There’s no denying now that automation will rule our future and data science will direct the path towards automation. An increasing number of data scientists will be employed to help companies extract meaning out of pools of data and new discoveries will be made based on such inferences. That future, surprisingly, isn’t that far from now – the latest developments in data science are testimonials to that. Even as we speak, thousands of data scientists are engaging in new data discoveries and leading the world towards a more data driven future. The following articles capture those trends and influences aptly. Keep reading.
Hotwiring Data Science: AIOps and the Evolution of DevOps for Big Data
Enterprises can help data science teams to build and operate data analytics platform by intercepting and implementing data patterns. Product development teams often face challenges while integrating new models of data analytics into existing applications. Similarly, due to the lack of proper analytics platform, data scientists also struggle to get the most out of ill-formed infrastructures. To help enterprises bridge the gap between data science expectations and real developments, development teams are using AIOps or AI for IT operations. AIOps practices focus on optimising model consumption and data scientist productivity by identifying DevOps patterns that answer AIOps challenges.
DoE Pours $27.6 million into Data Science Research and Development
“The rapid evolution of artificial intelligence, machine learning, and other data science techniques is creating new opportunities for advances in chemistry and material sciences,” said U.S. Secretary of Energy Rick Perry. With this in mind, the US Department of Energy (DOE) has announced $27.6 million funding for targeted research in data science to encourage and aid discovery in chemistry and material sciences. The funding will be provided over the next three years to help a smooth execution of the data science research. This research will propel discoveries in predictive understanding of materials and development of  new alloys, superconductors, catalysts and more. This financial grant towards data science research is expected to have a significant impact on energy production and delivery.
Five Factors Shaping Data Science
The key challenges in the path of data science evolution are quite a few, but that’s not to say that the solutions are not effective. A survey result of 2019 pointed out that 80% of companies have faced stagnation of data science project. These stalled projects have resulted in the waste of resources that could have used elsewhere. Whether it is the shortage of data science talents, lack of actionable data, or complex operational processes, organisations are meeting the challenges of data science projects with innovative solutions to compete in the new AI-driven economy.
Meet Berkeley’s New Data Science Leader
Former Microsoft technical fellow and managing director, Jennifer Tour Chayes will be becoming UC Berkeley’s inaugural associate provost for the department of data science and information and Dean of the School of information. Chayes, a leader in the field of network science, has devoted much of her time studying the ethics of data science and believes that the ethical issues which challenge the world of data science can be addressed by designing algorithms that mitigate biases in data set. 
Welsh University to Study Big Data Science and Offshore Wind
The Welsh Bangor University has secured a GBP of 4.6 million EU fund to fuel the research for low carbon energy systems which includes offshore wind. Data science inferences and studies will be used for deriving the results for energy efficient options. Joint research between Welsh and international organisations and businesses will be further conducted for the new Smart Efficient Energy Centre. The research will focus on new cyberinfrastructure and digital systems to increase the volume and speed of data analytics. The SEEC will become an international hub of excellence in data science research and contribute significantly towards the growth of low carbon energy sectors.
For more digests on data science, watch this space!



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