Sumo Logic plans to go public. The company offers log management services, along with analytics for the purpose of management and observability of IT Systems. The offer comes differentiated as a fully managed solution, delivered from the cloud. Now the company apparently plans for an IPO, reports Reuters:
Source: Reuters – Big data firm Sumo Logic aims to raise $310 million in U.S. IPO
Meanwhile, after Microsoft announced their cooperation with SAP in IoT with Leonardo, AWS also announced tighter integration with SAPs business processes.
The previously announced cooperation shows first results. Particularly in form of Microsofts announcement of having integrated SAP Leonardo into their Azure IoT Hub.
Source: SAP and Microsoft bring IoT data to the core of the business applications | Blog | Microsoft Azure
Today in dystopian news: Amazon, the book selling department, controlling about 40% of the US book market, collects reading habbits from their sales and Kindle. By now the corporation knows enough about it’s customers it could be generating best selling books. Spookey. And potentially game changing, when machines replace creative professions.
Amazon has the ability to track vast amounts of reader data and use it to change the landscape of American fiction.
Source: Amazon has so much data it could make algorithm-driven fiction — Quartz
Python ?:
Leseempfehlung: Ein Journalist spricht mit einem anonymen Big Data Engineer/Analyst über die Komplexität von Algorithmen. Wie erschreckend die Abhängigkeit von undurchschaubaren Komponenten geworden ist gegenüber dem Einfluss den Maschinen damit auf unser Leben haben.
Man kann das auch als Laie verstehen, wie ich meine, selbst mein Verständnis von Big Data reicht nur so weit als das als realistisch einzuschätzen.
‘I’ll lose my job if anyone knows about this.”There was a long silence which I didn’t dare to break. I had begged to make this meeting happen. And now the person I had long been trying to meet leaned towards me. “Someone is going to go through your book line by line,” he said, “to try to work out who I am.”He’d been a talented researcher, an academic, until his friend started a small technology company. He had joined the company and helped it to grow. It eventually became so big that the company had been acquired by one of the tech giants. And so, then, was he.He was now paid a fortune to help design the algorithms that were central to what the tech giant did. And he had signed solemn legal documents prohibiting him from speaking to me, or to anyone, about his work. But as the…
Source: The terrifying, hidden reality of Ridiculously Complicated Algorithms
The field begins to look like others that rely on data.
This is a discussion I had more than a decade back with economy students, as a student of computer science. The argument was much the same and nothing much has changed in the meantime. The difference is more data is available today and can be used much easier, though, which is to Noah Smiths argument.
Chris Stucchio hat einen interessanten Punkt bzgl. Big Data. Nämlich, dass Big Data heißt gar nicht Big ist. Nur weil Excel einen Datensatz nicht öffnen kann, heisst das nicht automatisch, dass Big Data Tools – in seinem Aufsatz Hadoop – notwendig sind. Gigabyteweise Daten lassen sich auch anders verarbeiten. Moderne Hardware hat nicht selten mehrere GB an Hauptspeicher. Die Geräte bei Mediamarkt waren vergangenen Samstag alleine mit mindestens 8Gb ausgestattet. Das heisst natürlich nicht, dass Hadoop oder vergleichbare Tools gar keinen Anwendungsfall hätten, aber die Use-Cases sind vielleicht anders gelagert, als man auf den ersten Gedanken annimmt.
Quelle: Dont use Hadoop – your data isnt that big – Chris Stucchio
Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World
Bruce Schneier wrote a book about Big Data, mass surveilance and the Internet of Things. Schneier talks about how this effects society and what to do about the increasing datarization of everything we’re doing.
Monitoring infrastructure in a meaningful way is important to any IT operations, yet it is hard to realize. Many vendors adress this problem and promise a silver bullet.
