Tag Archives: cars

NTSB Investigation of Fatal Driverless Car Accident

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/11/ntsb_investigat.html

Autonomous systems are going to have to do much better than this.

The Uber car that hit and killed Elaine Herzberg in Tempe, Ariz., in March 2018 could not recognize all pedestrians, and was being driven by an operator likely distracted by streaming video, according to documents released by the U.S. National Transportation Safety Board (NTSB) this week.

But while the technical failures and omissions in Uber’s self-driving car program are shocking, the NTSB investigation also highlights safety failures that include the vehicle operator’s lapses, lax corporate governance of the project, and limited public oversight.

The details of what happened in the seconds before the collision are worth reading. They describe a cascading series of issues that led to the collision and the fatality.

As computers continue to become part of things, and affect the world in a direct physical manner, this kind of thing will become even more important.

Detecting Credit Card Skimmers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/08/detecting_credi_1.html

Modern credit card skimmers hidden in self-service gas pumps communicate via Bluetooth. There’s now an app that can detect them:

The team from the University of California San Diego, who worked with other computer scientists from the University of Illinois, developed an app called Bluetana which not only scans and detects Bluetooth signals, but can actually differentiate those coming from legitimate devices — like sensors, smartphones, or vehicle tracking hardware — from card skimmers that are using the wireless protocol as a way to harvest stolen data. The full details of what criteria Bluetana uses to differentiate the two isn’t being made public, but its algorithm takes into account metrics like signal strength and other telltale markers that were pulled from data based on scans made at 1,185 gas stations across six different states.

License Plate "NULL"

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/08/license_plate_n.html

There was a DefCon talk by someone with the vanity plate “NULL.” The California system assigned him every ticket with no license plate: $12,000.

Although the initial $12,000-worth of fines were removed, the private company that administers the database didn’t fix the issue and new NULL tickets are still showing up.

The unanswered question is: now that he has a way to get parking fines removed, can he park anywhere for free?

And this isn’t the first time this sort of thing has happened. Wired has a roundup of people whose license places read things like “NOPLATE,” “NO TAG,” and “XXXXXXX.”

Modifying a Tesla to Become a Surveillance Platform

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/08/modifying_a_tes.html

From DefCon:

At the Defcon hacker conference today, security researcher Truman Kain debuted what he calls the Surveillance Detection Scout. The DIY computer fits into the middle console of a Tesla Model S or Model 3, plugs into its dashboard USB port, and turns the car’s built-in cameras­ — the same dash and rearview cameras providing a 360-degree view used for Tesla’s Autopilot and Sentry features­ — into a system that spots, tracks, and stores license plates and faces over time. The tool uses open source image recognition software to automatically put an alert on the Tesla’s display and the user’s phone if it repeatedly sees the same license plate. When the car is parked, it can track nearby faces to see which ones repeatedly appear. Kain says the intent is to offer a warning that someone might be preparing to steal the car, tamper with it, or break into the driver’s nearby home.

Another Attack Against Driverless Cars

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/07/another_attack_.html

In this piece of research, attackers successfully attack a driverless car system — Renault Captur’s “Level 0” autopilot (Level 0 systems advise human drivers but do not directly operate cars) — by following them with drones that project images of fake road signs in 100ms bursts. The time is too short for human perception, but long enough to fool the autopilot’s sensors.

Boing Boing post.

Adversarial Machine Learning against Tesla’s Autopilot

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/04/adversarial_mac.html

Researchers have been able to fool Tesla’s autopilot in a variety of ways, including convincing it to drive into oncoming traffic. It requires the placement of stickers on the road.

