Astera ReportMiner vs. AWS Data Pipeline

Astera ReportMiner is well suited for those who work with EMR Data or business operations data where different platforms may report on similar data but not everything is the same between the different systems and how they export their data. It works especially well when systems can't edit their exports so you need to clean up data a lot before they are combined into a single file. It is less appropriate a solution when you are trying to combine large data, let's say thousands of files and need some sort of platform to deduce analytic patterns out of it. This is more used for data preparedness rather than big data analysis. This may have changed with recent updates, however they do not do a good job of updating customers on new releases so keeping track of their developments is something worth doing if data management is an important part of your/your company's role.

AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.

Incentivized

• ReportMiner's OCR accuracy is flawless to my experience. I use the program to pull values from check details, and have yet to find an error.
• ReportMiner's interface is easy to learn. I never even got formal training on the program. I watched some YouTube videos and learned as I went.
• ReportMiner training personnel is very knowledgeable and quick to respond. Anytime I ran into a problem I could not figure out on my own, they would get back with me within a half a day.

• Helps you easily create complex data processing workloads
• Fault tolerant
• Highly available

Incentivized

• Could provide some features to help with advanced analytics for big data. (i.e. larger data sets)
• Too much clutter on their Youtube page, they should highlight the tutorials so they are easier to find for new users. Get rid of old tutorial video playlists so the organization is clean and up to date.
• Have sales rep follow up with customers to offer product updates, new product releases, and do check ins to see if customers have suggestions for feature improvement.

• Pipeline Stuck in Pending Status
• Pipeline Component Stuck in Waiting for Runner Status
• EMR Cluster Fails With Error

Incentivized

It is the best way to get a multi line record from pdf to Excel in one row.

I have never actually used another program like ReportMiner. Before I was just using PDF viewers such as Adobe that had OCR capabilities. I would have to select a range of numbers and copy and paste to Excel. It was tedious, slow, and sometimes error prone. I chose to learn ReportMiner because it saves me at least 4 times the amount of time I would have to use by copy and pasting.

AWS data pipelines are easy to use over data factory for data engineers

Incentivized

• Efficient and automated data extraction. Saves time and resources.
• User-friendly interface and good documentation. It is therefore easiest to learn and apply in a short time.
• Documents, which have various formats of data tables or arrangement, needed a lot of manual fixing. So it required a lot of time for validation and quality control.

• Easy to use
• Data engineers are able to create the data pipelines quickly and effectively
• Scalable and Fault tolerant

Incentivized