The Cloud Part Two: Disruption in motion in enterprise computing

IBM Cloud Computing

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As I said in my last post, Cloud computing has made operating systems, databases and applications more available, making business more democratic. A few concepts have been game changers in this disruption, and I’d like to touch on them. Note: I’m only mentioning a few key companies here, because this post can’t be 5,000 words long. If I leave your company out, please don’t be offended. I know you’re out there and you are great!

Data and Databases:  For decades, companies like Oracle dominated the large database arena. This poses several problems. First, we need more than one company in the database space to increase choice. Second, Relational Databases (RDBMS) and SQL have inherent limitations. SQL (structured query language) was designed about 35 years ago and does not suit the diversity, scale, distribution and unstructured data needs that have arisen with players like Facebook and YouTube. With the Apache Foundation we have democratized the availability of the tools and methods to address today’s database demands. This is a perfect example of open versus proprietary systems. Open systems grow via the involvement of an active global community! Some considerations and examples:

  • Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment, thus supporting data-intensive distributed applications. Note key here is data –intensive vs compute-intensive.  Cloudera and Greenplum are companies in this space.
  • Data-Intensive Distributed Applications: A class of parallel computing applications that use a data parallel approach to process large volumes of data—typically terabytes or petabytes. They are typically referred to as Big Data.
  • NoSQL (Not only SQL): These databases don’t need the data schema in advance and scale horizontally. This is key, as we can add nodes and expand our reach and access to data much more readily than the old paradigms. Today’s data is highly diverse, distributed and large scale.  Search is being redefined and real-time is very much becoming a reality!  Cloudant, Cassandra and Basho are companies in this space, while companies such as GenieDB are bridging the gap between SQL and NoSQL.

Analytics: For decades, SAS (Statistical Analysis Software) has been the icon of analytics software. But while SAS will continue to be used in large enterprise engines, it is not evolving as rapidly as needed to the new world of highly distributed, large scale, diverse data environments. Analytics is being distributed over large number of smart devices; it’s no longer something managed and controlled by old school business intelligence (BI) departments. In turn, BI departments are being replaced with inspired, intelligent enterprise end users and data engineers who need immediate access to data. Today’s world is about real-time analytics. Companies in this space include 1010Data, GoodData and Tableau Software, while companies such as Predixion Software are in the predictive analytics space.

App Mobility: With IT becoming distributed, data and applications are doing the same. Application mobility is critical in this environment, and companies such as Cloudsoft are making their mark in this area.

Social Enterprise: Enterprises are becoming open and distributed. At the same time, social media, once derided as a plaything for employees, has become the source of terabytes of new data that the enterprise needs to understand, work with in real time and mine. I call this the Social Enterprise. Initiatives like @WalmartLabs are exploring the potential of this immense data stream and redefining digital marketing, advertising, product development. There are many players emerging in this space.

These are some of the paradigm shifts and disruptions that are taking place.  There are more, all enabling innovation to excellence. What is most intriguing to me is that this is mindful disruption greatly enhancing our ability to extract information from big data, such to improve processes. No longer analysis for the sake of analytics, but critical analytics which defines our business processes,  available and open to all!  This is disruption at it’s best!  Our discussion continues…

 

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