Chief Data Science Officers Won't Supplant CIOs
One might argue that it's only a matter of time before data scientists assume their rightful place in a corner office. After all, according to this perspective, it's more than just being hip and with the times. Many organizations that have based their strategy on big data analytics have also identified data science as a key enabler. As the chief data officer (CDO) has risen in strategic importance, it only makes sense that this individual will oversee data science initiatives, personnel, and practices.
The end for 1024-bit SSL certificates is near, as Mozilla kills a few more
Owners of 2048-bit certificates that chain back to intermediate CA certificates with 1024-bit keys will also be impacted if they don't update the certificate chain on their Web servers to include a 2048-bit intermediate from their certificate authority. Each certificate authority has one or more root certificates that it uses to sign SSL certificates with when issuing them to customers. Those CA certificates are included in operating systems, major browsers and other products according to well established agreements and are used to verify the authenticity of SSL certificates presented by websites.
Evolution of Wearables - What is in store?
Medical and Wellness segment could be the one which will embrace this category of wearable devices and make health more affordable and self manageable for every one. For instance, one can wear a virtual doctor while on a specific treatment. A better example could be that the advances in wearable devices could lead to a scenario, where a diabetes patient may get appropriate doses of insulin administered into his body automatically based on various data collected by the sensors worn around the body. This could be risky, if the data, so collected are inaccurate and that is one of the major concern that is expected to be addressed in the coming years.
Building data science teams: The power of the technology stack
A factor that is frequently overlooked when setting up a data team is the selection of the technology stack. Often, this decision is delegated to the first hire in data science. Due to a lack of information about the right technologies, those in charge avoid making a decision. There is a case to be made for building a multilingual team. Nevertheless, I would like to highlight the advantages of choosing a technology stack during the conceptualization of a data team.
Technology Repaints the Payment Landscape
Across the globe, BCG predicts a time of “disruption and opportunity” driven by digital technologies that will require the existing credit card system to prove that it’s better than its new competition. “The smartphone is the catalyst for a lot of change in this industry,” says Dana Stalder, a venture capitalist with Matrix Partners and a former eBay and PayPal executive now on the board of Poynt, which recently introduced a smart credit card terminal. Venture capitalists invested over $2 billion in payment technology firms between January 2013 and June 2014, according to the data tracking firm CB Insights.
Microsoft throws down the gauntlet in business intelligence
James Phillips, Microsoft’s general manager for business intelligence, said the company has already had tens of thousands of organizations sign up for PowerBI since it became available in February 2014, and that CEO Satya Nadella opens up a PowerBI dashboard every morning to track certain metrics. ... Phillips said the business intelligence market is presently in its third wave. The first wave was technical and database-centric. The second wave was about self service, defined first by Excel and, over the past few years, by Tableau’s eponymous software. The third wave, he said, takes self service a step further in terms of ease of use and all but eliminates the need for individual employees to track down IT before they can get something done.
How Connected Cars Have Established A New Ecosystem Powered By IoT
The IoT-enabled “connected car” turns the vehicle itself into a hub for an entire ecosystem of connected services that offer consumers a wealth of benefits including enhanced safety and security, a richer user experience and a new suite of product offerings. From the manufacturer’s perspective, this also helps establish an ongoing customer relationship as well as incremental revenue streams over the life of the vehicle. Over-the-air (OTA) software updates in cars are very similar to the software updates that occur in smartphones. Any software update for a vehicle’s connected services is done wirelessly OTA, keeping the OEM in contact with the vehicle but removing the need for a dealership visit.
Big Data Processing with Apache Spark – Part 1: Introduction
Spark allows programmers to develop complex, multi-step data pipelines using directed acyclic graph (DAG) pattern. It also supports in-memory data sharing across DAGs, so that different jobs can work with the same data. Spark runs on top of existing Hadoop Distributed File System (HDFS) infrastructure to provide enhanced and additional functionality. It provides support for deploying Spark applications in an existing Hadoop v1 cluster (with SIMR – Spark-Inside-MapReduce) or Hadoop v2 YARN cluster or even Apache Mesos. We should look at Spark as an alternative to Hadoop MapReduce rather than a replacement to Hadoop.
A Historical Look at Enterprise Architecture with John Zachman
According to Zachman, Walker created a methodology for defining processes as separate entities from the organizational structure. Walker came out to Los Angeles, where Zachman and ARCO were based to help provide guidance on the merger. Zachman recalls Walker telling him that the key to defining the systems for Enterprise purposes was in the data, not necessarily the process itself. In other words, the data across the company needed to be normalized so that they could maintain visibility into the assets and structure of the enterprise. “The secret to this whole thing lies in the coding and the classification of the data,” Zachman recalled Walker saying. Walker’s methodology, he said, began by classifying data by its existence not by its use.
Increasingly, enterprise architecture looks outward
From a customer-facing perspective, EAs are now getting intimately involved in planning and managing digital strategies, along with existing internal systems. Oliver Bossert, Chris Ip, and Jürgen Laartz, all with McKinsey, point out that many organizations have extensive legacy systems wired into their organizations, yet are challenged with getting on the digital track as fast as possible. In a new post, they recommend organizations adopt a "two-speed IT architecture" that will meet the needs of planning back-end systems of record with digital front ends. Such a two-speed strategy would consist of "a fast-speed, customer-centric front end running alongside a slow-speed, transaction-focused legacy back end," the analysts explain.
