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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif
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Social Media and Mobile Technology for Health care

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Internet of Things Tutorial
(People also click these jobs to 
know skill set and to apply 
even from your phone!!)
The ubiquity of mobile phone accessibility around the world is increasing. Worldwide the number of mobile phones in use grew from fewer than 1 billion in 2000 to around 6 billion in 2012. Recent estimates conclude that over 75% of the world' s population have access to a mobile phone (World Bank, 2012).

Globally, there has been a rapid rise in the use of smart phones by consumers with over 1 billion Smart Phones subscribers (Approximately 30% of smartphone users are likely to use wellness apps by 2015, (Bjornland, Goh, Haanæs, Kainu, & Kennedy, 2012) with more than 30 billion mobile applications being downloaded in 2011 (World Bank, 2012).

Along with this increase in penetration, there has been a significant increase in the development and deployment of mobile software applications across multiple computing platforms (e.g. smart phones, tablets and laptops). The most popular of these include Apple's iOS and Google's Android software. Both were designed for use with touch screen mobile devices such as iPhones.

Today, there are a plethora of differing types of software applications that have been made available for use with the iOS and Android platforms. Software applications written for mobile or smart phones serve a range of purposes and uses, including; business, financial, educational, entertainment, gaming, lifestyle, health and fitness, news, music, photography, productivity, reference, graphics and design, developer tool, medical and health care consumer applications.
More recently, there has emerged significant interest in health care applications written for mobile phones. Mobile phone software applications are of particular interest because of their ability (in some cases) to improve lifestyle habits in well individuals and improve health outcomes in the chronically ill (Katz, Mesfin, & Barr, 2012).

In conjunction with this there has emerged a significant growth in the number of consumers that are downloading these health specific software applications for self-use (Kay, Santos, & Takane, 2011). Research suggests that mobile phone users use differing types of software applications in conjunction with their smart phones and their use of specific software applications may be role dependent. For example, research has found that physicians and other health care professionals tend to use mobile health applications that differ from those used by patients or members of the general public.

Physicians and health professionals are more likely to use mobile software applications that provide them with access to references to health care information (e.g. guidelines, information found in journal articles). These applications provide information to health professionals (i.e. they allow health professionals to review evidence-based research) that can be used in their clinical decision making. Unlike health care consumers that input data into mobile health applications, health professionals are less likely to employ mobile applications in the process of collecting data about patients. This may be because health professionals may perceive there to be privacy and security issues associated with collecting, transmitting and storing patient data via a mobile device (Jones, Hook, Park, & Scott, 2011).

As well, mobile phone applications present a potential risk for public health as some software applications have been questioned in regards to their clinical efficacy and other such software applications have been noted to induce technology-induced errors. Technology induced errors are errors made by software/hardware users that "arise from the: design and development of a technology; implementation and customisation of a technology; and interactions between the operation of a new technology and the new work processes that arise from the technology's use" (Borycki & Kushniruk, 2008).

Therefore, even as some software applications have been shown to improve consumer health and wellness, there have emerged concerns about the quality of these applications, the privacy and confidentiality of the information captured by these software applications (Spiekermann & Lorrie, 2009) and the ability of the technology to introduce technology-induced errors (Borycki & Kushniruk, 2008). This has led to calls by some researchers to achieve a balance between patient safety and innovation in mobile application development with the intent that no harm should occur to the general public (Barton, 2012) and for a deep integration of consumers' perspectives into the development of applications. More user centric applications for Smart Phones are needed (Jones et al., 2011).

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