Armed with a Ph.D. from UC San Diego, our guest started off with internships at Google and Microsoft before gaining valuable experience as a VP and a highly sought-after consultant for startups and SMBs. Now he’s one of the world’s foremost experts on wrangling vast data sets and maximizing efficiency.

In the past couple of months, after nearly a decade of huge returns and steady growth, the tech industry has officially slowed down. Companies are tightening their belts — laying off employees, freezing spending, and lowering budgets. If you work in tech right now, it’s likely you’ve felt it.

DevOps helps developers and operators work together to create high-quality software quickly. DevOps is a modern software development philosophy that uses various tools, processes, and people to get ideal results rapidly. As a result, companies that use DevOps satisfy customer needs, achieving a competitive advantage.

The Snowflake data cloud provides storage, reporting, and analytics for organizations that rely on their data to run their day-to-day operations. Snowflake has become a top data warehouse solution for its manageability, superior scalability, always-on data security, advanced analytics, and robust accessibility since its launch from stealth mode in 2014. But Snowflake isn't perfect. For example, Snowflake is a cloud-only solution, so it might not be the best choice for organizations with on-premises data.

Most companies today have a “cloud first” computing strategy. According to Foundry’s April 2022 report outlining their 2022 Cloud Computing research, 92% of businesses globally have moved to the cloud. What’s more, the percentage of companies with most or all of their IT infrastructure in the cloud is expected to leap from 41% today to 63% in the next 18 months. As companies move more workloads onto various cloud platforms, cloud budgets continue to increase.

In part one of this two-part blog post, we began our deep dive into Apache Spark tuning to optimize resources. We looked at what is involved in executor and partition sizing, particularly choosing the number of partitions and choosing an executor size. After establishing some principles of optimization here, we ended by asking an important question: Is it really practical for all applications to be optimized? As our recent State of the Market report helped reveal, the answer is two-sided. The good news?

Whether you’re a product manager, a marketing organization, or in finance, you’re probably using the cloud in some way. But many businesses are still immature when it comes to building systems in the cloud, especially when it comes to how they use their financial resources. Here, CloudZero founder and CTO Erik Peterson breaks down the responsibility of using the cloud, how to break down the costs of cloud computing, and what you need to do to change the conversation from cost to profit.

As our recent survey showed, Apache Spark is poised to continue as big data’s most dominant large-scale big data processing platform. Thus it is imperative that Spark users learn and master Spark tuning if they want to get the most out of their Spark environments. But what is tuning in Spark? How is it done? Read on to know more about Spark tuning.

One of the best ways to achieve efficient product development is to make sure everyone involved with a project is on the same page, working toward the same ultimate goals. However, this is harder to do than it sounds. Engineering and product teams bring very different priorities to the table, and establishing which priorities to focus on first often becomes a matter of debate.