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Managing data in a multicloud world

How to oversee, move, and access data across cloud environments

Melvin Greer

Multicloud environments can drive agility, but only if cloud data management and data protection are part of the strategy. Managing data in a multicloud world is a business imperative. Cloud engineers and IT leaders need to manage data assets across cloud and on-premises environments, and organizations demand that data be readily available, whether it’s in a cloud, across clouds, or on-premises.

Join expert Melvin Greer to learn the benefits of multicloud environments and discover how to best manage your data within them. You’ll get a blueprint for how to make the leap to data management via multicloud environments, helping you harness distributed data to transform your business. Along the way, you’ll gain insights into what data should be stored, used, and made available from which cloud options. You’ll leave with tools for rapid data recovery and managing workloads stored in multiple clouds.

What you'll learn-and how you can apply it

By the end of this live online course, you’ll understand:

  • How to move, manage, and use data across multiple clouds across cloud environments
  • New insights on country-specific data handling regulations
  • Best practices for maximizing data flexibility in a multicloud environment

And you’ll be able to:

  • Reduce cost, improve agility, and improve customer satisfaction with a multicloud model through a successful data management capability
  • Design and implement multicloud data governance that provides increased insight
  • Enhance and improve data portability and interoperability across cloud environments

This training course is for you because...

  • You’re a cloud computing architect, cloud engineer, data architect, or IT professional who needs to know which data should live in which cloud type or cloud storage option.
  • You’re a senior executive who wants to harness the power of data to transform your business through cloud computing.
  • You work with teams looking to leverage advanced IT capabilities (e.g., big data analytics, artificial intelligence, cloud computing, machine learning, and blockchain).
  • You want to become a cloud computing architect, cloud engineer, or data architect.

Prerequisites

  • Management experience leveraging cloud computing deployment and service models to deliver products and/or services
  • General knowledge of internet and web-related technologies

Recommended preparation:

Recommended follow-up:

About your instructor

  • Melvin Greer is a chief data scientist for the Americas at Intel, where he’s responsible for building the company’s data science platform through graph analytics, machine learning, and cognitive computing. He’s the founder and managing director of the Greer Institute for Leadership and Innovation; a fellow of the National Cybersecurity Institute; a professor within the Master of Science in Data Science Program at Southern Methodist University; an adjunct faculty member with the Advanced Academic Programs department at Johns Hopkins University; and a member of the board of trustees at Capitol Technology University. As a popular educator and board member at a number of historically black colleges and universities (HBCUs), Melvin leads STEM research initiatives, trying to shape a more diverse generation of up-and-coming technical talent. He’s one of the 2018 LinkedIn Top 10 Voices in data analytics and science and has received the inaugural WashingtonExec Pinnacle Award for the 2018 Artificial Intelligence Executive of the Year, the 2017 BDPA Lifetime Achievement Award, and the 2012 BEYA Technologist of the Year award. Melvin is a frequent speaker at conferences and universities and is an accomplished author; Practical Cloud Security a Cross Industry View is his most recently published book. He holds both a BS in computer information systems and technology and an MS in information systems from American University in Washington, DC, and completed both the executive leadership program at Cornell University’s Johnson Graduate School and the entrepreneurial finance program at MIT’s Sloan School of Management.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

Developing a multicloud data strategy (55 minutes)

  • Lecture: Creating a multicloud strategy based on your business and technology needs
  • Hands-on exercise: Select the appropriate multicloud architecture given a set of business data requirements
  • Group discussion
  • Q&A

Break (5 minutes)

Making multicloud data management simple (55 minutes)

  • Lecture: How to simplify multicloud complexity—data visibility and protection; migration enablement; data regulation and compliance
  • Hands-on exercise: Identify an appropriate data strategy based on cloud location and applicable regulation and compliance guidelines
  • Group discussion
  • Q&A

Break (5 minutes)

Lessons learned and avoiding common mistakes (50 minutes)

  • Lecture: Three common mistakes to avoid
  • Hands-on exercise: Identify three key aspects to consider before making the leap to data management across multicloud

Wrap-up and Q&A (10 minutes)