Abstract: Keen Security Lab has maintained the security research work on Tesla vehicle and shared our research results on Black Hat USA 2017 and 2018 in a row. Based on the ROOT privilege of the APE (Tesla Autopilot ECU, software version 18.6.1), we did some further interesting research work on this module. We analyzed the CAN messaging functions of APE, and successfully got remote control of the steering system in a contact-less way. We used an improved optimization algorithm to generate adversarial examples of the features (autowipers and lane recognition) which make decisions purely based on camera data, and successfully achieved the adversarial example attack in the physical world. In addition, we also found a potential high-risk design weakness of the lane recognition when the vehicle is in Autosteer mode. The whole article is divided into four parts: first a brief introduction of Autopilot, after that we will introduce how to send control commands from APE to control the steering system when the car is driving. In the last two sections, we will introduce the implementation details of the autowipers and lane recognition features, as well as our adversarial example attacking methods in the physical world. In our research, we believe that we made three creative contributions:

  1. We proved that we can remotely gain the root privilege of APE and control the steering system.
  2. We proved that we can disturb the autowipers function by using adversarial examples in the physical world.
  3. We proved that we can mislead the Tesla car into the reverse lane with minor changes on the road.

You can see the stickers in this photo. They’re unobtrusive.

This is machine learning’s big problem, and I think solving it is a lot harder than many believe.

Zipcar Disruption

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/03/zipcar_disrupti.html

This isn’t a security story, but it easily could have been. Last Saturday, Zipcar had a system outage: “an outage experienced by a third party telecommunications vendor disrupted connections between the company’s vehicles and its reservation software.”

That didn’t just mean people couldn’t get cars they reserved. Sometimes is meant they couldn’t get the cars they were already driving to work:

Andrew Jones of Roxbury was stuck on hold with customer service for at least a half-hour while he and his wife waited inside a Zipcar that would not turn back on after they stopped to fill it up with gas.

“We were just waiting and waiting for the call back,” he said.

Customers in other states, including New York, California, and Oregon, reported a similar problem. One user who tweeted about issues with a Zipcar vehicle listed his location as Toronto.

Some, like Jones, stayed with the inoperative cars. Others, including Tina Penman in Portland, Ore., and Heather Reid in Cambridge, abandoned their Zipcar. Penman took an Uber home, while Reid walked from the grocery store back to her apartment.

This is a reliability issue that turns into a safety issue. Systems that touch the direct physical world like this need better fail-safe defaults.

"Two Stage" BMW Theft Attempt

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/08/two_stage_bmw_t.html

Modern cars have alarm systems that automatically connect to a remote call center. This makes cars harder to steal, since tripping the alarm causes a quick response. This article describes a theft attempt that tried to neutralize that security system. In the first attack, the thieves just disabled the alarm system and then left. If the owner had not immediately repaired the car, the thieves would have returned the next night and — no longer working under time pressure — stolen the car.

Raspberry Pi as car computer

Post Syndicated from Liz Upton original https://www.raspberrypi.org/blog/raspberry-pi-as-car-computer/

Carputers! Fabrice Aneche is documenting his ongoing build, which equips an older (2011) car with some of the features a 2018 model might have: thus far, a reversing camera (bought off the shelf, with a modified GUI to show the date and the camera’s output built with Qt and Golang), GPS and offline route guidance.

rearcam

We’re not sure how the car got through that little door there.

It was back in 2013, when the Raspberry Pi had been on the market for about a year, that we started to see carputer projects emerge. They tended to be focussed in two directions: in-car entertainment, and on-board diagnostics (OBD). We ended up hiring the wonderful Martin O’Hanlon, who wrote up the first OBD project we came across, just this year. Being featured on this blog can change your life, I tell you.

