With so much packed into the latest Yellowfin 9 release, we figured it would be great to let you know about some of the coolest features (which will really transform how you do analytics!) in this series of blog posts - Fresh Features. At Yellowfin, we’re super excited that you will be benefiting from the huge amount of work our development team have been doing behind the scenes to complete revamp Yellowfin’s look, feel, and functionality.
In 2019 we spent a great deal of time visiting developers that use Bitrise, traveling around the globe with cross-functional teams, and continued talking to a lot of companies developing mobile apps. We also regularly analyzed a ton of behavioral data to understand how we could improve Bitrise to give the best experience for mobile developers. We've drawn our conclusions and thought it would be interesting to break them down into numbers and share the big picture with you.
Modern enterprises require a host of applications to manage their bookkeeping, inventory, marketing, and more. Finding powerful applications to cover these needs isn’t very difficult, but building the integrations that synchronize data between these solutions can be costly and labor-intensive while requiring enormous amounts of technical expertise. This is where Integration Platform as a Service (iPaaS) technology can help.
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.
A long time ago (in April 2019), in a galaxy far far away (in Tel Aviv, Planet Earth) we launched a self-serve option. Users could now sign up to Rookout without having to contact us first. We invested significant resources in online promotion and -- just like any startup at our stage -- we hoped to soon see legions of users signing up and using the tool to fetch data directly from their code.
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.
