Cloud Migration

Twelve Best Cloud & DataOps Articles

Our resource picks for October! Prescriptive Insights On Cloud & DataOps Topics Interested in learning about different technologies and methodologies, such as Databricks, Amazon EMR, cloud computing and DataOps? A good place to start is reading […]

  • 4 min read

Our resource picks for October!
Prescriptive Insights On Cloud & DataOps Topics

Interested in learning about different technologies and methodologies, such as Databricks, Amazon EMR, cloud computing and DataOps? A good place to start is reading articles that give tips, tricks, and best practices for working with these technologies.

Here are some of our favorite articles from experts on cloud migration, cloud management, Spark, Databricks, Amazon EMR, and DataOps!

Cloud Migration

Cloud-migration Opportunity: Business Value Grows but Missteps Abound
(Source: McKinsey & Company)
Companies aim to embrace the cloud more fully, but many are already failing to reap the sizable rewards. Outperformers have shown what it takes to overcome the costly hurdles and could potentially unlock $1 trillion in value, according to a recent McKinsey article.

4 Major Mistakes That Can Derail a Cloud Migration (Source: MDM)
If your organization is thinking of moving to the cloud, it’s important to know both what to do and what NOT to do. This article details four common missteps that can hinder your journey to the cloud. One such mistake is not having a cloud migration strategy.

Check out the full article on the Modern Distribution Management (MDM) site to learn about other common mistakes, their impacts, and ways to avoid them.

Plan Your Move: Three Tips For Efficient Cloud Migrations (Source: Forbes)
Think about the last time you moved to a new place. Moving is usually exciting, but the logistics can get complicated. The same can be said for moving to the cloud.

Just as a well-planned move is often the smoothest, the same holds true for cloud migrations.

As you’re packing up your data and workloads to transition business services to the cloud, check out this article on Forbes for three best practices for cloud migration planning.

(Bonus resource: Check out our Ten Steps to Cloud Migration post. If your company is considering making the move, these steps will help!)

Cloud Management

How to Improve Cloud Management (Source: DevOps)
The emergence of technologies like AI and IoT as well as the spike in remote work due to the COVID-19 pandemic have accelerated cloud adoption.

With this growth comes a need for a cloud management strategy in order to avoid unnecessarily high costs and security or compliance violations. This DevOps article shares insights on how to build a successful cloud management strategy.

The Challenges of Cloud Data Management (Source: TechTarget)
Cloud spend and the amount of data in the cloud continues to grow at an unprecedented rate. This rapid expansion is causing organizations to also face new cloud management challenges as they try to keep up with cloud data management advancements.

Head over to TechTarget to learn about cloud management challenges, including data governance and adhering to regulatory compliance frameworks.

Spark

Spark: A Data Engineer’s Best Friend (Source: CIO)
Spark is the ultimate tool for data engineers. It simplifies the work environment by providing a platform to organize and execute complex data pipelines and powerful tools for storing, retrieving, and transforming data.

This CIO article describes different things data engineers can do with Spark, touches on what makes Spark unique, and explains why it is so beneficial for data engineers.

Is There Life After Hadoop? The Answer is a Resounding Yes. (Source: CIO)
Many organizations who invested heavily in the Hadoop ecosystem have found themselves wondering what life after Hadoop is like and what lies ahead.

This article addresses life after Hadoop and lays out a strategy for organizations entering the post-Hadoop era, including reasons why you may want to embrace Spark as an alternative. Head to the CIO site for more!

Databricks

5 Ways to Boost Query Performance with Databricks and Spark (Source: Key2 Consulting)
When running Spark jobs on Databricks, do you often find yourself frustrated by slow query times?

Check out this article from Key2 Consulting to discover 5 rules for speeding up query times. The rules include:

  • Cache intermediate big dataframes for repetitive use.
  • Monitor the Spark UI within a cluster where a Spark job is running.

For more information on these rules and to find out the remaining three, check out the full article.

What is a Data Lakehouse and Why Should You Care? (Source: S&P Global)
A data lakehouse is an environment designed to combine the data structure and data management features of a data warehouse with the low-cost storage of a data lake.

Databricks offers a couple data lakehouses, including Delta Lake and Delta Engine. This article from S&P Global, gives a more comprehensive explanation of what a data lakehouse is, its benefits, and what lakehouses you can use on Databricks.

Amazon EMR

Data Management on the Cloud Leveraging AWS (Source: CIO)
As data volumes grow and managing multiple types of data becomes more complex, organizations require a well-considered cloud migration strategy for cost efficiencies and scale.

In some cases, when migrating to the cloud it may be beneficial to retain certain types of data on-premises due to regulatory requirements. In this case, Amazon EMR is useful to manage Hadoop clusters in the cloud.

This CIO article goes over different data management services provided by AWS that can help migrate and manage data on the cloud, including Amazon EMR.

What is Amazon EMR? – Amazon Elastic MapReduce Tutorial (Source: ADMET)
AWS EMR is among the hottest clouds and massive data-based platforms. It gives a supervised structure for simply, cost-effectively, and securely working information processing frameworks.

In this ADMET blog, learn what Amazon Elastic MapReduce is and how it can be used to deal with a variety of issues.

DataOps

3 Steps for Successfully Implementing Industrial DataOps (Source: eWeek)
DataOps has been growing in popularity over the past few years. Today, we see many industrial operations realizing the value of DataOps.

This article explains three steps for successfully implementing industrial DataOps:

1. Make industrial data available
2. Make data useful
3. Make data valuable

Head over to eWeek for a deeper dive into the benefits of implementing industrial DataOps and what these three steps really mean.

Using DataOps To Maximize Value For Your Business (Source: Forbes)
Everybody is talking about artificial intelligence and data, but how do you make it real for your business? That’s where DataOps comes in.

From this Forbes article, learn how DataOps can be used to solve common business challenges, including:

  • A process mismatch between traditional data management and newer techniques such as AI.
  • A lack of collaboration to drive a successful cultural shift and support operational readiness.
  • Unclear approach to measure success across the organization.

In Conclusion

Knowledge is power! We hope our data community enjoys these resources and they provide valuable insights to help you in your current role and beyond.

Be sure to visit our library of resources on DataOps, Cloud Migration, Cloud Management (and more) for best practices, happenings, and expert tips and techniques. If you want to know more about Unravel Data, you can sign up for a free trial or contact us.