A Quote by Ruchi Sanghvi
Dropbox looks really simple to the end user and is extremely magical and just works. But under the hood, the complexity of the technology is huge. The amount of work it requires to store, scale and move this data is pretty intense.
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I also thought the music was a huge contribution, in terms of creating the scale of that. And, I was impressed with just how natural and fluid the world looks. The world is so artificial and it requires so much work to make all the different pieces add up together, but when it comes together, it just looks effortless. It's amazing.
The team was unbelievable, and Dropbox was a really easy, simple-to-use product. Both Aditya and I believe this is the technology company we want to be working at now, and it has the potential to be the next big technology company.
For years I thought I was just a writer, but when I sat down to design and started playing around with it, I realized that, really, it's pretty easy. Obviously it's more than just a set of rules, but the basics of design are actually pretty simple and quite mathematical. The link between data and design works at quite a fundamental level.
MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.
Flexible working is not just for women with children. It is necessary at the other end of the scale. If people can move into part-time work, instead of retirement, then that will be a huge help. If people can fit their work around caring responsibilities for the elderly, the disabled, then again that's very positive.
Dropbox sweats the user experience details as commendably as it masters the considerable engineering challenges required to reliably sync files everywhere a user may need them.
For the user, it doesn't matter whether he is getting access on Wi-Fi, 3G or 2G networks. What matters is good connectivity, and as a technology provider, our job is to hide the complexity of the technology.
People who bet against the Internet, who think that somehow this change is just a generational shift, miss that it is a fundamental reorganizing of the power of the end user. The Internet brings tremendous tools to the end user, and that end user is going to use them.
The creative folks intuitively design what's best for the user, while data folks provide great insights. The true unicorns are those who can go end-to-end designing, building, measuring, analyzing, and iterating with a combination of user intuition and deep analytics.
It's unfair to expect the USTA, just because they make this pot of money, to just snap their fingers and make champions. It's not simple, and anyone who thinks it is hasn't really looked underneath the hood to see how the engine works.
I don't think I would live outside of the Northwest. I think the quality of life in Portland is really good. People move from intense, high-powered jobs, and move to Portland, work half as much and live twice as good. They can afford bigger houses, or they can actually afford to buy a house, they can work the minimal amount and still get by. I think there's a really strong sense of community there. It's beautiful.
I want to make sure I have a system that allows me to know that the platoon sergeant and platoon commander aren't going to move at the same time when we come back from deployment. That sounds pretty simple, but it's really about data.
It takes a huge amount of effort to move from a successful high-tech prototype to broader adoption of an imaging technology.
Hard numbers tell an important story; user stats and sales numbers will always be key metrics. But every day, your users are sharing a huge amount of qualitative data, too - and a lot of companies either don't know how or forget to act on it.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Every application has an inherent amount of irreducible complexity. The only question is who will have to deal with it, the user or the developer (programmer or engineer).
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