The ruling sets a high bar for the level of «creativity» that APIs may need to show before they deserve protection under copyright law.
From widespread open-source software use by its government, to improved connectivity on Mallorca, Menorca, Ibiza, and Formentera, the Balearic islands are aiming to appeal to technologists as well as tourists.
Didn’t make it to the Bay Area Maker Faire last weekend? You can still experience the magic! Here are a few choice moments and projects from the Faire.
These were created using the Seene app, and they work even better if you view them on a phone – where the accelerometer controls the rotation, and you can triple-tap to visualize the depth map the app creates. There’s also an option to view it in Cardboard VR. Sometimes they come out a bit glitchy, which I think is something to love about this new medium!
Here’s an FM radio made by one of the «Bring a Hack» dinner attendees. Check out how he’s used a resistor to anchor that wire for strain relief!
This giant robo-squid, «Mechateuthis», actually moves its tentacles. One of the most impressive moving robots I’ve seen, considering the torque that must be on those cantilevered limbs! According to PopMech, it’s triggered by a crank, but all the drive power comes from Arduino-controlled motors.
One exhibitor was selling beautiful lamps with custom-fabricated light bulbs! My companion noted the satisfying feel of this knob.
Here’s Eveii, a little sensing robot that I built for Cypress Semiconductor using the PSoC 4 Pioneer Kit.
We also paid a visit to Kelly, who built a skirt out of K’Nex and invited makers to add to it before her appearance in the fashion show.
Of course, there’s way more to see; the Make: team kept a stream of live updates going, so you can scratch that itch as much as you like.
I heard about Seene from Doc Pop – a local yoyo master and 3D artist. Go check out his profile for way more cool shots!
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A mix between data scientist and engineer, Big Data engineers are a new breed in the technology community. Do you have what it takes to be a pioneer? The skills required for Big Data engineering roles aren’t necessarily new things, but they do require a certain level of understanding in a few particular areas for candidates to be successful. Those particular areas? Math and scientific analysis.If you’ve been successful in engineering roles with those skills in the past, even if you don’t have all the skills or experience listed below, you might be a great fit for a Big Data engineering role.Click here to find Big Data engineer positions.You Can Do Lots of Things With DataNot all Big Data roles are the same, but there are a few things you can expect to see if you take on a position in this field. Typically the role will include a subset of the following high-level skills: Data Analysis: Are you a pro with MapReduce, Hadoop or even data mining? In addition to processing data, you may also need to know more specialized techniques like machine learning or even statistical analysis. Data Warehousing: Are you familiar with large data stores? Do you know how to get data in or take data out? Good. Data Transformation: Sometimes data needs to be changed or transformed into a different format in order to properly analyze it. Can you make it work? You may know this work as ETL or even just scripting. Data Collection: You have to crawl before you can walk. Crawling the Web or extracting data from an existing database or API are common chores for Big Data engineers.Every role is different, though, so some may require more specialized knowledge in one of these areas over the others. However, if you are an expert in one, it’s not usually too challenging to translate those skills to the other areas.What You NeedData Analysis MapReduce, Hadoop, Cloudera, IBM Big Insights, Hortonworks or MapR. Most people tend to have experience with one implementation of MapReduce (since many of these tools are only a few years old) but the underlying algorithms make it easy to learn new ones with a few weeks of ramp-up time. If you are familiar with one of the tools listed here, or one of the many flavors of MapReduce (like Hive or Pig), you’ll most likely be able to step into a role using a similar tool. Data mining or machine learning. This can include technologies like Mahout, or more specialized techniques like Neural Networks. Having these skills can be a huge asset for you over other candidates if the role requires this kind of work, since these skills are more specialized and harder to learn. Statistical analysis software: R, SPSS, SAS, Weka, MATLAB. Most data scientists have some statistical experience, but not all of them will use software to do their work. If that’s you—if you use Java, for example—you may be expected to learn these software tools, but it should be fairly easy to ramp up from what you’re used to. Programming skills: Java, Scala, Ruby, C++. Typically, more heavy lifting programming skills will be required for custom implementations or specialized implementations (leveraging things like machine learning, etc.).Data Warehousing Relational databases: MySQL, MS SQL Server, Oracle, DB2. Expertise with one of these tools takes time, so if your experience matches the tools used at the company you’re interviewing with, that’s a great thing. However, if you’re not an expert with their tools, experience with one of these will make it easier to learn the basics of a new one in a matter of weeks. NoSQL: HBase, SAP HANA, HDFS, Cassandra, MongoDB, CouchDB, Vertica, Greenplum, Pentaho and Teradata. In this area, it’s best if your experience matches what the company already uses. Knowledge of one won’t necessarily translate well to others.Upload Your ResumeEmployers want candidates like you. Upload your resume. Show them you’re awesome.Data Collection Data APIs (e.g., RESTful interfaces). Most candidates should have some experience working with APIs to collect or ingest data. If not, any candidate with programming or scripting experience can pick this up in less than a week. SQL expertise and data modeling. This is something all candidates for Big Data engineering roles should have, so you’ll need to brush up your skills if you haven’t done this kind of work for a while.Data Transformation ETL Tools: Informatica, DataStage, SSIS, Redpoint. In general, your experience with one of these tools will be applicable to using a different one, if required. Scripting. Do you know Linux/Unix commands, Python, Ruby or Perl? While each of these languages works differently, your knowledge of one should translate fairly easily to mastery of another.Big Data engineering is a new field with a lot of new technologies and new positions. Not all roles require expertise in every area, so pay attention to what needs the company you’re looking at really has. By taking on one of these roles, you’re tackling a br