In the last five years, the Pi’s evolved: you’re now working with a lot more processing power, there’s onboard WiFi, and far more peripherals which can be useful in a…vehicular context are available. Consequently, the flavour of the car projects we’re seeing has changed somewhat, with navigation systems and cameras much more visible. Fabrice’s is one of the best examples we’ve found.

solarised map

Night-view navigation system

GPS is all very well, but you, the human person driver, will want directions at every turn. So Fabrice wrote a user interface to serve up live maps and directions, mostly in Qt5 and QML (he’s got some interesting discussion on his website about why he stopped using X11, which turned out to be too slow for his needs). All the non-QML work is done in Go. It’s all open-source, and on GitHub, if you’d like to contribute or roll your own project. He’s also worked over the Linux GPS daemons, found them lacking, and has produced his own:

…the Linux gps daemons are using obscure and over complicated protocols so I’ve decided to write my own gps daemon in Go using a gRPC stream interface. You can find it here.

I’m also not satisfied with the map matching of OSRM for real time display, I may rewrite one using mbmatch.

street map display

We’ll be keeping an eye on this project; given how much clever has gone into it already, we’re pretty sure that Fabrice will be adding new features. Thanks Fabrice!

The post Raspberry Pi as car computer appeared first on Raspberry Pi.

Gas Pump Hack

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/07/gas_pump_hack.html

This is weird:

Police in Detroit are looking for two suspects who allegedly managed to hack a gas pump and steal over 600 gallons of gasoline, valued at about $1,800. The theft took place in the middle of the day and went on for about 90 minutes, with the gas station attendant unable to thwart the hackers.

The theft, reported by Fox 2 Detroit, took place at around 1pm local time on June 23 at a Marathon gas station located about 15 minutes from downtown Detroit. At least 10 cars are believed to have benefitted from the free-flowing gas pump, which still has police befuddled.

Here’s what is known about the supposed hack: Per Fox 2 Detroit, the thieves used some sort of remote device that allowed them to hijack the pump and take control away from the gas station employee. Police confirmed to the local publication that the device prevented the clerk from using the gas station’s system to shut off the individual pump.

Slashdot post.

Hard to know what’s true, but it seems like a good example of a hack against a cyber-physical system.

Welcome Jack — Data Center Tech

Post Syndicated from Yev original https://www.backblaze.com/blog/welcome-jack-data-center-tech/

As we shoot way past 500 petabytes of data stored, we need a lot of helping hands in the data center to keep those hard drives spinning! We’ve been hiring quite a lot, and our latest addition is Jack. Lets learn a bit more about him, shall we?

What is your Backblaze Title?
Data Center Tech

Where are you originally from?
Walnut Creek, CA until 7th grade when the family moved to Durango, Colorado.

What attracted you to Backblaze?
I had heard about how cool the Backblaze community is and have always been fascinated by technology.

What do you expect to learn while being at Backblaze?
I expect to learn a lot about how our data centers run and all of the hardware behind it.

Where else have you worked?
Garrhs HVAC as an HVAC Installer and then Durango Electrical as a Low Volt Technician.

Where did you go to school?
Durango High School and then Montana State University.

What’s your dream job?
I would love to be a driver for the Audi Sport. Race cars are so much fun!

Favorite place you’ve traveled?
Iceland has definitely been my favorite so far.

Favorite hobby?
Video games.

Of what achievement are you most proud?
Getting my Eagle Scout badge was a tough, but rewarding experience that I will always cherish.

Star Trek or Star Wars?
Star Wars.

Coke or Pepsi?
Coke…I know, it’s bad.

Favorite food?
Thai food.

Why do you like certain things?
I tend to warm up to things the more time I spend around them, although I never really know until it happens.

Anything else you’d like to tell us?
I’m a friendly car guy who will always be in love with my European cars and I really enjoy the Backblaze community!

We’re happy you joined us Out West! Welcome aboard Jack!

The post Welcome Jack — Data Center Tech appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

The devil wears Pravda

Post Syndicated from Robert Graham original https://blog.erratasec.com/2018/05/the-devil-wears-pravda.html

Classic Bond villain, Elon Musk, has a new plan to create a website dedicated to measuring the credibility and adherence to “core truth” of journalists. He is, without any sense of irony, going to call this “Pravda”. This is not simply wrong but evil.

