DEV Community: Yamika Perera

The future of tech jobs: prompt engineering

Yamika Perera — Sat, 11 Mar 2023 19:27:50 +0000

The world of technology is constantly evolving, and with it, the job market is also changing rapidly. One of the most promising fields in the tech industry is prompt engineering. With the increasing demand for prompt engineering, it is expected to become a crucial job in the future of technology.

Prompt engineering is the process of designing, developing, and maintaining systems that can respond to data in real time. These systems are used in various industries, including finance, healthcare, and transportation, to name a few. Prompt engineering jobs require a unique skill set that combines software engineering, data science, and mathematics. With these skills, prompt engineers can develop systems that can process large amounts of data in real time, detect anomalies, and generate insights that can be used to make informed decisions.

One of the main reasons why prompt engineering is becoming more important is the growth of the Internet of Things (IoT) and the increasing amount of data generated by various devices. IoT devices generate vast amounts of data that need to be processed in real-time to provide valuable insights. Prompt engineering is the key to developing systems that can handle this data in real time and generate insights that can be used to improve products, services, and processes.

The demand for prompt engineering is also driven by the increasing importance of artificial intelligence (AI) and machine learning (ML) in various industries. These technologies require the real-time processing of data to make accurate predictions and provide actionable insights. Prompt engineering is essential in developing AI and ML systems that can process data in real time and generate insights that can be used to improve business operations.

Another factor contributing to the growth of prompt engineering jobs is the increasing need for cybersecurity. Prompt engineers play a crucial role in developing secure systems that can detect and respond to cyber threats in real time. With the increasing frequency and sophistication of cyberattacks, the demand for prompt engineering jobs is expected to increase in the coming years.

The future of prompt engineering looks promising, with new technologies and applications emerging every day. The rise of 5G technology, for example, will create new opportunities for engineers to develop systems that can handle the high speeds and low latencies of 5G networks. In addition, the growth of edge computing will prompt engineers to develop systems that can process data at the edge of the network, closer to where the data is generated.

The growing importance of prompt engineering has also led to the emergence of new tools and platforms that can help prompt engineers develop and maintain real-time systems. These tools include real-time data processing frameworks like Apache Kafka and Apache Flink, as well as real-time analytics platforms like Apache Druid and ElasticSearch. These tools and platforms provide prompt engineers with the necessary tools to develop, test, and deploy real-time systems quickly and efficiently.

The demand for prompt engineering jobs is not limited to a particular industry or location. Prompt engineers are needed in various industries, including finance, healthcare, transportation, energy, and more. The growing importance of real-time data processing and the increasing amount of data generated by various devices make prompt engineering a crucial job in the future of technology.

In conclusion, prompt engineering is a rapidly growing field in the tech industry, with increasing demand for skilled professionals. The rise of IoT, AI, and ML, as well as the increasing need for cybersecurity, are some of the factors driving the growth of prompt engineering jobs. The future of prompt engineering looks promising, with new technologies and applications emerging every day. For anyone interested in pursuing a career in technology, prompt engineering is a field that offers exciting opportunities and challenges.

ArcGIS Survey123 Feature Report Generation with ArcPY Module

Yamika Perera — Tue, 20 Apr 2021 06:30:07 +0000

ArcGIS is a geographical information system for working with maps and geographic information. ArcGIS was developed by Environmental Systems Research Institute aka ESRI. ArcGIS platforms initial release was 21 years earlier. ArcGIS is used for creating and using maps, compiling geographic data, analyzing mapped information, sharing and discovering geographic information, using maps and geographic information in a range of applications, and managing geographic information in a database.
Inside the ArcGIS application bundle, we have so many tools for data collection and data analytics. Survey123 is a very useful app to collect data from the field and it’s very easy to configure. Once we collected our data using survey123 we can generate reports and analyse data using inbuilt web gis tools. The use of web gis tools is very time consuming and hard to work with a big data set. So the ArcGIS have its python modules to work and generate reports with feature layers.
We can use the ArcGIS python module to access those inbuilt functionalities.

