Like many other people, I used time over the recent holidays to clean out and organize my digital files. In that process, I finally trashed the speaking notes for a panel I participated in at SMA’s (Strategy Meets Action) first summit in 2012 when I worked at a large global insurer. During that session, a gentleman in the audience asked me what I thought about “big data” and its implications for Insurance.
One of the core reasons that organizations invest in analytic solutions is because they want to get everyone in their organization on the same page. They want everyone to understand what's happening and why it's happening so that individuals know what they need to do to be successful and drive outcomes for the organization.
Let’s try to figure out what happens with the application when the source file is much bigger than the available memory. The memory in the below tests is limited to 900MB […]. Naively we could think that a file bigger than available memory will fail the processing with OOM memory error. And this supposition is true.
In this post, we’ll look into tried and true methods of improving Rails view performance. Specifically, I will focus on database efficiency, view manipulation, and caching. I think the phrase “premature optimization is the root of all evil” has been taken a little out of context. I’ve often heard developers use this during code reviews when simple optimization techniques are pointed out.
Many of us have experienced the feeling of hopelessly digging through log files on multiple servers to fix a critical production issue. We can probably all agree that this is far from ideal. Locating and searching log files is even more challenging when dealing with real-time processing applications where the debugging process itself can be extremely time-sensitive.
The opportunity to create new economic, social and environmental value by unlocking the “good” in data is immense. While the problems we face as a society may be getting harder to solve, the advances we can make when we break down the silos between the physical and digital worlds are profound.
Once upon a time there was only one way to use Apache Spark but support for additional programming languages and APIs have been introduced in recent times. A novice can be confused by the different options that have become available since Spark 1.6 and intimidated by the idea of setting up a project to explore these APIs.
After a full year of development since our last major open source release, we are proud to announce the next chapter of our flagship open-source API gateway — Kong Gateway 2.0 is generally available! With this release, Kong will become more operationally agnostic for large-scale deployments across on-premises and multi-cloud environments, thanks to the new Hybrid Mode. In addition, plugin development also becomes more language agnostic, thanks to the new Golang PDK support.
In this post, we're going to look at what Shared-Nothing Architecture is, along with its benefits and downsides, concerning PHP and its impact on performance. Several different languages can be used for web-based application development, most of which you are likely already familiar. The most popular of these are JavaScript, Ruby, Python, Java, Go, R, and, of course, PHP. Of these languages, however, only PHP uses a Shared-Nothing Architecture by default.
Where did the last decade go? Seems like it was just 2010 and I was writing about the future of business in 2020, well it is nowhere! I’ve spent much of my career in finance/accounting and management consulting and the last decade+ helping companies link their business and technology strategies with a focus on data and analytics. Where will we head in 2020 and this next decade?