Musk has a point. Journalists do suck, and many suck consistently. I see this in my own industry, cybersecurity, and I frequently criticize them for their suckage.

But what he’s doing here is not correcting them when they make mistakes (or what Musk sees as mistakes), but questioning their legitimacy. This legitimacy isn’t measured by whether they follow established journalism ethics, but whether their “core truths” agree with Musk’s “core truths”.

An example of the problem is how the press fixates on Tesla car crashes due to its “autopilot” feature. Pretty much every autopilot crash makes national headlines, while the press ignores the other 40,000 car crashes that happen in the United States each year. Musk spies on Tesla drivers (hello, classic Bond villain everyone) so he can see the dip in autopilot usage every time such a news story breaks. He’s got good reason to be concerned about this.

He argues that autopilot is safer than humans driving, and he’s got the statistics and government studies to back this up. Therefore, the press’s fixation on Tesla crashes is illegitimate “fake news”, titillating the audience with distorted truth.

But here’s the thing: that’s still only Musk’s version of the truth. Yes, on a mile-per-mile basis, autopilot is safer, but there’s nuance here. Autopilot is used primarily on freeways, which already have a low mile-per-mile accident rate. People choose autopilot only when conditions are incredibly safe and drivers are unlikely to have an accident anyway. Musk is therefore being intentionally deceptive comparing apples to oranges. Autopilot may still be safer, it’s just that the numbers Musk uses don’t demonstrate this.

And then there is the truth calling it “autopilot” to begin with, because it isn’t. The public is overrating the capabilities of the feature. It’s little different than “lane keeping” and “adaptive cruise control” you can now find in other cars. In many ways, the technology is behind — my Tesla doesn’t beep at me when a pedestrian walks behind my car while backing up, but virtually every new car on the market does.

Yes, the press unduly covers Tesla autopilot crashes, but Musk has only himself to blame by unduly exaggerating his car’s capabilities by calling it “autopilot”.

What’s “core truth” is thus rather difficult to obtain. What the press satisfies itself with instead is smaller truths, what they can document. The facts are in such cases that the accident happened, and they try to get Tesla or Musk to comment on it.

What you can criticize a journalist for is therefore not “core truth” but whether they did journalism correctly. When such stories criticize “autopilot”, but don’t do their diligence in getting Tesla’s side of the story, then that’s a violation of journalistic practice. When I criticize journalists for their poor handling of stories in my industry, I try to focus on which journalistic principles they get wrong. For example, the NYTimes reporters do a lot of stories quoting anonymous government sources in clear violation of journalistic principles.

If “credibility” is the concern, then it’s the classic Bond villain here that’s the problem: Musk himself. His track record on business statements is abysmal. For example, when he announced the Model 3 he claimed production targets that every Wall Street analyst claimed were absurd. He didn’t make those targets, he didn’t come close. Model 3 production is still lagging behind Musk’s twice adjusted targets.

https://www.bloomberg.com/graphics/2018-tesla-tracker/

So who has a credibility gap here, the press, or Musk himself?

Not only is Musk’s credibility problem ironic, so is the name he chose, “Pravada”, the Russian word for truth that was the name of the Soviet Union Communist Party’s official newspaper. This is so absurd this has to be a joke, yet Musk claims to be serious about all this.

Yes, the press has a lot of problems, and if Musk were some journalism professor concerned about journalists meeting the objective standards of their industry (e.g. abusing anonymous sources), then this would be a fine thing. But it’s not. It’s Musk who is upset the press’s version of “core truth” does not agree with his version — a version that he’s proven time and time again differs from “real truth”.

Just in case Musk is serious, I’ve already registered “www.antipravda.com” to start measuring the credibility of statements by billionaire playboy CEOs. Let’s see who blinks first.


