presents signifcant savings on hardware, infrastructure and other expenses that come from traditional systems.

  2. Improved Profitability: By improving the way data has been collected and processed, you can enable much faster insights on that data.

  3. Sales Projections: With the data centralized in the cloud data warehouse, it's easier for a data analyst or data scientist to build analytics and get actionable insights from that data.

  4. Standardize Processes: By enabling your cloud data warehouse and centralizing your data, your data professionals can work together more efficiently. Data professionals from different teams can now perform real-time updates and see what other team members are working on. This level of collaboration between teams can improve the productivity of your projects, as well as your customer service initiatives. Your warehouse will also be dynamic and able to support any scale of workload.

  5. Improve Efficiencies: Running analytics on the centralized data in the organization provides you with lots of insights that may highlight gaps that have been impacting the growth of your organization.

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