Many companies have long used data warehouses for analytical purposes and decision making in departments that regularly leverage reports and dashboards, such as sales, marketing, and finance. The rise of digital technologies over the past few years however has changed the data warehouse landscape, according to Microsoft.
Companies are moving more applications – CRM, ERP and HR – to the cloud to consolidate systems, scale operations and enable mobile self-service.
This means that data warehouses now need to have the ability to capture data from cloud SaaS applications. Data points have expanded to include social media data, Internet of Things (IoT) sensor data, weather information, or even image, audio and video data.
But data warehouses are lagging. Data scientists are processing and analyzing this cloud-based data separately.
So companies are migrating from on-premise to the cloud to modernize their data warehouses and take advantage of its high speed, security, scalability, cost savings and performance.
Why Move Your Data Warehouse to the Cloud?
Many businesses are migrating their data warehouse to the cloud to advance their data capabilities, such as implementing machine learning in their operations. Moving to the cloud also enables a more seamless integration with newer technology systems, as well as provides greater data security. The benefits of moving your data warehouse to the cloud far outweigh on-premises and include:
Performance
With the cloud, you can optimize your data warehouse more efficiently. Having your data warehouse in the cloud increases the overall capabilities of the hardware and software used to process your data. Your solution can run smarter.
Speed
The data warehouse process requires ingestion, transformation and analysis, cleansing, aggregation and integration of the data. Then it makes visualizations and reports based on those findings. Those steps take time. The process is also complex, with each step dependent upon another. This dependency means one issue or a spike in data volume can bottleneck the entire process. With a fast-processing, cloud-based data warehouse, you can gain the critical information you need to make timely decisions.
Security and Compliance
The Microsoft Cloud provides multilayered security protections with over 3,500 global cybersecurity experts. The knowledge and reach that Microsoft has is more than most companies can achieve on their own, which means threats are detected faster, and your assets, information and sensitive data will be the secure. Although Microsoft acts as custodians of your cloud data, you are the sole owner and administrator of that data.
In addition, Microsoft is regularly audited by the ISO to confirm its compliance with rules and regulations. With regular updates, your solution will always have the most up-to-date compliance standards.
Lastly, in the case of disaster, your cloud solution has backup and disaster recovery capabilities. IDC research has shown that backup in the cloud can be 76% faster than on-premise, and data recovery 66% faster.
Elasticity
It’s not uncommon for customer demand and operations to fluctuate. There might be a spike around holidays and lulls during other months. With cloud elasticity, you can quickly increase and decrease your data warehouse’s capacity to match your needs – without hurting your infrastructure availability, stability, performance or security.
Cost effectiveness and savings
One of the major benefits of utilizing a cloud-based data warehouse is the flexibility in cost. If your needs dip and rise, your expenses will match that use. On-premise legacy solutions on the other hand require an outlay for servers and hardware, networking, the physical storage space, electricity, cooling and IT staffing. Those upfront costs aren’t required with a cloud solution.
With the cloud, businesses can:
- Lower the implementation and maintenance costs associated with their traditional on-premise data warehouse.
- Pay for additional data or tools when needed.
- Reduce the cost for storing staging and production data.
Managed infrastructure
Microsoft stores data in state-of-the-art data centers the company owns and manages itself. This means you remove this task from your team and can allocate those skills and resources to other more strategic aspects of your business. In addition, without the hassle of managing the infrastructure yourself, your team can focus on remaining leveraging the insights your cloud-based data provides.
Scalability
Having a solution that can grow with your business is critical. Given that the volume of historical data in your data warehouse will increase over time, with the cloud, you can add resources as your company’s needs, workloads and data increase.
Do more with your data
Whether your team prefers Apache Spark or SQL, or they all prefer different programming languages, with a Microsoft cloud-based data warehouse, users can easily collaborate. Data engineers can transform data into actionable insights and models, leveraging machine learning and tools like Power BI to deliver those to the people who need them most.
Remove data silos
Transform your data lake -- your vast expanse of raw data-- into a fully functional data warehouse that can manage, secure and analyze any type of data. Remove data silos and give your team the ability to create end-to-end analytics solutions – without having to piecemeal a bunch of services together.
Additional benefits of migrating to the cloud include:
- Avoid expensive updates as your data volume increases or capacity is used through extraction, load and transform (ELT) processing.
- Reduce your storage costs, even when your data volume grows.
- Gain future-proof infrastructure that easily integrates with other systems and tools.
The Data Cloud Migration Process
Start with a well thought out plan.
Preparation
During the preparation phase, you need to clearly define what needs to be migrated and build an inventory of your data and existing process. Identify and assess processes and business systems to improve outcomes, including your ERP, CRM, productivity software and design tools.
Defining your goals during the preparation phase is also crucial. Solidify the objectives of your data warehouse migration. It's also beneficial to work with a trusted partner during a migration. Review a potential partner’s skills and expertise based on how they would complement and advance your own IT team’s capabilities. For example, they can help you identify the best source data extract mechanism and help you create a migration plan that works best for your data warehouse, your goals and your team.
The Preparation stage also includes:
- Define data model changes, if any
- Define source data extract mechanism
- Identify the tools and services you will use
- Train staff early and often on the new platform
- Set up platform
Migration
The goal for this stage is to start small and simple, and automate whenever possible. It’s also useful to utilize available tools and features within the cloud solution to reduce effort on your part. There are two typical migration strategies:
The Lift and Shift Technique
As the name suggests, you simply migrate your existing data – unchanged – to your new cloud platform. This strategy works well for minimizing risk and reducing the time associated with migrating. Businesses that benefit from the Lift and Shift have legacy data warehouses and have a single data mart or data in a star or snowflake schema, which is the simplest schema setup. Businesses pressed for time that need immediate action should consider this technique.
The Redesign Strategy
If your data warehouse has evolved and changed over time, your migration might require re-engineering of the underlying data model to perform optimally and support new data types. However, although this is a separate strategy, the best foundation for any move to the cloud is the Lift and Shift. From there, modernize your data warehouse. Changing your data model comes with risks, such as affecting the flow from source to data warehouse.
Post-Migration
Once the migration is complete, you should:
- Monitor all stages of the process and document the turnout.
- Create a template for future migrations
- Begin any re-engineering of data models, if needed.
- Test applications and query tools.
- Benchmark the data warehouse’s performance to optimize future performance.
How to Reduce Complexity in Your Data Migration
The productivity inefficiencies and obstacles you currently have should not move to the cloud with your company. When planning your data migration, look for ways to optimize your processes and reduce complexity. Not only does this ensure you don’t take with you what isn’t working, but it also makes the migration process smoother.
- Avoid migrating data that is no longer being used or has no use for the future.
- Convert physical data marts to visual data marts. A data mart is a subset of data that’s focused on a particular department (such as operations, finance or marketing). IBM defines data mart as “a focused version of a data warehouse that contains a smaller subset of data…needed by a single team or a select group of users.” By converting these data marts into visual form, you reduce expenses and improve agility.
Underlying any move to the cloud is a well-designed plan, with a focus on architecture and data preparation. Columbus can help you build scalable, future-proof data platforms customized to address your present and future needs. Reach out today to learn more.
Source: Empower IT and Data Professionals to Achieve More With All Their Data, published by Microsoft.