Google Cloud Next ‘20: OnAir and in the Cloud with Maven Wave – Data Management & Databases Week

After learning the latest about data analytics during last week’s Google Cloud Next ‘20: OnAir sessions, we’re digging further into data with the week six “Data Management & Databases” theme. The virtual event has kept us on our toes over the past few days with lessons around new BigQuery features, storing and streaming data, empowering data through AI, and more, this quick GCP video reports. In one standout session, the Google Cloud team highlighted Major League Baseball’s journey from Teradata to BigQuery.

google_cloud_datamanagement_next

Now it’s time to dive into how enterprises can best migrate, manage, and optimize their unprecedented levels of data. Cloud SQL, Cloud Bigtable and Cloud Firestore make major appearances, and customer stories involving The New York Times and McKesson are on display. We’ll see you at the virtual presentation! 

For now, in typical OnAir and in the Cloud with Maven Wave fashion, we’ve asked one of our expert Mavens to weigh in on this week’s topic. Keep reading for our Q&A with Rao Bierneni – Principal, Cloud Application Architect at Maven Wave. (If you missed last week’s edition of this blog series, check it out here!) 

Q: How does Google Cloud help enterprises migrate, manage, and optimize traditional databases?

Databases are central to cloud migrations but they are also tough due to a number of reasons such as:

  • Traditional Databases: Include a lot of proprietary functionality built into the database. (ex. Oracle)
  • Monolithic On-Premise Databases: Often deployed on huge rigid servers that do not fit into the “cloud way” of doing things.
  • General Design: 1 database: n applications. Some might not be compatible with different platforms. 

Google supports two kinds of Cloud Database Migrations:

Homogeneous Migration (i.e. “Lift & Shift”)

Benefits: Faster migration time, fewer application rewrites, familiarity with the current stack.

Challenges: server sizing and configuration (ex. huge source Oracle databases will require “splitting up”)

Heterogeneous Migrations (i.e. “Modernization”)

Benefits: Reduce and/or eliminate reliance on a single database vendor, reduce Total Cost of Ownership (TCO) of your database deployments, adopt open-source and cloud-native database technologies, modernize database architecture.

Challenges: Schema conversion, real-time data migration (change data capture CDC), “breaking” vendor lock-in caused by proprietary features, application support, etc.

Q: Enterprises are embracing the rapid pace of innovation and the modern-day cloud. Still, many don’t want to disrupt their existing IT landscape or upgrade all their legacy applications just yet. How can Maven Wave address these challenges and enable enterprises to migrate workloads to GCP in a simple, cost-effective, and secure way?

Maven Wave has the proven tools, technology, and certified, skilled resources that make up our collective expertise to help ensure your business remains agile, scalable, and cost-effective. As such, we are meticulous in the planning and execution of your cloud infrastructure with Google Cloud. 

When combining Maven Wave’s knowledge of the cloud together with our vast experience with Google Cloud, you can be certain that your move to the cloud will be seamless and smooth. We help you achieve primary critical objectives, such as operational excellence, cost optimization, reliability, performance efficiency, and security.

Q: COVID-19 has spurred a new era of digital transformation. As digital access to critical information rapidly increases, how does Google Cloud deliver a scalable solution to meet rising digital service delivery needs? 

The Google Cloud Professional Services Organization (PSO) can help accelerate your journey to the cloud, create a cloud culture, and unlock next-generation technology for your business. Google Cloud is transforming customer experiences with artificial intelligence/machine learning and data-driven insights. Google supports Multi-AZ, cross-region disaster recovery (DR), and high availability (HA).

Cloud Database Options for Homogeneous & Heterogeneous Migrations: 

  • Relational: Bare Metal Solution, Cloud SQL, Cloud Spanner
  • NoSQL / Nonrelational: Cloud Bigtable, Cloud Firestore, Firebase Realtime Database, Cloud Memorystore. Google Cloud’s BigQuery and the associated advanced analytics products and services that surround it.

With Google Cloud, you can choose from a variety of databases, giving you the flexibility to migrate your workloads by choosing a purpose-driven database versus a traditional monolithic database.

Q:  Tell us more about how customers can take advantage of Maven Wave’s Google Cloud Partner Specialization in Data Analytics to build and manage their databases. 

Maven Wave has already been heavily vetted by Google. In order to obtain a Google Cloud Partner Specialization, a partner must go through a rigorous process of demonstrating (by presenting our work product) to Google that they have not only served customers in a specific specialization but also that the engagement was done at a very high strategic level. So with this specialization, a customer can be sure that Maven Wave has proven expertise across a number of clients and that we have strategic methodologies already in place to benefit the client and accelerate time to value.

We help you balance cost savings (“Lift & Shift”) + innovation (“Modernization”)

  • Cost-savings investment decreases operating costs
  • Innovation investment increases top-line revenue

Maven Wave’s Suggested Sessions for Google Next OnAir Data Management & Databases Week:

Thanks, Rao! Don’t miss next week’s Google Cloud Next ‘20: OnAir and in the Cloud with Maven Wave blog, where we’ll discuss all things Application Modernization. With a keynote around “Building Trust for Speedy Innovation,” week 7 will bring us discussions about shipping faster and managing apps with Anthos, optimizing cost to performance on Google Kubernetes Engine, and more. But for now, soak in the data knowledge!

August 17th, 2020
DATA ANALYTICS & MACHINE LEARNING

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2020-08-17T10:56:05-05:00