obeleask

There are many ways to get around this issue. Alerts/notifications based on thresholds being exceeded is one. Another is to start with a dashboard that highlights the major issues for you to look at. Another is to have a marker/icon next to any figure that needs your attention (ala Stephen Few style).

There is nothing wrong with investigative analytics. I'm not saying slice and dice is a bad thing - just there are much better ways to open your BI demo.

Seriously, who would pitch "it’s worth bridging because it’s a small technical team and they can probably soft land if this doesn't work out" to an investor?

On a venn diagram of electric cars, good looking cars, and cars that can do more than 100 miles on a charge, why is that the overlap area is still the Tesla by itself? If there was a more affordable Telsa, sales would be insane, yet we keep getting more ugly, tiny-range cars with limited appeal.

I think the article misses on all the biggest benefits I had working at a BigCo:

1) You can actually get to work with a lot of companies. We acquired a ton of companies over the years, and I'd often go work in those companies post acquisition while it was still being run as a separate company. So these were smaller companies that were generally successful - you got to see a lot of different practices.

2) Once you are done learning a new job/role (or new company as above), you can easily get the opportunity to move to around to different departments or jobs. I personally did consulting, product management, engineering, architecture, sales operations and strategy (sometimes for the mothership, sometimes for the acquired companies).

3) It's not about smart people I wouldn't say - its about mentors. At a small company, there are just less senior people around, and they are often more focused on delivering. At a big company, more senior execs are really willing and able to mentor the superstars in their teams that make them look good. You combine that with moving about companies or departments, and you get a mix of different mentors with different styles and strengths.

4) It won't apply to everyone, but I personally must have evaluated 50 - 100 companies for M&A or partnerships. I know exactly how to analyze a business, where to look for skeletons, what works well/what doesn't, what a big company will look for (and what are red flags) in an acquisition, when you can/can't get a partnership and what you can use to your advantage in negotiations, etc. Will all be extremely useful skills when you're on the other side of the table.

Between the above things, you can learn so much. Stuff like the food/work environmental is so irrelevant compared to this.

Don't get me wrong - I have no intentions of ever going back to a big company again. But these were the big benefits for me.

And here I was thinking they had found an Australian Planet...

http://www.urbandictionary.com/define.php?term=true%20blue

I'm looking at that page right now and don't see it. I see the chart of views, the text "How many times you appeared in LinkedIn Search", with the total number of hits displayed and the counter showing the weekly change next to (as I can see in your screenshot in the blog). But there is nothing below that.

And I meant to say nice job too... good post :-)

The article says "How many times section can be found in the lower right" under who has viewed your profile. I don't see this? Is it a premium account feature only? Article says it's free...

Sometimes your roadmap is for sale, it happens (http://www.bothsidesofthetable.com/2013/04/15/how-to-sell-yo...). But you know when to say yes by having: 1) A vision of what your product is going to become 2) Understanding of your customers and your market

Only when these things intersect do you say yes.

Nice work. This would have been a nice tool to use when i was working with Neo4j. We had to roll our own for what we needed.

Some minor feedback since I know it's just a demo... but I think it would be more intuitive if when you "X" (remove) the facets in the search bar, the resulting nodes are removed too. I know this could get tricky given you can click a node to expand it, so you aren't visualizing only what was searched on - but some may find it confusing why removing the facets doesn't do anything.

As a car guy, maybe I am biased, but:

1) Where are the data/charts behind this statement: "Part of the explanation certainly lies in the recession, because cash-strapped Americans could not afford new cars, and the unemployed weren’t going to work anyway. But by many measures the decrease in driving preceded the downturn and appears to be persisting now that recovery is under way. " If the whole premise of the article is that this is more than just something related to the recession, shouldn't we be able to see that data for ourselves, and the justification should be more than a passing statement. The wording of "by many measures" also makes it sound like the author is cherry picking metrics to make his point. I'd also like to see the car usage compared to unemployment rates for the same age group. Overall, I just don't believe the validity of the claim without seeing more data.

2) As the author says "Whether members of the millennial generation will start buying more cars once they have kids to take to soccer practice and school plays remains an open question." I'm not sure it is an open question. When you're single and can live near where you work, it's reasonable to get on without a car. Then life changes, and you need a car.

3) If there is an actual drop-off in car usage, then it could be because we likely are at an inflection point of some significant changes in the industry. The two big ones being electric cars with Tesla leading the way, and the second one being self-driving cars with Google leading the way. We might just be seeing a temporary drop as people reject the "old" way, and as these two new technologies take-off and become more mainstream, so again will car usage .