I stole the title, with permission, from this tweet:

Brutus 2: the gaming PC case of your dreams

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/brutus-2-gaming-pc-case/

Attention, case modders: take a look at the Brutus 2, an extremely snazzy computer case with a partly transparent, animated side panel that’s powered by a Pi. Daniel Otto and Carsten Lehman have a current crowdfunder for the case; their video is in German, but the looks of the build speak for themselves. There are some truly gorgeous effects here.

der BRUTUS 2 by 3nb Gaming

Vorbestellungen ab sofort auf https://www.startnext.com/brutus2 Weitere Infos zu uns auf: https://3nb.de https://www.facebook.com/3nb.de https://www.instagram.com/3nb.de Über 3nb: – GbR aus Leipzig, gegründet 2017 – wir kommen aus den Bereichen Elektronik und Informatik – erstes Produkt: der Brutus One ein Gaming PC mit transparentem Display in der Seite Kurzinfo Brutus 2: – Markencomputergehäuse für Gaming- /Casemoddingszene – Besonderheit: animiertes Seitenfenster angesteuert mit einem Raspberry Pi – Vorteile von unserem Case: o Case ist einzeln lieferbar und nicht nur als komplett-PC o kein Leistungsverbrauch der Grafikkarte dank integriertem Raspberry Pi o bessere Darstellung von Texten und Grafiken durch unscharfen Hintergrund

What’s case modding?

Case modding just means modifying your computer or gaming console’s case, and it’s very popular in the gaming community. Some mods are functional, while others improve the way the case looks. Lots of dedicated gamers don’t only want a powerful computer, they also want it to look amazing — at home, or at LAN parties and games tournaments.

The Brutus 2 case

The Brutus 2 case is made by Daniel and Carsten’s startup, 3nb electronics, and it’s a product that is officially Powered by Raspberry Pi. Its standout feature is the semi-transparent TFT screen, which lets you play any video clip you choose while keeping your gaming hardware on display. It looks incredibly cool. All the graphics for the case’s screen are handled by a Raspberry Pi, so it doesn’t use any of your main PC’s GPU power and your gaming won’t suffer.

Brutus 2 PC case powered by Raspberry Pi

The software

To use Brutus 2, you just need to run a small desktop application on your PC to choose what you want to display on the case. A number of neat animations are included, and you can upload your own if you want.

So far, the app only runs on Windows, but 3nb electronics are planning to make the code open-source, so you can modify it for other operating systems, or to display other file types. This is true to the spirit of the case modding and Raspberry Pi communities, who love adapting, retrofitting, and overhauling projects and code to fit their needs.

Brutus 2 PC case powered by Raspberry Pi

Daniel and Carsten say that one of their campaign’s stretch goals is to implement more functionality in the Brutus 2 app. So in the future, the case could also show things like CPU temperature, gaming stats, and in-game messages. Of course, there’s nothing stopping you from integrating features like that yourself.

If you have any questions about the case, you can post them directly to Daniel and Carsten here.

The crowdfunding campaign

The Brutus 2 campaign on Startnext is currently halfway to its first funding goal of €10000, with over three weeks to go until it closes. If you’re quick, you still be may be able to snatch one of the early-bird offers. And if your whole guild NEEDS this, that’s OK — there are discounts for bulk orders.

The post Brutus 2: the gaming PC case of your dreams appeared first on Raspberry Pi.

Infamous ‘Kodi Box’ Case Sees Man Pay Back Just £1 to the State

Post Syndicated from Andy original https://torrentfreak.com/infamous-kodi-box-case-sees-man-pay-back-just-1-to-the-state-180507/

In 2015, Middlesbrough-based shopkeeper Brian ‘Tomo’ Thompson shot into the headlines after being raided by police and Trading Standards in the UK.

Thompson had been selling “fully-loaded” piracy-configured Kodi boxes from his shop but didn’t think he’d done anything wrong.

“All I want to know is whether I am doing anything illegal. I know it’s a gray area but I want it in black and white,” he said.

