What Is Cloud Data Migration?
Cloud data migration is moving data storage and applications into the cloud. A migration initiative may involve consolidating and moving data workload from legacy, on-premises data warehouses to a cloud data warehouse. Or, it might require building new cloud data warehouses or data lakes. Or perhaps it uses a hybrid cloud data management solution incorporating both.
Why Is Migration to the Cloud Important?
You might be moving existing on-premises data to the cloud or building a new data warehouse or data lake from scratch. Either way, organizations migrate to the cloud to leverage the inherent benefits of cloud computing, such as agility, fast provisioning, infinite scalability, consumption-based pricing, reduced infrastructure cost, cost optimization, seamless upgrades, and rapid technology innovation.
Benefits of Cloud Modernization
Cloud data migration lets you modernize your infrastructure, enabling your organization to accelerate time to value, improve operational efficiency and reduce migration costs, time, and risk.
By moving to the cloud, you can:
- Ingest virtually any type of data (structured, unstructured, semi-structured) and efficiently process large amounts of data in less time
- Scale elastically and quickly meet changing business needs and unpredictable demands
- Reduce IT maintenance costs as you retire your on-premises data centers
- Streamline data analytics with cloud processing power and optimize costs with a unified data infrastructure
- Futureproof your data infrastructure with a flexible, sustainable, and agile data foundation that is future-ready data use cases at your own pace.
- Democratize data for any data user. Empower virtually any data practitioner (i.e., business analysts, data scientists and data engineers) with intuitive, self-service tools to increase efficiency and accelerate time to insight.
Checklist for Cloud Data Migration
1. Define your future end state
Don’t engage with a vendor and work backward to dovetail your data needs into their cloud data warehouse, cloud data lake or both. Instead, start by determining your business goals. Then, choose a cloud-native data management solution that meets your current needs and is future-proof. It should address your future data management needs as your business evolves. It also needs to offer the extensibility to support growth without forcing you to rip and replace previous work. The right cloud data management solution should have multi-cloud support. This gives you the flexibility to support your modernization journey with the cloud vendor of your choice.
2. Catalog your data
An intelligent data catalog provides insight into what data you have, where it is located, what is currently used, and how that data needs to be protected. It also makes it easier to find and access specific data as required. That way, you can quickly identify high-value data and prioritize its move to your new cloud data warehouse or data lake. This allows your data consumers to start using the new technology right away. At the same time, your development team can backfill data without disruptions.
3. Standardize and cleanse your data
Pay attention to data quality and governance before your cloud data migration. This will reduce the preparation work you need for cloud analysis. Look for an extensive set of pre-built data quality rules. These should enable you to cleanse, standardize and enrich all data without coding. This ensures that your data users can trust the data they receive and analyze.
4. Manage your metadata
Metadata management is key to automating the process of moving data into your cloud data warehouse or data lake. It simplifies discovering, tagging, relating and provisioning your data. To be effective, your cloud data management solution collects metadata from all your enterprise systems. This includes technical, business, operational, infrastructure and usage metadata — from database schemas and glossary terms to volume metrics and user access patterns. In addition, your solution should curate your metadata and augment it with business context. It should also be able to infer data lineage and relationships between entities.
Cloud Modernization Success Stories
BMC Software Reduces Conversion Time by 70%
BMC is a leading cloud-based SaaS company. As part of their larger cloud modernization journey, they wanted to modernize from PowerCenter to the Informatica Intelligent Data Management Cloud™ (IDMC). By using the Informatica Migration Factory, BMC transferred 4,000 database tables and associated data. Informatica then focused on data pipelines, converting 217 workflows and 5,174 mappings. BMC further accelerated migration using its own data ops capabilities and tools for data validation. The Migration Factory successfully migrated 99% of PowerCenter mappings, leaving only 1% to be rewritten manually. This reduced BMC’s expected conversion timeline by 70%, while also achieving 70% cost savings for code migration.
Driving Customer Engagement at McGraw Hill Education
McGraw Hill Education (MHE) is one of the "big three" educational publishers that puts out educational content, software and services for pre-K through postgraduate education. MHE decided to accelerate its cloud journey by modernizing from PowerCenter to IDMC. With an eye toward lowering TCO and time to market, MHE sought to consolidate integration solutions onto one platform to support all integration patterns. The modernization will help them enhance customer engagement, realize cost savings and accelerate time to market.
Pfizer Reduces the Time Needed to Manage Orders by 50%
During its COVID-19 vaccine clinical trials, when speed was critical, global pharmaceutical and technology company Pfizer reduced the time needed to manage orders from distributors to manufacturing by 50%. They achieved this by consolidating and migrating their legacy on-premises workloads for supply chain analytics to the cloud. Native integration between the new cloud data management platform and Pfizer’s data warehouse helped the company reuse the global supply chain business logic that they had built, protecting years’ worth of on-premises investments and saving data transfer costs. Sophisticated cloud-native data management services automated 99% of the code, significantly reducing development effort. Pfizer also slashed data loading time for 5 million records from 19 hours (with hand coding) to just four hours.
Getting Started with Cloud Data Migration
IDMC delivers best-of-breed data cataloging, data quality and metadata management so you can:
- Quickly discover high-value data assets
- Streamline integration efforts with standardized and reusable integration assets
- Take advantage of cloud data warehouse and data lake technologies to avoid persisting redundant or outdated legacy solutions
- Discover and improve the quality of your data before you integrate it
As part of IDMC, Informatica supports your successful cloud migration with a next-generation integration platform-as-a-service (IPaaS). It offers microservices-based, API-driven, AI-powered support for all the leading cloud platforms, including Amazon Web Services, Microsoft Azure, Snowflake, Databricks and Google Cloud.
- Find out more about how the Informatica Cloud Modernization program facilitates cloud data migration.
- Check out this resource on how to go beyond lift and shift for cloud data migration and operations.
- Learn more about modernizing from Informatica PowerCenter to IDMC here.
- What is cloud data integration?
