{"id":14287,"date":"2019-02-20T14:11:18","date_gmt":"2019-02-20T14:11:18","guid":{"rendered":"https:\/\/rsoftsolution.com\/blog\/why-daimler-moved-its-big-data-platform-to-the-cloud.html"},"modified":"2019-02-20T14:11:18","modified_gmt":"2019-02-20T14:11:18","slug":"why-daimler-moved-its-big-data-platform-to-the-cloud","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/why-daimler-moved-its-big-data-platform-to-the-cloud.html","title":{"rendered":"Why Daimler moved its big data platform to the cloud"},"content":{"rendered":"

Like virtually every big enterprise company, a few years ago, the German auto giant Daimler <\/a> decided to invest in its own on-premises data centers. And while those aren\u2019t going away anytime soon, the company today announced that it has successfully moved its on-premises big data platform to Microsoft\u2019s Azure cloud. This new platform, which the company calls eXtollo, is Daimler\u2019s first major service to run outside of its own data centers, though it\u2019ll probably not be the last.<\/p>\n

As Daimler\u2019s head of its corporate center of excellence for advanced analytics and big data Guido Vetter told me, that the company started getting interested in big data about five years ago. \u201cWe invested in technology \u2014 the classical way,\u00a0on-premise \u2014 and got a couple of people on it. And we were investigating what we could do with data because data is transforming our whole business as well,\u201d he said.<\/p>\n

By 2016, the size of the organization had grown to the point where a more formal structure was needed to enable the company to handle its data at a global scale. At the time, the buzzword was \u2018data lakes\u2019 and the company started building its own in order to build out its analytics capacities.<\/p>\n

\"\"<\/p>\n

Electric Line-Up, Daimler AG<\/p>\n

\u201cSooner or later, we hit the limits as it\u2019s not our core business to run these big environments,\u201d Vetter said. \u201cFlexibility and scalability are what you need for AI and advanced analytics and our whole operations are not set up for that. Our backend operations are set up for keeping a plant running and keeping everything safe and secure.\u201d But in this new world of enterprise IT, companies need to be able to be flexible and experiment \u2014 and, if necessary, throw out failed experiments quickly.<\/p>\n

So about a year and a half ago, Vetter\u2019s team started the eXtollo\u00a0project to bring all the company\u2019s activities around advanced analytics, big data and artificial intelligence into the Azure Cloud and just over two weeks ago, the team shut down its last on-premises servers after slowly turning on its solutions in Microsoft\u2019s data centers in Europe, the U.S. and Asia. All in all, the actual transition between the on-premises data centers and the Azure cloud took about nine months. That may not seem fast, but for an enterprise project like this, that\u2019s about as fast as it gets (and for a while, it fed all new data into both its on-premises data lake and Azure).<\/p>\n

<\/p>\n

If you work for a startup, then all of this probably doesn\u2019t seem like a big deal, but for a more traditional enterprise like Daimler, even just giving up control over the physical hardware where your data resides was a major culture change and something that took quite a bit of convincing. In the end, the solution came down to encryption.<\/p>\n

\u201cWe needed the means to secure the data in the Microsoft data center with our own means that ensure that only we have access to the raw data and work with the data,\u201d explained Vetter. In the end, the company decided to use thethAzure Key Vault to manage and rotate its encryption keys. Indeed, Vetter noted that knowing that the company had full control over its own data was what allowed this project to move forward.<\/p>\n

Vetter tells me that the company obviously looked at Microsoft\u2019s competitors as well, but he noted that his team didn\u2019t find a compelling offer from other vendors in terms of functionality and the security features that it needed.<\/p>\n

Today, Daimler\u2019s big data unit uses tools like HD Insights and Azure\u00a0Databricks, which covers more than 90 percents of the company\u2019s current use cases. In the future, Vetter also wants to make it easier for less experienced users to use self-service tools to launch AI and analytics services.<\/p>\n

While cost is often a factor that counts against the cloud since renting server capacity isn\u2019t cheap, Vetter argues that this move will actually save the company money and that storage cost, especially, are going to be cheaper in the cloud than in its on-premises data center (and chances are that Daimler, given its size and prestige as a customer, isn\u2019t exactly paying the same rack rate that others are paying for the Azure services).<\/p>\n

As with so many big data AI projects, predictions are the focus of much of what Daimler is doing. That may mean looking at a car\u2019s data and error code and helping the technician diagnose an issue or doing predictive maintenance on a commercial vehicle. Interestingly, the company isn\u2019t currently bringing any of its own IoT data from its plants to the cloud. That\u2019s all managed in the company\u2019s on-premises data centers because it wants to avoid the risk of having to shut down a plant because its tools lost the connection to a data center, for example.<\/p>\n

Article source: http:\/\/feedproxy.google.com\/~r\/techcrunchIt\/~3\/oLt4aXHxcQk\/<\/p>","protected":false},"excerpt":{"rendered":"

Like virtually every big enterprise company, a few years ago, the German auto giant Daimler decided to invest in its own on-premises data centers. And while those aren\u2019t going away <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[19],"tags":[25],"class_list":["post-14287","post","type-post","status-publish","format-standard","hentry","category-enterprise-software","tag-enterprise"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t