The Ever-Increasing Importance of Predictive Analytics
Pretty much anywhere you look, you can find countless examples of how this trend is manifesting itself. As just one, Forbes recently reported that Google is making numerous changes to its Google Analytics platform and a number of other search guidelines and algorithms, which will have a colossal impact on the operations of content creators in 2014. However, few things in the big data and analytics space are likely to have the overall weight that predictive analytics are expected, by many experts, to possess.
Tablets Get More Sophisticated, with Bigger Screens, Dual OSes and Car Access
German car maker Audi unveiled an Android device that it plans to bundle with its cars. The Audi Smart Display connects to a car via Bluetooth and can be used to remotely access and control the vehicle's music, radio, and navigation systems. The 10-inch tablet can also become a typical Android device with access to the Google Play app store. Audi is calling the tablet a next-generation in-car entertainment device that Audi buyers can choose to purchase as an additional feature. However, the company wouldn't name a ship date, only saying the device would arrive in the near future.
The Relationships between MOOD/QMOOD Metrics and External Software Quality Attributes
Empiricalstudies have been conducted to evaluate these metrics as indicators of external software quality attributes (ESQAs). However,there has been no attempt to systematically review and report these empirical evidences. To identify the relation ofMOOD/QMOOD metrics with ESQAs, we have performed a systematic review of empirical evidences published in the literaturethat support or reject MOOD/QMOOD metrics as indicators of ESQAs. Our search strategy identified 413 papers, out of which15 papers were identified as reporting empirical evidence showing relation between CK metrics and ESQAs.
Using Scenario-Based Architecture Analysis to Inform Code Quality Measures
Scenario-based architecture analysis offers a broad understanding of how a software-reliant system evolves over time and can form a basis for assessing the amount of rework that may be necessary in the foreseeable future. Using the architectural risks identified during scenario-based architecture analysis, we clarified the level of system decomposition where code quality metrics reveal relevant information
Reasoning and Improving on Software Resilience against Unanticipated Exceptions
Exceptions are widely used in prac- tice [6]. To us, the resilience against exceptions is the ability to correctly handle exceptions that were never foreseen at speciļ¬cation time neither encountered during development. Our motivation is to help the developers to understand and improve the resilience of their applications. This sets a three-point research agenda: (RQ#1) What does it mean to specify anticipated exceptions? (RQ#2) How to characterize and measure resilience against unantic- ipated exceptions? (RQ#3) How to put this knowledge in action to improve the resilience?
The Internet of Things outlook for 2014: Everything connected and communicating
IoT isn't just a fancy buzzword that describes how your refrigerator can let you know when you need to replace your spoiling milk or your rotting vegetables (although it can), it is so much more. How much more is only left to your imagination and to your budget. You can do as little or as much with IoT as you want. For example, if you operate food distribution business, you could install sensors in your trucks that send temperature, humidity, and dock-to-dock travel times back to your home office for analysis.
Naming and Classifying: Text Analysis Vs. Text Analytics
Analysis is an examination of structure, composition, and meaning that provides insight to advance some purpose. Analysis may be heuristic, informal, and/or qualitative. Contrast with analytics, which is algorithmic rather than heuristic. I define analytics as the systematic application of numerical and statistical methods that derive and deliver quantitative information, whether in the form of indicators, tables, or visualizations. Analytics is formal and repeatable.
The Future of Business Intelligence: An Impending Realization
What once appeared as two opposing trends that could potentially cancel each other out has merged into a synthesis in which formal education in the field – in addition to developments in automation, Data Discovery tools, Cloud computing and Big Data – is readily used to simplify the process of leveraging BI for laymen. BI’s crossroads has become a solitary path paved by the consumerization of (and burgeoning familiarity and comfort with) IT, which Gartner describes as “how enterprises will be affected, and how they can take advantage of new technologies and models that originate and develop in the consumer space, rather than in the enterprise IT sector.”
Windows Azure Security Guidance
In cloud applications more responsibility lays on the shoulders of the application developers to design, develop, and maintain their cloud applications to high security standards to keep attackers at bay. Consider the following diagram (from J.D. Meier's Windows Azure Security Notes PDF): notice how the infrastructure part is being addressed by the cloud provider--in our case by Windows Azure--leaving more security work to the application developers:
Data Integrity, Physical Security and REST APIs Contribute to Tape's Ongoing Relevance
Other benefits which tape still holds strong are its security and reliability. Data backed up to tape is typically more secure than data stored on disk or on the cloud because, in part, tape can make data more difficult to access and then retrieve. The average hacker is more likely to spend time trying to hack data stored in a cloud or on disk than to go to the trouble of breaking into a storage facility where tape backups are stored, retrieve those tapes, load them into a tape library, and then go through them linearly to find and access the data they store.