Quote for the day:
"People ask the difference between a leader and a boss. The leader leads, and the boss drives." -- Theodore Roosevelt
One might argue that it's only a matter of time before data scientists assume their rightful place in a corner office. After all, according to this perspective, it's more than just being hip and with the times. Many organizations that have based their strategy on big data analytics have also identified data science as a key enabler. As the chief data officer (CDO) has risen in strategic importance, it only makes sense that this individual will oversee data science initiatives, personnel, and practices.
The end for 1024-bit SSL certificates is near, as Mozilla kills a few more
Owners of 2048-bit certificates that chain back to intermediate CA certificates with 1024-bit keys will also be impacted if they don't update the certificate chain on their Web servers to include a 2048-bit intermediate from their certificate authority. Each certificate authority has one or more root certificates that it uses to sign SSL certificates with when issuing them to customers. Those CA certificates are included in operating systems, major browsers and other products according to well established agreements and are used to verify the authenticity of SSL certificates presented by websites.
Evolution of Wearables - What is in store?
Medical and Wellness segment could be the one which will embrace this category of wearable devices and make health more affordable and self manageable for every one. For instance, one can wear a virtual doctor while on a specific treatment. A better example could be that the advances in wearable devices could lead to a scenario, where a diabetes patient may get appropriate doses of insulin administered into his body automatically based on various data collected by the sensors worn around the body. This could be risky, if the data, so collected are inaccurate and that is one of the major concern that is expected to be addressed in the coming years.
Building data science teams: The power of the technology stack
A factor that is frequently overlooked when setting up a data team is the selection of the technology stack. Often, this decision is delegated to the first hire in data science. Due to a lack of information about the right technologies, those in charge avoid making a decision. There is a case to be made for building a multilingual team. Nevertheless, I would like to highlight the advantages of choosing a technology stack during the conceptualization of a data team.
Technology Repaints the Payment Landscape
Across the globe, BCG predicts a time of “disruption and opportunity” driven by digital technologies that will require the existing credit card system to prove that it’s better than its new competition. “The smartphone is the catalyst for a lot of change in this industry,” says Dana Stalder, a venture capitalist with Matrix Partners and a former eBay and PayPal executive now on the board of Poynt, which recently introduced a smart credit card terminal. Venture capitalists invested over $2 billion in payment technology firms between January 2013 and June 2014, according to the data tracking firm CB Insights.
Microsoft throws down the gauntlet in business intelligence
James Phillips, Microsoft’s general manager for business intelligence, said the company has already had tens of thousands of organizations sign up for PowerBI since it became available in February 2014, and that CEO Satya Nadella opens up a PowerBI dashboard every morning to track certain metrics. ... Phillips said the business intelligence market is presently in its third wave. The first wave was technical and database-centric. The second wave was about self service, defined first by Excel and, over the past few years, by Tableau’s eponymous software. The third wave, he said, takes self service a step further in terms of ease of use and all but eliminates the need for individual employees to track down IT before they can get something done.
How Connected Cars Have Established A New Ecosystem Powered By IoT
The IoT-enabled “connected car” turns the vehicle itself into a hub for an entire ecosystem of connected services that offer consumers a wealth of benefits including enhanced safety and security, a richer user experience and a new suite of product offerings. From the manufacturer’s perspective, this also helps establish an ongoing customer relationship as well as incremental revenue streams over the life of the vehicle. Over-the-air (OTA) software updates in cars are very similar to the software updates that occur in smartphones. Any software update for a vehicle’s connected services is done wirelessly OTA, keeping the OEM in contact with the vehicle but removing the need for a dealership visit.
Big Data Processing with Apache Spark – Part 1: Introduction
Spark allows programmers to develop complex, multi-step data pipelines using directed acyclic graph (DAG) pattern. It also supports in-memory data sharing across DAGs, so that different jobs can work with the same data. Spark runs on top of existing Hadoop Distributed File System (HDFS) infrastructure to provide enhanced and additional functionality. It provides support for deploying Spark applications in an existing Hadoop v1 cluster (with SIMR – Spark-Inside-MapReduce) or Hadoop v2 YARN cluster or even Apache Mesos. We should look at Spark as an alternative to Hadoop MapReduce rather than a replacement to Hadoop.
A Historical Look at Enterprise Architecture with John Zachman
According to Zachman, Walker created a methodology for defining processes as separate entities from the organizational structure. Walker came out to Los Angeles, where Zachman and ARCO were based to help provide guidance on the merger. Zachman recalls Walker telling him that the key to defining the systems for Enterprise purposes was in the data, not necessarily the process itself. In other words, the data across the company needed to be normalized so that they could maintain visibility into the assets and structure of the enterprise. “The secret to this whole thing lies in the coding and the classification of the data,” Zachman recalled Walker saying. Walker’s methodology, he said, began by classifying data by its existence not by its use.
Increasingly, enterprise architecture looks outward
From a customer-facing perspective, EAs are now getting intimately involved in planning and managing digital strategies, along with existing internal systems. Oliver Bossert, Chris Ip, and Jürgen Laartz, all with McKinsey, point out that many organizations have extensive legacy systems wired into their organizations, yet are challenged with getting on the digital track as fast as possible. In a new post, they recommend organizations adopt a "two-speed IT architecture" that will meet the needs of planning back-end systems of record with digital front ends. Such a two-speed strategy would consist of "a fast-speed, customer-centric front end running alongside a slow-speed, transaction-focused legacy back end," the analysts explain.
Quote for the day:
"People ask the difference between a leader and a boss. The leader leads, and the boss drives." -- Theodore Roosevelt
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