import arcgis
from arcgis.gis import GIS

now we have imported all the modules we need to get going.
next, we have to log in to the ArcGIS. I’m writing this code inside my main function.

def main():
gis = GIS(username="USERNAME", password="PASSWORD")
The next step is to access our survey manager.
survey_manager = arcgis.apps.survey123.SurveyManager(gis)
For future steps, we need to find our survey id.
surveys = survey_manager.surveys
p = [print(s.properties['id'], s.properties['title']) for s in surveys]

this code will print the survey id and its title so you can find your relevant survey id for further steps. The next step is to access our survey using survey id.

survey_by_id = survey_manager.get("Survey_ID")

To ensure we have accessed our survey use the next code to print properties of the survey.

print(survey_by_id.properties)

This code will print the survey properties and the next step is to access our template to generate reports.

templates = survey_by_id.report_templates

this code will output a list and if we have uploaded a new template it will stay in templates[1]. The ArcGIS default template is templates[0]
Finally, we can generate our report. You can replace where parameter with your own column name and data to query a record and generate reports.

report = survey_by_id.generate_report(templates[1], where="column=data")

This will generate your report in Docx format and download it into C:\Users\Admin\AppData\Local\Temp\ folder.
For further customizations, you can use a dynamic where parameter.
ex:
Query_String = input("Enter Query String ")
Where_Parameter = f"Field_Name = {Query_String}"
report = survey_by_id.generate_report(templates[1], where=Where_Parameter)

Hope you got an idea about feature report generation in Survey123. Thank you!

5 Most useful websites for web designers you wish you found earlier!

Yamika Perera — Mon, 20 Apr 2020 16:16:39 +0000

Looking for help with your web design business? Check out these really helpful websites that can make the web design process a lot faster and easier for web designers and web developers.

https://tinyjpg.com When we talk about web site speed biggest fact is images. If you have integrated heavy images it will take more time to load your page. Tinyjpg.com providing the images compress service up to 70% per image, you can reduce image size while keeping the quality as it is. You have to just upload the picture to their website, they will compress the image for you. When you upload a JPEG file, the image is analyzed. Textures, patterns and colors are automatically identified. The encoder creates an optimally compressed JPEG file based on that information. The final result is compared with the original and fine-tuned. Distracting JPEG artifacts are minimized without big sacrifices in file size. Unnecessary metadata is stripped as well. You will get an optimal image, every time!
https://woorank.com Search engine optimization is a broad area when it comes to web developing. Mainly you have to consider about on page seo and off page seo. Woorank.com is a tool for analyzing both in one place. It indicates your ups and downs. Very easy to use and you can check your website seo status free of charge.
https://gtmetrix.com Gtmetrix.com is a tool for check your website performance. It’s giving a score based on your website performance. This tool is also free to use. You can test any number of websites using this website. Normally it’s checking our server status, image optimization, caching problems and minifying the resources, and also number of request which we have sent to the server. Really helpful tool to identify your drawbacks. It’s also suggesting things to improve your website performance.
https://pixabay.com This website contains a large collection of Photos, Illustrations, Vectors, Videos and Music. Pixabay is a vibrant community of creatives, sharing copyright free images and videos. All contents are released under the Pixabay License, which makes them safe to use without asking for permission or giving credit to the artist — even for commercial purposes. All content on Pixabay can be used for free for commercial and noncommercial use across print and digital, except in the cases mentioned in “What is not allowed”. Attribution is not required. Giving credit to the contributor or Pixabay is not necessary but is always appreciated by our community. You can make modifications to content from Pixabay.
https://developers.google.com/speed/pagespeed/insights/ PageSpeed Insights reports on the performance of a page on both mobile and desktop devices, and provides suggestions on how that page may be improved. PSI provides both lab and field data about a page. Lab data is useful for debugging performance issues, as it is collected in a controlled environment. However, it may not capture real-world bottlenecks. Field data is useful for capturing true, real-world user experience — but has a more limited set of metrics. See How to Think about Speed Tools for more information on the 2 types of data.