Category Archives: Art of BI
Making Your SQL Server to MySQL Migration as Smooth as Possible
Sometimes your first choice of a relational database management system ends up being a poor fit for a new project or your long-term goals. If you need to migrate from SQL Server to MySQL, you can improve your chances of a successful migration by going through a few preparation steps.
Analyze Your Current Database Performance
Establish a performance baseline for your SQL Server. You need that data to compare to the MySQL deployment, so you know if you’re achieving the expected performance goals and improvements.
Audit Your SQL Server Databases to Improve Data Quality
Deduplicate your databases, get rid of junk data, and generally clean up the SQL Server databases. You don’t want poor data quality to migrate to the MySQL servers, so address it long before the migration process.
Check-in on Project Schedules and Deadlines
If the migration results in significant downtime, it’s critical to coordinate with key stakeholders to avoid disruptions. Get feedback from departments and teams within your organization, as well as from larger client accounts. While you can’t make everyone happy if downtime occurs, you can at least minimize the impact on top priority and critical projects.
Decide Which Type of Deployment Makes Sense for Your SQL Server to MySQL Migration
Do you want to take an on-premise server into the cloud? Are you looking for a hybrid infrastructure instead? Establish the type of deployment and the associated resource requirements before you get too far into the planning process.
Create a Realistic Timeline with Extensive Testing
Best case scenario timelines may sound good when you’re getting buy-in from upper management, but delays come in many forms. Unrealistic timelines lead to more stress and hassle in the long-term. Account for enough testing time for any schedule that you develop.
Make Sure You Have Enough People on Hand for the Migration Process
Do you have the right mix of specialists to handle the SQL Server migration? Consider working with database managed services providers, such as Datavail, to staff this project without taking away from other critical IT tasks.
Put MySQL Training Materials In-place
Offer training workshops and resources to your team so they’re familiar with the differences between SQL Server and MySQL. While you likely have database professionals experienced in this technology, improving awareness of its features and benefits is worthwhile. A training program also helps SQL Server specialists upskill into MySQL if they need to make that change.
Back Up Your Data
Data loss is a risk for any migration, so check your backups before you proceed. A robust disaster recovery plan gives you the safety net you need in case unexpected problems delete or corrupt critical data.
SQL Server to MySQL migrations don’t need to be filled with stress, downtime, and adoption difficulties. Advance preparation and the right database team go a long way. Contact us to learn more.
Read This Next
The Advantages of Migrating from SQL Server to MySQL
This paper highlights the four steps to take to migrate from SQL Server to MySQL, plus the best features available in the latest version, MySQL 8.0. This paper also intends to help you determine whether it’s time for your organization to migrate from SQL Server to MySQL.
The post Making Your SQL Server to MySQL Migration as Smooth as Possible appeared first on Datavail.
Use Cases for Kubernetes on MongoDB
Containerization offers many benefits for your development team through its flexibility, versatility, and support for a wide range of deployment environments. MongoDB supports Kubernetes, an open-source container orchestration technology that automates many key aspects of working with containerized applications. Container orchestration empowers your organization with several compelling use cases.
Microservices Orchestration
The use case that many people think of when Kubernetes is mentioned is microservices management. It groups your application’s containers together and facilitates managing them. Complex applications benefit the most from this type of infrastructure, and it streamlines many software development tasks, such as updating components and troubleshooting program errors.
Another benefit of using Kubernetes on MongoDB for microservices management is improving the reliability of applications. A component failure is automatically addressed with the right configuration, and each microservice can also access resources based on its current needs.
Deployment Flexibility
Kubernetes is not tied to a particular deployment infrastructure. It’s capable of working with public clouds, private clouds, hybrid clouds, and on-premise environments. Your software development team can evaluate each MongoDB-based application to determine the ideal option. If you end up needing to move to a different environment, migration is straightforward and relatively fast. This flexibility allows your organization to take advantage of new technology and keep up with changing best practices.
Hassle-free Horizontal Scaling
MongoDB offers excellent scaling capabilities, and Kubernetes adds more useful features in this area. You can set up your application to automatically scale up and down based on the container’s CPU usage, or you can manually control it via a command line or a handy UI. When you’re working with very large data sets, being able to seamlessly manage their distribution in a cluster allows you to work with them sustainably.
Automating Changes to Containers
Keeping applications up to date and avoiding unexpected downtime can be a challenge. Kubernetes on MongoDB manages this process through automation. It will deploy your updates and continually monitor the application. If it detects a problem, the change rolls back to avoid outages. This self-healing mechanism saves a lot of time and trouble in the testing process. It also makes iterative updates easier to deploy.
Load Balancing MongoDB Clusters
Kubernetes assigns unique IP addresses and DNS names to Pods, which are grouped containers. This process makes service discovery simple and facilitates load-balancing measures.