Thompson started out with a particularly brave tone. He insisted he’d take the case to Crown Court and even to the European Court. His mission was show what was legal and what wasn’t, he said.

Very quickly, Thompson’s case took on great importance, with observers everywhere reporting on a potential David versus Goliath copyright battle for the ages. But Thompson’s case wasn’t straightforward.

The shopkeeper wasn’t charged with basic “making available” under the Copyrights, Designs and Patents Acts that would have found him guilty under the earlier BREIN v Filmspeler case. Instead, he stood accused of two offenses under section 296ZB of the Copyright, Designs and Patents Act, which deals with devices and services designed to “circumvent technological measures”.

In the end it was all moot. After entering his official ‘not guilty’ plea, last year Thompson suddenly changed his tune. He accepted the prosecution’s version of events, throwing himself at the mercy of the court with a guilty plea.

In October 2017, Teeside Crown Court heard that Thompson cost Sky around £200,000 in lost subscriptions while the shopkeeper made around £38,500 from selling the devices. But despite the fairly big numbers, Judge Peter Armstrong decided to go reasonably light on the 55-year-old, handing him an 18-month prison term, suspended for two years.

“I’ve come to the conclusion that in all the circumstances an immediate custodial sentence is not called for. But as a warning to others in future, they may not be so lucky,” the Judge said.

But things wouldn’t end there for Thompson.

In the UK, people who make money or obtain assets from criminal activity can be forced to pay back their profits, which are then confiscated by the state under the Proceeds of Crime Act (pdf). Almost anything can be taken, from straight cash to cars, jewellery and houses.

However, it appears that whatever cash Thompson earned from Kodi Box activities has long since gone.

During a Proceeds of Crime hearing reported on by Gazette Live, the Court heard that Thompson has no assets whatsoever so any confiscation order would have to be a small one.

In the end, Judge Simon Hickey decided that Thompson should forfeit a single pound, an amount that could increase if the businessman got lucky moving forward.

“If anything changes in the future, for instance if you win the lottery, it might come back,” the Judge said.

With that seeming particularly unlikely, perhaps this will be the end for Thompson. Considering the gravity and importance placed on his case, zero jail time and just a £1 to pay back will probably be acceptable to the 55-year-old and also a lesson to the authorities, who have gotten very little out of this expensive case.

Who knows, perhaps they might sum up the outcome using the same eight-letter word that Thompson can be seen half-covering in this photograph.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

NIST Issues Call for "Lightweight Cryptography" Algorithms

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/nist_issues_cal.html

This is interesting:

Creating these defenses is the goal of NIST’s lightweight cryptography initiative, which aims to develop cryptographic algorithm standards that can work within the confines of a simple electronic device. Many of the sensors, actuators and other micromachines that will function as eyes, ears and hands in IoT networks will work on scant electrical power and use circuitry far more limited than the chips found in even the simplest cell phone. Similar small electronics exist in the keyless entry fobs to newer-model cars and the Radio Frequency Identification (RFID) tags used to locate boxes in vast warehouses.

All of these gadgets are inexpensive to make and will fit nearly anywhere, but common encryption methods may demand more electronic resources than they possess.

The NSA’s SIMON and SPECK would certainly qualify.

10 visualizations to try in Amazon QuickSight with sample data

Post Syndicated from Karthik Kumar Odapally original https://aws.amazon.com/blogs/big-data/10-visualizations-to-try-in-amazon-quicksight-with-sample-data/

If you’re not already familiar with building visualizations for quick access to business insights using Amazon QuickSight, consider this your introduction. In this post, we’ll walk through some common scenarios with sample datasets to provide an overview of how you can connect yuor data, perform advanced analysis and access the results from any web browser or mobile device.

The following visualizations are built from the public datasets available in the links below. Before we jump into that, let’s take a look at the supported data sources, file formats and a typical QuickSight workflow to build any visualization.

