Successful Data Integration Into Azure: 3 Things to Consider
Organizations interested in leveraging the power of Azure should consider the following three tips when architecting data integration solutions.
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According to Forrester, as of the beginning of 2019, close to 60 percent of North American enterprises rely on public cloud platforms, which is five times the percentage five years prior. On top of this, organizations use their internal data centers as private clouds.
At year-over-year growth of 76 percent (as of January 2019), Microsoft’s Azure is not only one of the largest but also one of the fastest growing public cloud platforms. But, as with any technology platform, organizations can’t necessarily simply sign up for an account and reap immediate rewards. A careful approach is required.
Cloud data integration can apply to a variety of use cases: integrating from various sources into an Azure Data Lake Store (ADLS) data lake, migrating on-premises to the Azure cloud, running real-time analytics in the cloud, or integrating into cloud systems. Organizations interested in leveraging the power of Azure should consider the following three tips when architecting data integration solutions:
1. Secure Your Data
For years, security (or rather the perceived lack thereof) was one of the main concerns limiting the adoption of the cloud. However, there is now a strong focus on cloud data security given that data breaches can negatively impact cloud providers’ business. Many data breaches are now caused by delayed patching of known problems or poor password management. Although data security is a priority for the Azure cloud, the responsibility of ensuring all of your data remains secure is your responsibility. Following are some tips to consider:
- Use Azure’s virtual network, and avoid the use of public IP addresses, if possible.
- Encrypt data, especially between public IP addresses on the network, using an AES256 or stronger encryption method.
- Limit access to the on-premises data stores by keeping the firewall closed, if possible. Take advantage of a proxy in a DMZ (de-militarized zone) if a port must be open between the cloud into the on-premises system.
- Use strong authentication when connecting from the outside by deploying two-factor authentication. Once in Azure, use the Azure Active Directory.
- Take advantage of the Azure-native Storage Service Encryption using Microsoft managed keys or by storing your own keys in the Azure Key Vault.
2. Optimize Your Network Utilization
The best way to maximize your network resources is to optimize the unavoidable use and avoid unnecessary use – figure out how to use your network as efficiently as possible when you must it, and eliminate network use that isn’t required. To do this, look for data integration solutions that:
- Compress data before sending it across the wire. Balance the compression ratio with the cost of compression/decompression to satisfy your business needs for latency and utilization by other resources.
- Use a Change Data Capture (CDC) mechanism, ideally by identifying relevant changes as close to the data source as possible.
- Use optimization techniques to leverage available bandwidth even if latency is relatively high.
3. Validate Your Data
Irrespective of whether you gradually migrate on-premises databases into Azure, implement a data warehouse using Azure SQL Data Warehouse, or build a data lake in the ADLS, data accuracy should be top of mind. Minimize risk during data migrations by validating data for accuracy before switching over to the database in Azure. By regularly validating data and sharing accuracy reports, you can ensure end users’ trust in the data warehouse or lake.
Azure is a powerful — and increasingly popular — cloud platform, and the flexibility and compute power it provides can more than meet your organization’s data needs. By carefully thinking through security, network optimization, and data validation as you develop your data integration solution, you can be certain you’re harnessing all that Azure can offer.
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