Data is one of the most valuable assets any organization has, but few are using it to its full advantage. Various studies have shown that 68 percent to 75 percent of data goes unused, meaning that it’s collected and stored but never analyzed or leveraged for insights. Siloed data, poor data management practices and lack of data analytics skills are among the causes.
In today’s AI-powered environment, failing to leverage data means losing competitive advantages. Organizations miss out on the insights and improved decision-making that can help them become more efficient, serve customers better, and develop new products and services.
In order to capitalize on data assets, many organizations need to migrate data from legacy systems to modern data platforms. To perform optimally, most AI models and systems need centralized, well-structured data that is readily accessible. Data scattered across the IT environment must be consolidated, standardized and cleansed to ensure that AI models produce reliable and accurate output.
Types of Data Repositories
Over the years, various models have been used to collect and prepare data for analysis. Traditionally, analytics required a data warehouse — a centralized repository that stores large amounts of data from multiple sources in a hierarchical system of files and folders. Data warehouses primarily store structured data so they can be queried and analyzed efficiently.
However, as much as 90 percent of data is unstructured, meaning that it doesn’t have a prescribed format. Unstructured data includes text documents, email, chat sessions, graphics, audio files and videos. It isn’t neatly organized into rows and columns like a spreadsheet and thus requires a different approach. This led to the development of the data lake, which can house massive volumes of structured and unstructured data in a flat architecture.
A newer approach is to move data into a data lakehouse, which combines aspects of a data warehouse and a data lake. A data lakehouse captures unstructured, structured and semi-structured data so that it can be accessed and used for AI and analytics.
Why Data Migration Is Difficult
Whichever model an organization chooses, it generally makes sense to migrate data to cloud storage. Cloud object storage is cost-effective, can store large volumes of diverse data types and scales on demand as data volumes grow. Leading cloud platforms also provide data management features, encryption and access controls.
However, moving data from one device or platform to another is a complex process that’s fraught with risk. One of the most challenging aspects of the process is handling discrepancies in formats, architectures and encoding standards between the source and target systems. Typically, data needs to be converted to meet the target system’s requirements, a complex and potentially error-prone process.
Data should be cleansed before migration to remove data that is inaccurate, duplicate or incomplete. During and after migration, the data should be tested and validated to ensure that it transferred correctly and is error-free. It’s important to catch issues early to reduce the risk of bigger problems or outright failure of the migration.
The Value of Data Migration Services
As with any other complex IT project, data migration should begin with thorough planning. IT teams should thoroughly assess both source and target systems and determine how best to handle the transformation, cleansing and transfer process. Security and regulatory compliance should be addressed in the planning process to ensure that data isn’t compromised during migration.
Few organizations have this expertise in-house, so it often makes sense to engage experienced professionals to plan and execute the migration. Qualified experts will adhere to best practices to reduce risk.
Verteks offers data migration services to help our customers improve data management, reduce storage costs and better leverage their data. Whether you’re adopting AI, looking to improve performance and scalability, or need to meet regulatory requirements, Verteks can help you migrate your data to a more modern platform.