Which data sources does Amazon QuickSight support?

At the time of publication, you can use the following data methods:

  • Connect to AWS data sources, including:
    • Amazon RDS
    • Amazon Aurora
    • Amazon Redshift
    • Amazon Athena
    • Amazon S3
  • Upload Excel spreadsheets or flat files (CSV, TSV, CLF, and ELF)
  • Connect to on-premises databases like Teradata, SQL Server, MySQL, and PostgreSQL
  • Import data from SaaS applications like Salesforce and Snowflake
  • Use big data processing engines like Spark and Presto

This list is constantly growing. For more information, see Supported Data Sources.

Answers in instants

SPICE is the Amazon QuickSight super-fast, parallel, in-memory calculation engine, designed specifically for ad hoc data visualization. SPICE stores your data in a system architected for high availability, where it is saved until you choose to delete it. Improve the performance of database datasets by importing the data into SPICE instead of using a direct database query. To calculate how much SPICE capacity your dataset needs, see Managing SPICE Capacity.

Typical Amazon QuickSight workflow

When you create an analysis, the typical workflow is as follows:

  1. Connect to a data source, and then create a new dataset or choose an existing dataset.
  2. (Optional) If you created a new dataset, prepare the data (for example, by changing field names or data types).
  3. Create a new analysis.
  4. Add a visual to the analysis by choosing the fields to visualize. Choose a specific visual type, or use AutoGraph and let Amazon QuickSight choose the most appropriate visual type, based on the number and data types of the fields that you select.
  5. (Optional) Modify the visual to meet your requirements (for example, by adding a filter or changing the visual type).
  6. (Optional) Add more visuals to the analysis.
  7. (Optional) Add scenes to the default story to provide a narrative about some aspect of the analysis data.
  8. (Optional) Publish the analysis as a dashboard to share insights with other users.

The following graphic illustrates a typical Amazon QuickSight workflow.

Visualizations created in Amazon QuickSight with sample datasets

Visualizations for a data analyst

Source:  https://data.worldbank.org/

Download and Resources:  https://datacatalog.worldbank.org/dataset/world-development-indicators

Data catalog:  The World Bank invests into multiple development projects at the national, regional, and global levels. It’s a great source of information for data analysts.

The following graph shows the percentage of the population that has access to electricity (rural and urban) during 2000 in Asia, Africa, the Middle East, and Latin America.

The following graph shows the share of healthcare costs that are paid out-of-pocket (private vs. public). Also, you can maneuver over the graph to get detailed statistics at a glance.

Visualizations for a trading analyst

Source:  Deutsche Börse Public Dataset (DBG PDS)

Download and resources:  https://aws.amazon.com/public-datasets/deutsche-boerse-pds/

Data catalog:  The DBG PDS project makes real-time data derived from Deutsche Börse’s trading market systems available to the public for free. This is the first time that such detailed financial market data has been shared freely and continually from the source provider.

The following graph shows the market trend of max trade volume for different EU banks. It builds on the data available on XETRA engines, which is made up of a variety of equities, funds, and derivative securities. This graph can be scrolled to visualize trade for a period of an hour or more.

The following graph shows the common stock beating the rest of the maximum trade volume over a period of time, grouped by security type.

Visualizations for a data scientist

Source:  https://catalog.data.gov/

Download and resources:  https://catalog.data.gov/dataset/road-weather-information-stations-788f8

Data catalog:  Data derived from different sensor stations placed on the city bridges and surface streets are a core information source. The road weather information station has a temperature sensor that measures the temperature of the street surface. It also has a sensor that measures the ambient air temperature at the station each second.

The following graph shows the present max air temperature in Seattle from different RWI station sensors.

The following graph shows the minimum temperature of the road surface at different times, which helps predicts road conditions at a particular time of the year.