MongoDB and Kubernetes are a match made in heaven. When you’re working with a MongoDB cluster and you want to take advantage of containerization, this combination is hard to beat. Datavail can help you implement Kubernetes and get more out of your MongoDB applications. Tell us about your project today!
Read This Next
MongoDB on Kubernetes: How to Add Containerization Tech
Containerization is a powerful and flexible way to create modular applications that can easily move between platforms. Download our white paper to learn the features & benefits of MongoDB on Kubernetes and how to maximize the value of Kubernetes in a MongoDB environment.
The post Use Cases for Kubernetes on MongoDB appeared first on Datavail.
Say No to Startup Data Overwhelm
The exponential growth in the numbers of programming languages, apps, formats, and devices makes managing today’s data stores incredibly intricate. The work is made even more difficult when also adding the equally increasing numbers of regulations and regulators around the world, who continue to issue ever-more stringent rules about data privacy and control. For many startup companies, the consequent data management hurdle would be too great to overcome without the support of a dedicated “Data Management as a Service” team.
Data Management as a Service?
The growing influx of data concerns brings with it an obligation to understand and master the control of each, regardless of its origin or purpose. Further, in today’s global economy, no company can exempt itself from the practice without risking losing its prime target market. However, those same companies rarely have the funding to fully staff a dedicated data management team. A managed services provider can help resolve problems many of these issues such as:
- The team brings instant expertise. As a data management contractor, Datavail is already experienced in both legacy and emerging data management systems, having worked through the evolution of Big Data into “Mega Immense Data.” Having already mastered the demands of the varying channels, devices, operating systems, etc., Datavail now shares its knowledge and skills with its customers to ensure that they, too, can master the data that drives their business.
- They’re ahead of the regulations curve. Europe’s implementation of the General Data Protection Regulation (GDPR) last year appears to be just the beginning of a global sweep toward stricter data privacy rules. In January 2020, California’s“Consumer Privacy Act” (CCPA) goes into effect, which is creating yet another layer of compliance oversight for organizations that handle consumer data.
Like the GDPR, the CCPA applies to any company doing business in the state, even if they don’t actually have a physical presence there. Companies doing business in Europe or with Europeans that are already compliant with the GDPR will have an easier time becoming compliant with the CCPA. Those organizations that aren’t yet (or don’t need to be) compliant with the GDPR, however, may be starting at square one; accessing a data management service provider already skilled with similar compliance mandates will certainly ease that process.
- They’re on top of data management architectures. Managing the volume of data also means managing how it’s used, stored, and accessed. The emergence of Artificial Intelligence and Machine Learning means that more machines and programs than ever before are accessing data and gleaning ever-more granular business insights in the process. A dedicated data management service provider will help its customers implement these tools to delve even deeper into their proprietary information.
Data management is challenging especially when a company is not in the business of data management. Accessing the services of a data management specialist can save money and time for every startup that wants to use its internal resources to achieve more specific corporate goals.
At Datavail, the security and privacy of our client data forms the bedrock of our culture. We continue to invest in security capabilities that enable the safety of the data and systems entrusted to us by our clients. This investment is at the heart of our ISO/IEC 27001:2013 commitment, compliance and certification. Contact us to learn more.
Further Reading
Team Up to Secure Your Startup Success
10 Reasons You Need Half a DBA
5 Application Development & Management Issues You Can Solve with a Sprint Teama>
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EPM 11.2.2.0 – Notable Differences Between Windows & Linux
Weekends sometimes offer time for some leisurely R&D (especially with the current lock-down/mask rules). I posted previously about some issues I noticed in the Linux edition of Oracle EPM/Hyperion 11.2.2.0. Well, this weekend I finished standing up the Windows edition. Here are some key configuration errors/issues I spotted.
FDM Enterprise Edition (FDMEE)
You’ll find a 3-part post concerning 11.2.2.0 FDMEE errors in Linux. In the Windows edition, I encountered none of those issues. The ODI tables built successfully, and FDMEE in Workspace, ODI Web Studio and ODI Agent were all functional.
Suggestion for Linux users:
Install the 11.2.2.0 Windows edition (you don’t need to configure) and zip up \Oracle\Middleware\odi, ftp it over to your Linux server, and unzip it with the Replace option in /Oracle/Middleware/odi.
Also copy aif.ear from Windows to Linux.
Then re-try your Configure Database and Deploy for FDMEE.
Planning RMI
This starts up just fine in Linux and successfully binds to port 11333. In Windows, we still have the issue I wrote about for 11.2.0.0 and 11.2.1.0. You’ll find the solution to fixing the Windows Registry for Planning RMI here on my blog.
Analytic Provider Services
In Windows, it deploys just fine. In Linux, it gets a deployment error.
Suggested solution for Linux users:
Install the Windows edition of EPM 11.2.2.0 (you don’t need to deploy). Copy aps.ear from Windows to Linux, and then redeploy in Linux.
Cross-posted from EPM On-Prem Pro. Read the original post here.
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