Quote for the day:
"There is only one thing more painful than learning from experience and that is not learning from experience." -- Archibald McLeish
Pretty much anywhere you look, you can find countless examples of how this trend is manifesting itself. As just one, Forbes recently reported that Google is making numerous changes to its Google Analytics platform and a number of other search guidelines and algorithms, which will have a colossal impact on the operations of content creators in 2014. However, few things in the big data and analytics space are likely to have the overall weight that predictive analytics are expected, by many experts, to possess.
German car maker Audi unveiled an Android device that it plans to bundle with its cars. The Audi Smart Display connects to a car via Bluetooth and can be used to remotely access and control the vehicle's music, radio, and navigation systems. The 10-inch tablet can also become a typical Android device with access to the Google Play app store. Audi is calling the tablet a next-generation in-car entertainment device that Audi buyers can choose to purchase as an additional feature. However, the company wouldn't name a ship date, only saying the device would arrive in the near future.
Empiricalstudies have been conducted to evaluate these metrics as indicators of external software quality attributes (ESQAs). However,there has been no attempt to systematically review and report these empirical evidences. To identify the relation ofMOOD/QMOOD metrics with ESQAs, we have performed a systematic review of empirical evidences published in the literaturethat support or reject MOOD/QMOOD metrics as indicators of ESQAs. Our search strategy identified 413 papers, out of which15 papers were identified as reporting empirical evidence showing relation between CK metrics and ESQAs.
Using Scenario-Based Architecture Analysis to Inform Code Quality Measures
Scenario-based architecture analysis offers a broad understanding of how a software-reliant system evolves over time and can form a basis for assessing the amount of rework that may be necessary in the foreseeable future. Using the architectural risks identified during scenario-based architecture analysis, we clarified the level of system decomposition where code quality metrics reveal relevant information
Reasoning and Improving on Software Resilience against Unanticipated Exceptions
Exceptions are widely used in prac- tice [6]. To us, the resilience against exceptions is the ability to correctly handle exceptions that were never foreseen at speciļ¬cation time neither encountered during development. Our motivation is to help the developers to understand and improve the resilience of their applications. This sets a three-point research agenda: (RQ#1) What does it mean to specify anticipated exceptions? (RQ#2) How to characterize and measure resilience against unantic- ipated exceptions? (RQ#3) How to put this knowledge in action to improve the resilience?
The Internet of Things outlook for 2014: Everything connected and communicating
IoT isn't just a fancy buzzword that describes how your refrigerator can let you know when you need to replace your spoiling milk or your rotting vegetables (although it can), it is so much more. How much more is only left to your imagination and to your budget. You can do as little or as much with IoT as you want. For example, if you operate food distribution business, you could install sensors in your trucks that send temperature, humidity, and dock-to-dock travel times back to your home office for analysis.
Naming and Classifying: Text Analysis Vs. Text Analytics
Analysis is an examination of structure, composition, and meaning that provides insight to advance some purpose. Analysis may be heuristic, informal, and/or qualitative. Contrast with analytics, which is algorithmic rather than heuristic. I define analytics as the systematic application of numerical and statistical methods that derive and deliver quantitative information, whether in the form of indicators, tables, or visualizations. Analytics is formal and repeatable.
The Future of Business Intelligence: An Impending Realization
What once appeared as two opposing trends that could potentially cancel each other out has merged into a synthesis in which formal education in the field – in addition to developments in automation, Data Discovery tools, Cloud computing and Big Data – is readily used to simplify the process of leveraging BI for laymen. BI’s crossroads has become a solitary path paved by the consumerization of (and burgeoning familiarity and comfort with) IT, which Gartner describes as “how enterprises will be affected, and how they can take advantage of new technologies and models that originate and develop in the consumer space, rather than in the enterprise IT sector.”
Windows Azure Security Guidance
In cloud applications more responsibility lays on the shoulders of the application developers to design, develop, and maintain their cloud applications to high security standards to keep attackers at bay. Consider the following diagram (from J.D. Meier's Windows Azure Security Notes PDF): notice how the infrastructure part is being addressed by the cloud provider--in our case by Windows Azure--leaving more security work to the application developers:
Data Integrity, Physical Security and REST APIs Contribute to Tape's Ongoing Relevance
Other benefits which tape still holds strong are its security and reliability. Data backed up to tape is typically more secure than data stored on disk or on the cloud because, in part, tape can make data more difficult to access and then retrieve. The average hacker is more likely to spend time trying to hack data stored in a cloud or on disk than to go to the trouble of breaking into a storage facility where tape backups are stored, retrieve those tapes, load them into a tape library, and then go through them linearly to find and access the data they store.
Quote for the day:
"There is only one thing more painful than learning from experience and that is not learning from experience." -- Archibald McLeish
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