Visualizations for a data engineer

Source:  https://www.kaggle.com/

Download and resources:  https://www.kaggle.com/datasnaek/youtube-new/data

Data catalog:  Kaggle has come up with a platform where people can donate open datasets. Data engineers and other community members can have open access to these datasets and can contribute to the open data movement. They have more than 350 datasets in total, with more than 200 as featured datasets. It has a few interesting datasets on the platform that are not present at other places, and it’s a platform to connect with other data enthusiasts.

The following graph shows the trending YouTube videos and presents the max likes for the top 20 channels. This is one of the most popular datasets for data engineers.

The following graph shows the YouTube daily statistics for the max views of video titles published during a specific time period.

Visualizations for a business user

Source:  New York Taxi Data

Download and resources:  https://data.cityofnewyork.us/Transportation/2016-Green-Taxi-Trip-Data/hvrh-b6nb

Data catalog: NYC Open data hosts some very popular open data sets for all New Yorkers. This platform allows you to get involved in dive deep into the data set to pull some useful visualizations. 2016 Green taxi trip dataset includes trip records from all trips completed in green taxis in NYC in 2016. Records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.

The following graph presents maximum fare amount grouped by the passenger count during a period of time during a day. This can be further expanded to follow through different day of the month based on the business need.

The following graph shows the NewYork taxi data from January 2016, showing the dip in the number of taxis ridden on January 23, 2016 across all types of taxis.

A quick search for that date and location shows you the following news report:

Summary

Using Amazon QuickSight, you can see patterns across a time-series data by building visualizations, performing ad hoc analysis, and quickly generating insights. We hope you’ll give it a try today!

 


Additional Reading

If you found this post useful, be sure to check out Amazon QuickSight Adds Support for Combo Charts and Row-Level Security and Visualize AWS Cloudtrail Logs Using AWS Glue and Amazon QuickSight.


Karthik Odapally is a Sr. Solutions Architect in AWS. His passion is to build cost effective and highly scalable solutions on the cloud. In his spare time, he bakes cookies and cupcakes for family and friends here in the PNW. He loves vintage racing cars.

 

 

 

Pranabesh Mandal is a Solutions Architect in AWS. He has over a decade of IT experience. He is passionate about cloud technology and focuses on Analytics. In his spare time, he likes to hike and explore the beautiful nature and wild life of most divine national parks around the United States alongside his wife.

 

 

 

 

Welcome Victoria — Sales Development Representative

Post Syndicated from Yev original https://www.backblaze.com/blog/welcome-victoria-sales-development-representative/

Ever since we introduced our Groups feature, Backblaze for Business has been growing at a rapid rate! We’ve been staffing up in order to support the product and the newest addition to the sales team, Victoria, joins us as a Sales Development Representative! Let’s learn a bit more about Victoria, shall we?

What is your Backblaze Title?
Sales Development Representative.

Where are you originally from?
Harrisburg, North Carolina.

What attracted you to Backblaze?
The leaders and family-style culture.

What do you expect to learn while being at Backblaze?
How to sell, sell, sell!

Where else have you worked?
The North Carolina Autism Society, an ophthalmologist’s office, home health care, and another tech startup.

Where did you go to school?
The University of North Carolina Chapel Hill and Duke University’s Fuqua School of Business.

What’s your dream job?
Fighter pilot, professional snowboarder or killer whale trainer.

Favorite place you’ve traveled?
Hawaii and Banff.

Favorite hobby?
Basketball and cars.

Of what achievement are you most proud?
Missionary work and helping patients feel better.

Star Trek or Star Wars?
Neither, but probably Star Wars.

Coke or Pepsi?
Neither, bubble tea.

Favorite food?
Snow crab legs.

Why do you like certain things?
Because God made me that way.

Anything else you’d like you’d like to tell us?
I’m a germophobe, drink a lot of water and unfortunately, am introverted.

Being on the phones all day is a good way to build up those extroversion skills! Welcome to the team and we hope you enjoy learning how to sell, sell, sell!

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