{"id":46799,"date":"2014-07-14T08:04:25","date_gmt":"2014-07-14T12:04:25","guid":{"rendered":"http:\/\/danielschristian.com\/learning-ecosystems\/?p=46799"},"modified":"2014-07-14T08:04:45","modified_gmt":"2014-07-14T12:04:45","slug":"reflections-on-the-internet-of-things-will-radically-change-your-big-data-strategy-kavis","status":"publish","type":"post","link":"http:\/\/danielschristian.com\/learning-ecosystems\/2014\/07\/14\/reflections-on-the-internet-of-things-will-radically-change-your-big-data-strategy-kavis\/","title":{"rendered":"Reflections on “The Internet of Things will radically change your Big Data strategy” [Kavis]"},"content":{"rendered":"

The Internet of Things will radically change your Big Data strategy\u00a0<\/strong><\/a>— from forbes.com by Mike Kavis<\/p>\n

Excerpt (emphasis DSC):<\/span><\/em><\/p>\n

Companies are jumping on the Internet of Things (IoT) bandwagon and for good reasons. McKinsey Global Institute reports that the IoT business\u00a0will deliver $6.2 trillion\u00a0of revenue by 2025. Many people wonder if companies are ready<\/a> for this explosion of data generated for IoT. As with any new technology, security is always the first point of resistance. I agree that IoT brings a wave of new security concerns but the bigger concern is how woefully unprepared most data centers are for the massive amount of data coming from all of the \u201cthings\u201d in the near future.<\/p>\n

Some companies are still hanging on to the belief that they can manage their own data centers better than the various cloud providers out there. This state of denial should all but go away when the influx of petabyte scale data becomes a reality for enterprises. Enterprises are going to have to ask themselves, \u201cDo we want to be in the infrastructure business?\u201d because that is what it will take to provide the appropriate amount of bandwidth, disk storage, and compute power to keep up with the demand for data ingestion, storage, and real-time analytics that will serve the business needs. If there ever was a use case for the cloud, the IoT and Big Data is it.<\/span><\/p>\n

…<\/p>\n

Even if enterprises manage to make it past the data ingestion phase, the data storage phase presents another set of challenges. In this area, companies must learn new technologies like Hadoop, Map Reduce, etc. and be able to provision enough disk, network, and compute capacity to keep up with the influx of new data. There is a major skills shortage<\/strong> in the area which creates a serious challenge in the do-it-yourself (DIY) model.<\/span><\/p>\n

…<\/p>\n

In the DIY model, engineers need to acquire a broad range of skills<\/strong> in order to work with the underlying technologies.<\/span><\/p>\n

 <\/p>\n

From DSC:<\/span><\/em>
\nThe above item made be wonder:<\/span><\/p>\n