One of our customers said: Our small mining operation needed to go from paper based process to digital forms. At first, Google forms allowed us to use this Web-based platform that lets individuals and businesses of all sizes build customizable forms to conduct surveys and generate real-time response charts.
We saw that a small sample of our field workers quickly adopted the new way of working.
Step 1: accomplished.
Now unto step 2.
How do we deploy this unto our whole team? We needed email notifications, offline response collection when without wifi on the field. Our CIO and his director of operations needed deep data and trends analysis as well. Our inspectors, when doing their audits, needed to capture approx. 25 high definition pictures, some audio notes and a video which wasn't really possible with google forms.
So, we can 100% credit the use of google forms to our transition towards a paperless process, but as we navigated saashub.com a little more, we were able to discover a world of alternatives. We strongly suggest to start using google forms before undergoing a big implementation plan towards such enterprise level inspection tools like nspek or even cheaper solutions like prontoforms.
I am not sure if we would start with google's solution first if we would to do this digital transformation all over, but it did allow us to discover it's limits pretty quickly.
At some point, we needed custom fields and functions, and none of us was able to code, so the nSpek training that comes with the application definitely sets it's self apart, giving us full autonomy.
Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Survey Monkey - Create and publish online surveys in minutes, and view results graphically and in real time. SurveyMonkey provides free online questionnaire and survey software.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Typeform - Create beautiful, next-generation online forms with Typeform, the form & survey builder that makes asking questions easy & human on any device. Try it FREE!
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Qualtrics - Qualtrics is the most trusted research platform, helping brands make crucial business decisions. From surveys to insights to action.