SAS Institute which pioneered the data analytics software field was co-founded by Jim Goodnight over 40 odd years back. He has seen the evolution of the company from its roots in mainframes to its current star status in the cloud-based applications of today.
Besides being the CEO of the outfit from Cary in North Carolina, Mr. Goodnight is also the majority owner of the firm and is seen as a sort of “Godfather” of the field of analytics. He launched SAS way back in 1976 when analytics was still referred to as statistics and the number of independent software firms amounted to only a few as all of the users of mainframes sourced their software from IBM.
About a decade or so back SAS turned its focus to PC based analytics products and today finds itself returning to in some ways returning back to mainframes in the form of shared cloud servers. Mr. Goodnight reminiscences about the days of the old mainframes, with cloud servers reminding him of the days when you controlled the mainframe through a screen.
SAS is yet to witness a single losing year in the four decades it has been operational for and whose annual revenue stood at over $3 billion in the year 2014. That is pretty impressive when you factor in the fact that the company owes its origins to a project undertaken by the North Carolina State University in order to develop a Statistical Analysis System referred to as SAS in short originally intended to sort out loads of data related to agriculture for USDA.
Mr. Goodnight recently voiced his opinion on what the impact of the Internet of Things, often referred to as IoT, on analytics might be. With a doctorate in statistics, he is well placed to voice his opinion, which he indeed did. He also spoke of the voice recognition tool of Google and the lessons that software makers of analytics may learn from.
According to Mr. Goodnight, the banking industry has changed the most over the course of his involvement with SAS with the pace of change increasing in the last 25 years. They have been quick to adopt a data-based decision model. From the 90’s people at banks started to make use of predictive models of data. And these days banks are found to put into use 200 such models each passing day.
About IoT however, Mr. Goodnight is not impressed as its potentialities are yet to be tapped beyond being used as an enhanced bar code.
According to him deep learning where machines train themselves is where the future lies citing the example of the voice recognition tool of Google. He also drew an analogy of that with analytics where people are putting forth using a cognitive tool on the front end of a particular system.
On an ending note, he opined that retention of quality talent and encouraging innovation are the means towards achieving success in the highly competitive fields of business organizations functioning today to replicate the success of SAS Institute.
And if you wish to dive in to the details of Big Data you should consider opting for a course from a SAS Training Institute in Delhi.
Besides being the CEO of the outfit from Cary in North Carolina, Mr. Goodnight is also the majority owner of the firm and is seen as a sort of “Godfather” of the field of analytics. He launched SAS way back in 1976 when analytics was still referred to as statistics and the number of independent software firms amounted to only a few as all of the users of mainframes sourced their software from IBM.
About a decade or so back SAS turned its focus to PC based analytics products and today finds itself returning to in some ways returning back to mainframes in the form of shared cloud servers. Mr. Goodnight reminiscences about the days of the old mainframes, with cloud servers reminding him of the days when you controlled the mainframe through a screen.
SAS is yet to witness a single losing year in the four decades it has been operational for and whose annual revenue stood at over $3 billion in the year 2014. That is pretty impressive when you factor in the fact that the company owes its origins to a project undertaken by the North Carolina State University in order to develop a Statistical Analysis System referred to as SAS in short originally intended to sort out loads of data related to agriculture for USDA.
Mr. Goodnight recently voiced his opinion on what the impact of the Internet of Things, often referred to as IoT, on analytics might be. With a doctorate in statistics, he is well placed to voice his opinion, which he indeed did. He also spoke of the voice recognition tool of Google and the lessons that software makers of analytics may learn from.
According to Mr. Goodnight, the banking industry has changed the most over the course of his involvement with SAS with the pace of change increasing in the last 25 years. They have been quick to adopt a data-based decision model. From the 90’s people at banks started to make use of predictive models of data. And these days banks are found to put into use 200 such models each passing day.
About IoT however, Mr. Goodnight is not impressed as its potentialities are yet to be tapped beyond being used as an enhanced bar code.
According to him deep learning where machines train themselves is where the future lies citing the example of the voice recognition tool of Google. He also drew an analogy of that with analytics where people are putting forth using a cognitive tool on the front end of a particular system.
On an ending note, he opined that retention of quality talent and encouraging innovation are the means towards achieving success in the highly competitive fields of business organizations functioning today to replicate the success of SAS Institute.
And if you wish to dive in to the details of Big Data you should consider opting for a course from a SAS Training Institute in Delhi.
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